Geospatial covariate data layers Covariates / Gridded maps of building patterns - Google (PIB) / Burkina Faso 100m. Covariates

Burkina Faso 100m. Covariates
Gridded maps of building patterns - Google (PIB), Burkina Faso

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.
Building metrics are calculated based on the pixel(s) that their geometries intersect (Pixel Intersected Based – PIB method)

  • _buildings_count_PIB_ - The value of each grid cell represents the counts of buildings within the cells, based on PIB method.
  • _buildings_cv_area_PIB_ - The value of each grid cell represents the grid cell level coefficient of variation of building areas for all buildings inside a grid cell, based on the PIB method.
  • _buildings_cv_length_PIB_ - The value of each grid cell represents the coefficient of variation of building lengths (perimeter) for all buildings inside a grid cell, based on the PIB mrthod.
  • _buildings_mean_area_PIB_ - The value of each grid cell represents the mean area of all buildings whose centroids are within the respective grid cells, based on the PIB method.
  • _buildings_mean_length_PIB_ - The value of each grid cell represents the mean perimeter length of all the buildings inside a grid cell, based on the PIB method.
  • _buildings_total_area_PIB_ - The value of each grid cell represents the total building footprint area within respective grid cells, based on the PIB method.
  • _buildings_total_length_PIB_ - The value of each grid cell represents the total building footprint area within respective grid cells, based on the PIB method.


Data Source
Sirko, W. et al. (2021). Continental-Scale Building Detection from High Resolution Satellite Imagery. arXiv:2107.12283. https://ui.adsabs.harvard.edu/abs/2021arXiv210712283S.

Region : Burkina Faso
DOI : 10.5258/SOTON/WP00772
Date of production : 2024-01-01
Recommended citation

D. Woods, T. McKeen, A. Cunningham, R. Priyatikanto, A. Sorichetta , A.J. Tatem and M. Bondarenko. 2024 "WorldPop high resolution, harmonised annual global geospatial covariates. Version 1.0." University of Southampton: Southampton, UK. DOI:10.5258/SOTON/WP00772

Data Files :
WorldPop datasets are available under the Creative Commons Attribution 4.0 International License. This means that you are free to share (copy and redistribute the material in any medium or format) and adapt (remix, transform, and build upon the material) for any purpose, even commercially, provided attribution is included (appropriate credit and a link to the licence).

WorldPop datasets derived from OpenStreetMap, Microsoft Building Footprints or Microsoft Roads Detection are available under the Open Database License (ODbL). This means you are free to share the data, provided attribution is included (appropriate credit and a link to the license). If you alter or build upon the data, you may distribute the result only under the same ODbL license.