[{"id":"24521","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"dza_subnational_admin_2000_2020.png","continent":"Africa","country":"Algeria","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24524","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"ago_subnational_admin_2000_2020.png","continent":"Africa","country":"Angola","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24569","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"ben_subnational_admin_2000_2020.png","continent":"Africa","country":"Benin","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24539","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"bwa_subnational_admin_2000_2020.png","continent":"Africa","country":"Botswana","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24747","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"bfa_subnational_admin_2000_2020.png","continent":"Africa","country":"Burkina Faso","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24548","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"bdi_subnational_admin_2000_2020.png","continent":"Africa","country":"Burundi","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24551","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"cmr_subnational_admin_2000_2020.png","continent":"Africa","country":"Cameroon","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24552","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"cpv_subnational_admin_2000_2020.png","continent":"Africa","country":"Cape Verde","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24554","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"caf_subnational_admin_2000_2020.png","continent":"Africa","country":"Central African Republic","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24556","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"tcd_subnational_admin_2000_2020.png","continent":"Africa","country":"Chad","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24559","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"com_subnational_admin_2000_2020.png","continent":"Africa","country":"Comoros","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24618","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"civ_subnational_admin_2000_2020.png","continent":"Africa","country":"Cote d'Ivoire","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24589","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"dji_subnational_admin_2000_2020.png","continent":"Africa","country":"Djibouti","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24562","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"cod_subnational_admin_2000_2020.png","continent":"Africa","country":"DRC","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24741","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"egy_subnational_admin_2000_2020.png","continent":"Africa","country":"Egypt","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24575","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"gnq_subnational_admin_2000_2020.png","continent":"Africa","country":"Equatorial Guinea","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24577","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"eri_subnational_admin_2000_2020.png","continent":"Africa","country":"Eritrea","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24722","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"swz_subnational_admin_2000_2020.png","continent":"Africa","country":"Eswatini","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24576","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"eth_subnational_admin_2000_2020.png","continent":"Africa","country":"Ethiopia","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24590","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"gab_subnational_admin_2000_2020.png","continent":"Africa","country":"Gabon","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24592","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"gmb_subnational_admin_2000_2020.png","continent":"Africa","country":"Gambia","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24595","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"gha_subnational_admin_2000_2020.png","continent":"Africa","country":"Ghana","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24603","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"gin_subnational_admin_2000_2020.png","continent":"Africa","country":"Guinea","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24687","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"gnb_subnational_admin_2000_2020.png","continent":"Africa","country":"Guinea-Bissau","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24623","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"ken_subnational_admin_2000_2020.png","continent":"Africa","country":"Kenya","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24630","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"lso_subnational_admin_2000_2020.png","continent":"Africa","country":"Lesotho","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24632","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"lbr_subnational_admin_2000_2020.png","continent":"Africa","country":"Liberia","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24633","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"lby_subnational_admin_2000_2020.png","continent":"Africa","country":"Libya","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24638","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"mdg_subnational_admin_2000_2020.png","continent":"Africa","country":"Madagascar","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24639","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"mwi_subnational_admin_2000_2020.png","continent":"Africa","country":"Malawi","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24642","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"mli_subnational_admin_2000_2020.png","continent":"Africa","country":"Mali","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24645","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"mrt_subnational_admin_2000_2020.png","continent":"Africa","country":"Mauritania","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24646","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"mus_subnational_admin_2000_2020.png","continent":"Africa","country":"Mauritius","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24560","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"myt_subnational_admin_2000_2020.png","continent":"Africa","country":"Mayotte","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24653","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"mar_subnational_admin_2000_2020.png","continent":"Africa","country":"Morocco","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24654","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"moz_subnational_admin_2000_2020.png","continent":"Africa","country":"Mozambique","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24656","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"nam_subnational_admin_2000_2020.png","continent":"Africa","country":"Namibia","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24668","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"ner_subnational_admin_2000_2020.png","continent":"Africa","country":"Niger","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24669","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"nga_subnational_admin_2000_2020.png","continent":"Africa","country":"Nigeria","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24561","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"cog_subnational_admin_2000_2020.png","continent":"Africa","country":"Rep. Congo","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24691","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"reu_subnational_admin_2000_2020.png","continent":"Africa","country":"R\u00e9union","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24693","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"rwa_subnational_admin_2000_2020.png","continent":"Africa","country":"Rwanda","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24695","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"shn_subnational_admin_2000_2020.png","continent":"Africa","country":"Saint Helena, Ascension and Tristan da Cunha","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24703","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"stp_subnational_admin_2000_2020.png","continent":"Africa","country":"Sao Tome and Principe","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24705","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"sen_subnational_admin_2000_2020.png","continent":"Africa","country":"Senegal","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24707","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"syc_subnational_admin_2000_2020.png","continent":"Africa","country":"Seychelles","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24708","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"sle_subnational_admin_2000_2020.png","continent":"Africa","country":"Sierra Leone","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24713","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"som_subnational_admin_2000_2020.png","continent":"Africa","country":"Somalia","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24714","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"zaf_subnational_admin_2000_2020.png","continent":"Africa","country":"South Africa","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24717","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"ssd_subnational_admin_2000_2020.png","continent":"Africa","country":"South Sudan","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24718","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"sdn_subnational_admin_2000_2020.png","continent":"Africa","country":"Sudan","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24746","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"tza_subnational_admin_2000_2020.png","continent":"Africa","country":"Tanzania","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24728","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"tgo_subnational_admin_2000_2020.png","continent":"Africa","country":"Togo","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24733","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"tun_subnational_admin_2000_2020.png","continent":"Africa","country":"Tunisia","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24738","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"uga_subnational_admin_2000_2020.png","continent":"Africa","country":"Uganda","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24719","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"esh_subnational_admin_2000_2020.png","continent":"Africa","country":"Western Sahara","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24754","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"zmb_subnational_admin_2000_2020.png","continent":"Africa","country":"Zambia","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24715","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"zwe_subnational_admin_2000_2020.png","continent":"Africa","country":"Zimbabwe","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24697","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"aia_subnational_admin_2000_2020.png","continent":"Americas","country":"Anguilla","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24525","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"atg_subnational_admin_2000_2020.png","continent":"Americas","country":"Antigua and Barbuda","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24527","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"arg_subnational_admin_2000_2020.png","continent":"Americas","country":"Argentina","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24661","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"abw_subnational_admin_2000_2020.png","continent":"Americas","country":"Aruba","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24529","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: Global national level input population data-summary<\/a>Methodology<\/b>: 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. \u201cGlobal Spatio-temporally Harmonised Datasets for Producing High-resolution Gridded Population Distribution Datasets\u201d. Big Earth Data (https:\/\/doi.org\/10.1080\/20964471.2019.1625151<\/a>).","doi":"10.5258\/SOTON\/WP00651","popyear":null,"date":"2018-11-02","file_img":"bhs_subnational_admin_2000_2020.png","continent":"Americas","country":"Bahamas","resolution":"100","type":"Administrative Areas","file_html":""},{"id":"24533","desc":"The dataset is available to download in Geotiff format at a resolution of 3 arc-second (approximately 100m at the equator). The projection is Geographic Coordinate System, WGS84. Grid cell values represent incremental, globally unique, numerical identifiers for the highest-level, temporally-harmonized, subnational units associated with the population counts obtained for each country and territory (with zeroes globally identifying inland waterbodies within each subnational unit).Data Source<\/b>: