[{"id":"24023","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"dza_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Algeria","resolution":"100","type":"Covariates","file_html":""},{"id":"24026","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ago_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Angola","resolution":"100","type":"Covariates","file_html":""},{"id":"24071","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ben_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Benin","resolution":"100","type":"Covariates","file_html":""},{"id":"24041","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"bwa_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Botswana","resolution":"100","type":"Covariates","file_html":""},{"id":"24249","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"bfa_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Burkina Faso","resolution":"100","type":"Covariates","file_html":""},{"id":"24050","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"bdi_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Burundi","resolution":"100","type":"Covariates","file_html":""},{"id":"24053","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"cmr_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Cameroon","resolution":"100","type":"Covariates","file_html":""},{"id":"24054","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"cpv_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Cape Verde","resolution":"100","type":"Covariates","file_html":""},{"id":"24056","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"caf_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Central African Republic","resolution":"100","type":"Covariates","file_html":""},{"id":"24058","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"tcd_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Chad","resolution":"100","type":"Covariates","file_html":""},{"id":"24061","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"com_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Comoros","resolution":"100","type":"Covariates","file_html":""},{"id":"24120","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"civ_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Cote d'Ivoire","resolution":"100","type":"Covariates","file_html":""},{"id":"24091","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"dji_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Djibouti","resolution":"100","type":"Covariates","file_html":""},{"id":"24064","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"cod_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"DRC","resolution":"100","type":"Covariates","file_html":""},{"id":"24243","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"egy_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Egypt","resolution":"100","type":"Covariates","file_html":""},{"id":"24077","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"gnq_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Equatorial Guinea","resolution":"100","type":"Covariates","file_html":""},{"id":"24079","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"eri_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Eritrea","resolution":"100","type":"Covariates","file_html":""},{"id":"24224","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"swz_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Eswatini","resolution":"100","type":"Covariates","file_html":""},{"id":"24078","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"eth_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Ethiopia","resolution":"100","type":"Covariates","file_html":""},{"id":"24092","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"gab_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Gabon","resolution":"100","type":"Covariates","file_html":""},{"id":"24094","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"gmb_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Gambia","resolution":"100","type":"Covariates","file_html":""},{"id":"24097","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"gha_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Ghana","resolution":"100","type":"Covariates","file_html":""},{"id":"24105","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"gin_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Guinea","resolution":"100","type":"Covariates","file_html":""},{"id":"24189","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"gnb_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Guinea-Bissau","resolution":"100","type":"Covariates","file_html":""},{"id":"24125","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ken_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Kenya","resolution":"100","type":"Covariates","file_html":""},{"id":"24132","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"lso_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Lesotho","resolution":"100","type":"Covariates","file_html":""},{"id":"24134","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"lbr_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Liberia","resolution":"100","type":"Covariates","file_html":""},{"id":"24135","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"lby_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Libya","resolution":"100","type":"Covariates","file_html":""},{"id":"24140","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mdg_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Madagascar","resolution":"100","type":"Covariates","file_html":""},{"id":"24141","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mwi_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Malawi","resolution":"100","type":"Covariates","file_html":""},{"id":"24144","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mli_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Mali","resolution":"100","type":"Covariates","file_html":""},{"id":"24147","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mrt_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Mauritania","resolution":"100","type":"Covariates","file_html":""},{"id":"24148","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mus_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Mauritius","resolution":"100","type":"Covariates","file_html":""},{"id":"24062","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"myt_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Mayotte","resolution":"100","type":"Covariates","file_html":""},{"id":"24155","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mar_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Morocco","resolution":"100","type":"Covariates","file_html":""},{"id":"24156","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"moz_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Mozambique","resolution":"100","type":"Covariates","file_html":""},{"id":"24158","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"nam_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Namibia","resolution":"100","type":"Covariates","file_html":""},{"id":"24170","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ner_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Niger","resolution":"100","type":"Covariates","file_html":""},{"id":"24171","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"nga_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Nigeria","resolution":"100","type":"Covariates","file_html":""},{"id":"24063","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"cog_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Rep. Congo","resolution":"100","type":"Covariates","file_html":""},{"id":"24193","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"reu_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"R\u00e9union","resolution":"100","type":"Covariates","file_html":""},{"id":"24195","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"rwa_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Rwanda","resolution":"100","type":"Covariates","file_html":""},{"id":"24197","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"shn_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Saint Helena, Ascension and Tristan da Cunha","resolution":"100","type":"Covariates","file_html":""},{"id":"24205","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"stp_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Sao Tome and Principe","resolution":"100","type":"Covariates","file_html":""},{"id":"24207","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"sen_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Senegal","resolution":"100","type":"Covariates","file_html":""},{"id":"24209","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"syc_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Seychelles","resolution":"100","type":"Covariates","file_html":""},{"id":"24210","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"sle_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Sierra Leone","resolution":"100","type":"Covariates","file_html":""},{"id":"24215","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"som_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Somalia","resolution":"100","type":"Covariates","file_html":""},{"id":"24216","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"zaf_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"South Africa","resolution":"100","type":"Covariates","file_html":""},{"id":"24219","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ssd_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"South Sudan","resolution":"100","type":"Covariates","file_html":""},{"id":"24220","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"sdn_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Sudan","resolution":"100","type":"Covariates","file_html":""},{"id":"24248","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"tza_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Tanzania","resolution":"100","type":"Covariates","file_html":""},{"id":"24230","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"tgo_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Togo","resolution":"100","type":"Covariates","file_html":""},{"id":"24235","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"tun_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Tunisia","resolution":"100","type":"Covariates","file_html":""},{"id":"24240","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"uga_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Uganda","resolution":"100","type":"Covariates","file_html":""},{"id":"24221","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"esh_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Western Sahara","resolution":"100","type":"Covariates","file_html":""},{"id":"24256","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"zmb_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Zambia","resolution":"100","type":"Covariates","file_html":""},{"id":"24217","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"zwe_esaccilc_dst_water_100m_2000_2012.png","continent":"Africa","country":"Zimbabwe","resolution":"100","type":"Covariates","file_html":""},{"id":"24199","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"aia_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Anguilla","resolution":"100","type":"Covariates","file_html":""},{"id":"24027","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"atg_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Antigua and Barbuda","resolution":"100","type":"Covariates","file_html":""},{"id":"24029","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"arg_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Argentina","resolution":"100","type":"Covariates","file_html":""},{"id":"24163","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"abw_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Aruba","resolution":"100","type":"Covariates","file_html":""},{"id":"24031","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"bhs_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Bahamas","resolution":"100","type":"Covariates","file_html":""},{"id":"24035","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"brb_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Barbados","resolution":"100","type":"Covariates","file_html":""},{"id":"24043","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"blz_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Belize","resolution":"100","type":"Covariates","file_html":""},{"id":"24037","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"bmu_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Bermuda","resolution":"100","type":"Covariates","file_html":""},{"id":"24039","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"bol_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Bolivia","resolution":"100","type":"Covariates","file_html":""},{"id":"24165","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"bes_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Bonaire, Sint Eustatius and Saba","resolution":"100","type":"Covariates","file_html":""},{"id":"24017","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"bra_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Brazil","resolution":"100","type":"Covariates","file_html":""},{"id":"24046","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"vgb_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"British Virgin Islands","resolution":"100","type":"Covariates","file_html":""},{"id":"24018","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"can_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Canada","resolution":"100","type":"Covariates","file_html":""},{"id":"24055","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"cym_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Cayman Islands","resolution":"100","type":"Covariates","file_html":""},{"id":"24019","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"chl_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Chile","resolution":"100","type":"Covariates","file_html":""},{"id":"24060","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"col_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Colombia","resolution":"100","type":"Covariates","file_html":""},{"id":"24066","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"cri_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Costa Rica","resolution":"100","type":"Covariates","file_html":""},{"id":"24068","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"cub_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Cuba","resolution":"100","type":"Covariates","file_html":""},{"id":"24162","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"cuw_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Cura\u00e7ao","resolution":"100","type":"Covariates","file_html":""},{"id":"24073","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"dma_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Dominica","resolution":"100","type":"Covariates","file_html":""},{"id":"24074","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"dom_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Dominican Republic","resolution":"100","type":"Covariates","file_html":""},{"id":"24075","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ecu_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Ecuador","resolution":"100","type":"Covariates","file_html":""},{"id":"24076","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"slv_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"El Salvador","resolution":"100","type":"Covariates","file_html":""},{"id":"24082","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"flk_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Falkland Islands (Malvinas)","resolution":"100","type":"Covariates","file_html":""},{"id":"24088","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"guf_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"French Guiana","resolution":"100","type":"Covariates","file_html":""},{"id":"24014","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"grl_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Greenland","resolution":"100","type":"Covariates","file_html":""},{"id":"24101","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"grd_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Grenada","resolution":"100","type":"Covariates","file_html":""},{"id":"24102","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"glp_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Guadeloupe","resolution":"100","type":"Covariates","file_html":""},{"id":"24104","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"gtm_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Guatemala","resolution":"100","type":"Covariates","file_html":""},{"id":"24106","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"guy_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Guyana","resolution":"100","type":"Covariates","file_html":""},{"id":"24107","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"hti_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Haiti","resolution":"100","type":"Covariates","file_html":""},{"id":"24110","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"hnd_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Honduras","resolution":"100","type":"Covariates","file_html":""},{"id":"24121","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"jam_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Jamaica","resolution":"100","type":"Covariates","file_html":""},{"id":"24146","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mtq_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Martinique","resolution":"100","type":"Covariates","file_html":""},{"id":"24149","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mex_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Mexico","resolution":"100","type":"Covariates","file_html":""},{"id":"24154","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"msr_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Montserrat","resolution":"100","type":"Covariates","file_html":""},{"id":"24169","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"nic_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Nicaragua","resolution":"100","type":"Covariates","file_html":""},{"id":"24181","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"pan_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Panama","resolution":"100","type":"Covariates","file_html":""},{"id":"24183","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"pry_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Paraguay","resolution":"100","type":"Covariates","file_html":""},{"id":"24184","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"per_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Peru","resolution":"100","type":"Covariates","file_html":""},{"id":"24191","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"pri_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Puerto Rico","resolution":"100","type":"Covariates","file_html":""},{"id":"24196","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"blm_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Saint Barth\u00e9lemy","resolution":"100","type":"Covariates","file_html":""},{"id":"24198","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"kna_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Saint Kitts and Nevis","resolution":"100","type":"Covariates","file_html":""},{"id":"24200","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"lca_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Saint Lucia","resolution":"100","type":"Covariates","file_html":""},{"id":"24201","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"maf_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Saint Martin","resolution":"100","type":"Covariates","file_html":""},{"id":"24202","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"spm_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Saint Pierre and Miquelon","resolution":"100","type":"Covariates","file_html":""},{"id":"24203","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"vct_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Saint Vincent and the Grenadines","resolution":"100","type":"Covariates","file_html":""},{"id":"24164","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"sxm_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Sint Maarten (Dutch part)","resolution":"100","type":"Covariates","file_html":""},{"id":"24222","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"sur_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Suriname","resolution":"100","type":"Covariates","file_html":""},{"id":"24233","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"tto_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Trinidad and Tobago","resolution":"100","type":"Covariates","file_html":""},{"id":"24238","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"tca_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Turks and Caicos Islands","resolution":"100","type":"Covariates","file_html":""},{"id":"24012","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"usa_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"United States of America","resolution":"100","type":"Covariates","file_html":""},{"id":"24013","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"vir_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"United States Virgin Islands","resolution":"100","type":"Covariates","file_html":""},{"id":"24250","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ury_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Uruguay","resolution":"100","type":"Covariates","file_html":""},{"id":"24252","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ven_esaccilc_dst_water_100m_2000_2012.png","continent":"Americas","country":"Venezuela","resolution":"100","type":"Covariates","file_html":""},{"id":"24022","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ata_esaccilc_dst_water_100m_2000_2012.png","continent":"Antarctica","country":"Antarctica","resolution":"100","type":"Covariates","file_html":""},{"id":"24042","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"bvt_esaccilc_dst_water_100m_2000_2012.png","continent":"Antarctica","country":"Bouvet Island (Bouvetoya)","resolution":"100","type":"Covariates","file_html":""},{"id":"24090","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"atf_esaccilc_dst_water_100m_2000_2012.png","continent":"Antarctica","country":"French Southern Territories","resolution":"100","type":"Covariates","file_html":""},{"id":"24108","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"hmd_esaccilc_dst_water_100m_2000_2012.png","continent":"Antarctica","country":"Heard Island and McDonald Islands","resolution":"100","type":"Covariates","file_html":""},{"id":"24083","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"sgs_esaccilc_dst_water_100m_2000_2012.png","continent":"Antarctica","country":"South Georgia and the South Sandwich Islands","resolution":"100","type":"Covariates","file_html":""},{"id":"24020","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"afg_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Afghanistan","resolution":"100","type":"Covariates","file_html":""},{"id":"24034","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"arm_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Armenia","resolution":"100","type":"Covariates","file_html":""},{"id":"24028","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"aze_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Azerbaijan","resolution":"100","type":"Covariates","file_html":""},{"id":"24032","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"bhr_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Bahrain","resolution":"100","type":"Covariates","file_html":""},{"id":"24033","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"bgd_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Bangladesh","resolution":"100","type":"Covariates","file_html":""},{"id":"24038","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"btn_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Bhutan","resolution":"100","type":"Covariates","file_html":""},{"id":"24044","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"iot_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"British Indian Ocean Territory (Chagos Archipelago)","resolution":"100","type":"Covariates","file_html":""},{"id":"24047","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"brn_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Brunei Darussalam","resolution":"100","type":"Covariates","file_html":""},{"id":"24052","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"khm_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Cambodia","resolution":"100","type":"Covariates","file_html":""},{"id":"24015","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"chn_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"China","resolution":"100","type":"Covariates","file_html":""},{"id":"24069","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"cyp_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Cyprus","resolution":"100","type":"Covariates","file_html":""},{"id":"24093","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"geo_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Georgia","resolution":"100","type":"Covariates","file_html":""},{"id":"24111","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"hkg_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Hong Kong","resolution":"100","type":"Covariates","file_html":""},{"id":"24114","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ind_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"India","resolution":"100","type":"Covariates","file_html":""},{"id":"24011","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"idn_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Indonesia","resolution":"100","type":"Covariates","file_html":""},{"id":"24115","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"irn_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Iran","resolution":"100","type":"Covariates","file_html":""},{"id":"24116","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"irq_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Iraq","resolution":"100","type":"Covariates","file_html":""},{"id":"24118","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"isr_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Israel","resolution":"100","type":"Covariates","file_html":""},{"id":"24122","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"jpn_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Japan","resolution":"100","type":"Covariates","file_html":""},{"id":"24124","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"jor_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Jordan","resolution":"100","type":"Covariates","file_html":""},{"id":"24123","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"kaz_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Kazakhstan","resolution":"100","type":"Covariates","file_html":""},{"id":"24128","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"kwt_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Kuwait","resolution":"100","type":"Covariates","file_html":""},{"id":"24129","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"kgz_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Kyrgyz Republic","resolution":"100","type":"Covariates","file_html":""},{"id":"24130","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"lao_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Lao People's Democratic Republic","resolution":"100","type":"Covariates","file_html":""},{"id":"24131","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"lbn_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Lebanon","resolution":"100","type":"Covariates","file_html":""},{"id":"24139","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mac_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Macao","resolution":"100","type":"Covariates","file_html":""},{"id":"24142","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mys_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Malaysia","resolution":"100","type":"Covariates","file_html":""},{"id":"24143","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mdv_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Maldives","resolution":"100","type":"Covariates","file_html":""},{"id":"24151","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mng_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Mongolia","resolution":"100","type":"Covariates","file_html":""},{"id":"24049","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mmr_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Myanmar","resolution":"100","type":"Covariates","file_html":""},{"id":"24160","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"npl_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Nepal","resolution":"100","type":"Covariates","file_html":""},{"id":"24126","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"prk_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"North Korea","resolution":"100","type":"Covariates","file_html":""},{"id":"24157","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"omn_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Oman","resolution":"100","type":"Covariates","file_html":""},{"id":"24180","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"pak_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Pakistan","resolution":"100","type":"Covariates","file_html":""},{"id":"24095","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"pse_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Palestinian Territory","resolution":"100","type":"Covariates","file_html":""},{"id":"24185","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"phl_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Philippines","resolution":"100","type":"Covariates","file_html":""},{"id":"24192","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"qat_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Qatar","resolution":"100","type":"Covariates","file_html":""},{"id":"24206","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"sau_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Saudi Arabia","resolution":"100","type":"Covariates","file_html":""},{"id":"24211","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"sgp_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Singapore","resolution":"100","type":"Covariates","file_html":""},{"id":"24127","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"kor_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"South Korea","resolution":"100","type":"Covariates","file_html":""},{"id":"24258","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"spr_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Spratly Islands","resolution":"100","type":"Covariates","file_html":""},{"id":"24057","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"lka_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Sri Lanka","resolution":"100","type":"Covariates","file_html":""},{"id":"24227","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"syr_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Syrian Arab Republic","resolution":"100","type":"Covariates","file_html":""},{"id":"24059","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"twn_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Taiwan","resolution":"100","type":"Covariates","file_html":""},{"id":"24228","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"tjk_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Tajikistan","resolution":"100","type":"Covariates","file_html":""},{"id":"24229","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"tha_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Thailand","resolution":"100","type":"Covariates","file_html":""},{"id":"24190","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"tls_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Timor-Leste","resolution":"100","type":"Covariates","file_html":""},{"id":"24236","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"tur_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Turkiye","resolution":"100","type":"Covariates","file_html":""},{"id":"24237","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"tkm_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Turkmenistan","resolution":"100","type":"Covariates","file_html":""},{"id":"24234","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"are_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"United Arab Emirates","resolution":"100","type":"Covariates","file_html":""},{"id":"24251","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"uzb_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Uzbekistan","resolution":"100","type":"Covariates","file_html":""},{"id":"24213","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"vnm_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Vietnam","resolution":"100","type":"Covariates","file_html":""},{"id":"24255","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"yem_esaccilc_dst_water_100m_2000_2012.png","continent":"Asia","country":"Yemen","resolution":"100","type":"Covariates","file_html":""},{"id":"24021","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"alb_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Albania","resolution":"100","type":"Covariates","file_html":""},{"id":"24025","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"and_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Andorra","resolution":"100","type":"Covariates","file_html":""},{"id":"24030","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"aut_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Austria","resolution":"100","type":"Covariates","file_html":""},{"id":"24051","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"blr_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Belarus","resolution":"100","type":"Covariates","file_html":""},{"id":"24036","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"bel_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Belgium","resolution":"100","type":"Covariates","file_html":""},{"id":"24040","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"bih_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Bosnia and Herzegovina","resolution":"100","type":"Covariates","file_html":""},{"id":"24048","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"bgr_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Bulgaria","resolution":"100","type":"Covariates","file_html":""},{"id":"24067","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"hrv_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Croatia","resolution":"100","type":"Covariates","file_html":""},{"id":"24070","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"cze_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Czech Republic","resolution":"100","type":"Covariates","file_html":""},{"id":"24072","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"dnk_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Denmark","resolution":"100","type":"Covariates","file_html":""},{"id":"24080","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"est_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Estonia","resolution":"100","type":"Covariates","file_html":""},{"id":"24081","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"fro_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Faroe Islands","resolution":"100","type":"Covariates","file_html":""},{"id":"24085","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"fin_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Finland","resolution":"100","type":"Covariates","file_html":""},{"id":"24087","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"fra_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"France","resolution":"100","type":"Covariates","file_html":""},{"id":"24096","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"deu_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Germany","resolution":"100","type":"Covariates","file_html":""},{"id":"24098","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"gib_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Gibraltar","resolution":"100","type":"Covariates","file_html":""},{"id":"24100","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"grc_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Greece","resolution":"100","type":"Covariates","file_html":""},{"id":"24245","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ggy_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Guernsey","resolution":"100","type":"Covariates","file_html":""},{"id":"24109","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"vat_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Holy See (Vatican City State)","resolution":"100","type":"Covariates","file_html":""},{"id":"24112","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"hun_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Hungary","resolution":"100","type":"Covariates","file_html":""},{"id":"24113","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"isl_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Iceland","resolution":"100","type":"Covariates","file_html":""},{"id":"24117","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"irl_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Ireland","resolution":"100","type":"Covariates","file_html":""},{"id":"24247","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"imn_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Isle of Man","resolution":"100","type":"Covariates","file_html":""},{"id":"24119","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ita_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Italy","resolution":"100","type":"Covariates","file_html":""},{"id":"24246","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"jey_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Jersey","resolution":"100","type":"Covariates","file_html":""},{"id":"24257","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"kos_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Kosovo ","resolution":"100","type":"Covariates","file_html":""},{"id":"24133","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"lva_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Latvia","resolution":"100","type":"Covariates","file_html":""},{"id":"24136","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"lie_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Liechtenstein","resolution":"100","type":"Covariates","file_html":""},{"id":"24137","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ltu_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Lithuania","resolution":"100","type":"Covariates","file_html":""},{"id":"24138","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"lux_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Luxembourg","resolution":"100","type":"Covariates","file_html":""},{"id":"24242","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mkd_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Macedonia","resolution":"100","type":"Covariates","file_html":""},{"id":"24145","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mlt_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Malta","resolution":"100","type":"Covariates","file_html":""},{"id":"24152","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mda_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Moldova","resolution":"100","type":"Covariates","file_html":""},{"id":"24150","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mco_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Monaco","resolution":"100","type":"Covariates","file_html":""},{"id":"24153","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mne_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Montenegro","resolution":"100","type":"Covariates","file_html":""},{"id":"24161","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"nld_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Netherlands","resolution":"100","type":"Covariates","file_html":""},{"id":"24174","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"nor_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Norway","resolution":"100","type":"Covariates","file_html":""},{"id":"24187","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"pol_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Poland","resolution":"100","type":"Covariates","file_html":""},{"id":"24188","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"prt_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Portugal","resolution":"100","type":"Covariates","file_html":""},{"id":"24194","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"rou_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Romania","resolution":"100","type":"Covariates","file_html":""},{"id":"24010","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"rus_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Russian Federation","resolution":"100","type":"Covariates","file_html":""},{"id":"24204","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"smr_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"San Marino","resolution":"100","type":"Covariates","file_html":""},{"id":"24208","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"srb_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Serbia","resolution":"100","type":"Covariates","file_html":""},{"id":"24212","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"svk_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Slovakia (Slovak Republic)","resolution":"100","type":"Covariates","file_html":""},{"id":"24214","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"svn_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Slovenia","resolution":"100","type":"Covariates","file_html":""},{"id":"24218","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"esp_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Spain","resolution":"100","type":"Covariates","file_html":""},{"id":"24223","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"sjm_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Svalbard & Jan Mayen Islands","resolution":"100","type":"Covariates","file_html":""},{"id":"24225","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"swe_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Sweden","resolution":"100","type":"Covariates","file_html":""},{"id":"24226","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"che_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Switzerland","resolution":"100","type":"Covariates","file_html":""},{"id":"24241","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ukr_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"Ukraine","resolution":"100","type":"Covariates","file_html":""},{"id":"24244","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"gbr_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"United Kingdom of Great Britain & Northern Ireland","resolution":"100","type":"Covariates","file_html":""},{"id":"24086","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ala_esaccilc_dst_water_100m_2000_2012.png","continent":"Europe","country":"\u00c5land Islands","resolution":"100","type":"Covariates","file_html":""},{"id":"24024","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"asm_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"American Samoa","resolution":"100","type":"Covariates","file_html":""},{"id":"24016","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"aus_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Australia","resolution":"100","type":"Covariates","file_html":""},{"id":"24065","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"cok_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Cook Islands","resolution":"100","type":"Covariates","file_html":""},{"id":"24084","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"fji_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Fiji","resolution":"100","type":"Covariates","file_html":""},{"id":"24089","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"pyf_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"French Polynesia","resolution":"100","type":"Covariates","file_html":""},{"id":"24103","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"gum_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Guam","resolution":"100","type":"Covariates","file_html":""},{"id":"24099","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"kir_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Kiribati","resolution":"100","type":"Covariates","file_html":""},{"id":"24178","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mhl_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Marshall Islands","resolution":"100","type":"Covariates","file_html":""},{"id":"24177","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"fsm_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Micronesia","resolution":"100","type":"Covariates","file_html":""},{"id":"24159","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"nru_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Nauru","resolution":"100","type":"Covariates","file_html":""},{"id":"24166","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ncl_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"New Caledonia","resolution":"100","type":"Covariates","file_html":""},{"id":"24168","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"nzl_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"New Zealand","resolution":"100","type":"Covariates","file_html":""},{"id":"24172","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"niu_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Niue","resolution":"100","type":"Covariates","file_html":""},{"id":"24173","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"nfk_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Norfolk Island","resolution":"100","type":"Covariates","file_html":""},{"id":"24175","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"mnp_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Northern Mariana Islands","resolution":"100","type":"Covariates","file_html":""},{"id":"24179","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"plw_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Palau","resolution":"100","type":"Covariates","file_html":""},{"id":"24182","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"png_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Papua New Guinea","resolution":"100","type":"Covariates","file_html":""},{"id":"24186","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"pcn_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Pitcairn Islands","resolution":"100","type":"Covariates","file_html":""},{"id":"24254","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"wsm_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Samoa","resolution":"100","type":"Covariates","file_html":""},{"id":"24045","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"slb_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Solomon Islands","resolution":"100","type":"Covariates","file_html":""},{"id":"24231","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"tkl_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Tokelau","resolution":"100","type":"Covariates","file_html":""},{"id":"24232","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"ton_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Tonga","resolution":"100","type":"Covariates","file_html":""},{"id":"24239","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"tuv_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Tuvalu","resolution":"100","type":"Covariates","file_html":""},{"id":"24176","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"umi_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"United States Minor Outlying Islands","resolution":"100","type":"Covariates","file_html":""},{"id":"24167","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"vut_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Vanuatu","resolution":"100","type":"Covariates","file_html":""},{"id":"24253","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. The value of each grid cell represents the distance (in kilometres) from its centre to the nearest inland waterbody<br\/><br\/><b>Data Source<\/b>: Lamarche, C., Santoro, M., Bontemps, S., d'Andrimont, R., Radoux, J., Giustarini, L., Brockmann, C., Wevers, J., Defourny, P. and Arino, O., 2017. 'Compilation and validation of SAR and optical data products for a complete and global map of inland\/ocean water tailored to the climate modeling community'. Remote Sensing, 9(1), 36 (<a href='https:\/\/doi.org\/10.3390\/rs9010036' target='_blank'>https:\/\/doi.org\/10.3390\/rs9010036<\/a>) \u2013 ESA (European Space Agency) CCI (Climate Change Initiative) Land Cover project led by UCLouvain, 2017: Water Bodies v4.0 (<a href='http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/' target='_blank'>http:\/\/maps.elie.ucl.ac.be\/CCI\/viewer\/<\/a>)<br\/><br\/><b>Methodology<\/b>: The geodesic distance from each grid cell centre to the nearest inland waterbody has been calculated using the haversine formula and a global gridded inland waterbody dataset to avoid edge effects at the country boundaries. The global gridded inland waterbody datasets have been created following the description in Lloyd, C. T., H. Chamberlain, D. Kerr, G. Yetman, L. Pistolesi, F. R. Stevens, A. E. Gaughan, J. J. Nieves, G. Hornby, K. MacManus, P. Sinha, M. Bondarenko, A. Sorichetta, and A. J. Tatem, 2019. 'Global Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets'. Big Earth Data (<a href='https:\/\/doi.org\/10.1080\/20964471.2019.1625151' target='_blank'>https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00644","popyear":null,"date":"2018-11-02","file_img":"wlf_esaccilc_dst_water_100m_2000_2012.png","continent":"Oceania","country":"Wallis and Futuna","resolution":"100","type":"Covariates","file_html":""}]