The current version supersedes GRID3 NGA - Settlement Extents v3.0; the following changes were made:Corrections on imputed values for building count and building areas.Edits to the data release notes.The GRID3 NGA - Settlement Extents v3.1 include:GRID3_NGA_settlement_extents_v3_1.gpkg: a spatial layer representing settlement polygons.GRID3_NGA_settlement_grid_v3_1.gpkg: a spatial layer representing the centroids of settled grid cells.For more information on data inputs, methodology, and codebooks please see the Data Release Notes.Recommended Citation: Center for International Earth Science Information Network (CIESIN), Columbia University. 2024. GRID3 NGA - Settlement Extents v3.1. New York: GRID3. https://doi.org/10.7916/x9xg-e262. Accessed [DAY MONTH YEAR].Terms of use:Users are free to download, store, access, use, copy, adapt, transform, alter, arrange, build upon, distribute and transmit this work and any derivative works. Attribution of the source must be provided, and further distribution of this work or derived work must maintain the same terms of data use and license as set forth in this Terms of Use.Copyright 2024. The Trustees of Columbia University in the City of New York.Data license:The data and accompanying document are licensed under a Creative Commons Attribution-ShareAlike 4.0 International, CC BY-SA 4.0(https://creativecommons.org/licenses/by-sa/4.0) and specified in legal code (https://creativecommons.org/licenses/by-sa/4.0/legalcode).Contacts and data queries:The authors of this dataset appreciate feedback regarding the data, including suggestions, discovery of errors, difficulties in using the data, and format preferences. For dataset-related questions, please send an email to: info@ciesin.columbia.edu

The Gridded Population of the World, Version 3 (GPWv3): Population Count Grid consists of estimates of human population for the years 1990, 1995, and 2000 by 2.5 arc-minute grid cells and associated data sets dated circa 2000. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative Units, is used to assign population values to grid cells. The population count grids contain estimates of the number of persons per grid cell. The grids are available in various GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).

The current version supersedes GRID3 COD - Settlement Extents v3.0; the following changes were made:Corrections on imputed values for building count and building areas.Corrections on probability values from field-collected dataEdits in the Data Release NotesThe two layers contained within the GRID3 COD - Settlement Extents v3.1 include:GRID3_COD_settlement_extents_v3_1.gpkg: a spatial layer representing settlement polygons.GRID3_COD_settlement_grid_v3_1.gpkg: a spatial layer representing the centroids of settled grid cells.For more information on data inputs, methodology, and codebooks please see the Data Release Notes. Recommended Citation: Center for International Earth Science Information Network (CIESIN), Columbia University. 2024. GRID3 COD - Settlement Extents v3.1. New York: GRID3. https://doi.org/10.7916/d6gy-yh28. Accessed [DAY MONTH YEAR].Terms of use:Users are free to download, store, access, use, copy, adapt, transform, alter, arrange, build upon, distribute and transmit this work and any derivative works. Attribution of the source must be provided, and further distribution of this work or derived work must maintain the same terms of data use and license as set forth in this Terms of Use.Copyright 2024. The Trustees of Columbia University in the City of New York.Data license:The data and accompanying document are licensed under a Creative Commons Attribution-ShareAlike 4.0 International, CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0) and specified in legal code (https://creativecommons.org/licenses/by-sa/4.0/legalcode)Contacts and data queries:The authors of this dataset appreciate feedback regarding the data, including suggestions, discovery of errors, difficulties in using the data, and format preferences. For dataset-related questions, please send an email to: info@ciesin.columbia.edu

Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. This dataset provides index values for small spatial units within urban areas in Chad. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.

Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. This dataset provides index values for small spatial units within urban areas in Côte d'Ivoire. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.

The two layers contained within the GRID3 SHN - Settlement Extents v3.0 include:GRID3_SHN_settlement_extents_v3.gpkg: a spatial layer representing settlement polygons.GRID3_SHN_settlement_grid_v3.gpkg: a spatial layer representing the centroids of settled grid cells.For more information on data inputs, methodology, and codebooks please see the Data Release Notes.Recommended Citation:Center for International Earth Science Information Network (CIESIN), Columbia University. 2024. GRID3 SHN - Settlement Extents v3.0. New York: GRID3. https://doi.org/10.7916/fya2-0h07. Accessed [DAY MONTH YEAR].Terms of use:Users are free to download, store, access, use, copy, adapt, transform, alter, arrange, build upon, distribute and transmit this work and any derivative works. Attribution of the source must be provided, and further distribution of this work or derived work must maintain the same terms of data use and license as set forth in this Terms of Use.Copyright 2024. The Trustees of Columbia University in the City of New York.Data license:The data and accompanying document are licensed under a Creative Commons Attribution-ShareAlike 4.0 International, CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0) and specified in legal code (https://creativecommons.org/licenses/by-sa/4.0/legalcode).Contacts and data queries:The authors of this dataset appreciate feedback regarding the data, including suggestions, discovery of errors, difficulties in using the data, and format preferences. For dataset-related questions, please send an email to: info@ciesin.columbia.edu

The "GRID3 Comoros Settlement Extents, Version 01" supersedes "GRID3 Comoros Settlement Extents Version 01, Alpha."

The dataset consists of settlement extents across Comoros, as well as accompanying population estimates for each settlement extent.

This data product contains all information contained in the previous “GRID3 Comoros Settlement Extents, Version 01 Alpha” product, with updates. Updates in this version include: a single settlement extent feature class (alpha version contains the same data in three separate feature class layers: BUAs, SSAs, and hamlets) and new population estimate fields (Population and Pop_UN_adj) for each settlement extent.

This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Comoros Settlement Extents, Version 01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-1gxk-ac24 . Accessed DAY MONTH YEAR.

Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. This dataset provides index values for small spatial units within urban areas in Nigeria. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.

NOTE: This version of the Nigeria settlement extents has been superseded by "GRID3 Nigeria Settlement Extents, Version 01.01", now available here: https://doi.org/10.7916/d8-mb4j-1p68 The database constitutes a comprehensive set of settlement polygons nationwide. It is in geodatabase format and consists of three feature classes for built up areas (BUA), small settlement areas (SSA), and hamlets (hamlets). This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Nigeria. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Keywords: built up areas, BUA, small settlement areas, SSA, hamlets, settlement aggregation, settlement extent, CIESIN, GRID3, Novel-T

The "GRID3 Nigeria Settlement Extents, Version 01" supersedes "GRID3 Nigeria Settlement Extents Version 01, Alpha."

The dataset consists of settlement extents across Nigeria, as well as accompanying population estimates for each settlement extent.

This data product contains all information contained in the previous “GRID3 Nigeria Settlement Extents, Version 01 Alpha” product, with updates. Updates in this version include: a single settlement extent feature class (alpha version contains the same data in three separate feature class layers: BUAs, SSAs, and hamlets) and new population estimate fields (Population and Pop_UN_adj) for each settlement extent.

This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Nigeria Settlement Extents, Version 01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-5hp4-p287 . Accessed DAY MONTH YEAR.

These data include gridded estimates of population sizes at approximately 100 m resolution with national coverage across South Sudan. This includes estimates of total population sizes and population counts in 40 different age-sex groups. It also includes a breakdown of the total population sizes into internally displaced persons (IDPs) and non-IDPs. These results were produced using publicly available census projections from the South Sudan National Bureau of Statistics and displacement data from the International Organisation for Migration (IOM) and the United Nations Refugee Agency (UNHCR), as well as building footprints from Maxar/Ecopia that were derived from recent satellite imagery. Note that this dataset is most likely to represent South Sudan's population distribution as of September 2020 given the age of the input data.1. SSD_population_v2_0_gridded.zipThis zip file contains three rasters in geotiff format:SSD_population_v2_0_gridded_population.tif This geotiff raster contains estimates of total population size for each approximately 100 m grid cell (0.0008333 decimal degrees grid) across South Sudan. NA values represent grid cells where no building footprints were present. Zero values represent grid cells that contain building footprints but are estimated to contain no people due to displacement of people away from those grid cells. These population estimates include decimals (e.g. 10.3 people). This provides more accurate population totals when grid cells are summed. A population estimate of 0.5 people in each of two neighboring grid cells would indicate an expectation that one person lives somewhere within those two grid cells. SSD_population_v2_0_gridded_nonidps.tif This geotiff raster contains estimates of non-internally displaced persons (non-IDPs) for each approximately 100 m grid cell (0.0008333 decimal degrees grid) across South Sudan, i.e. the number of people who have not been displaced from another area. This raster plus the SSD_population_v2_0_gridded_idps.tif raster equal the values given in the SSD_population_v2_0_gridded_population.tif raster. SSD_population_v2_0_gridded_idps.tif This geotiff raster contains estimates of internally displaced persons (IDPs) for each approximately 100 m grid cell (0.0008333 decimal degrees grid) across South Sudan, i.e. the number of people who have been displaced from another area. This raster plus the SSD_population_v2_0_gridded_nonidps.tif raster equal the values given in the SSD_population_v2_0_gridded_population.tif raster.2. SSD_population_v2_0_agesex.zip This zip file contains 40 rasters in geotiff format:Each raster provides gridded population estimates for an age-sex group. These were derived from the SSD_population_v2_0_gridded_population.tif raster. Note that, in this dataset, we do not provide age-sex group estimates for non-IDPs and IDPs separately. We provide 36 rasters for the commonly reported age-sex groupings of sequential age classes for males and females separately. These are labelled with either an “m” (male) or an “f” (female) followed by the number of the first year of the age class represented by the data. “f0” and “m0” are population counts of under 1 year olds for females and males, respectively. “f1” and “m1” are population counts of 1 to 4 year olds for females and males, respectively. Over 4 years old, the age groups are in five year bins labelled with a “5”, “10”, etc. Eighty year olds and over are represented in the groups “f80” and “m80”. We provide an addition four rasters that represent demographic groups often targeted by programmes and interventions. These are “under1” (all females and males under the age of 1), “under5” (all females and males under the age of 5), “under15” (all females and males under the age of 15) and “f15_49” (all females between the ages of 15 and 49, inclusive). These data were produced by the WorldPop Research Group at the University of Southampton. Data Citation: WorldPop (School of Geography and Environmental Science, University of Southampton). 2021. South Sudan 2020 gridded population estimates from census projections adjusted for displacement, version 2.0. WorldPop, University of Southampton. doi: 10.5258/SOTON/WP00709 CREDITS: The modelling work was led by Claire Dooley with support from Chris Jochem and oversight by WorldPop director Andy Tatem and GRID3 lead Attila Lazar. The support of the whole WorldPop group is acknowledged, as well as the our GRID3 partners (UNFPA, Columbia University and Flowminder). This work was supported with funding from the Bill & Melinda Gates Foundation (BMGF) and the United Kingdom’s Department for International Development (DFID).This work is part of the GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) programme funded by the Bill & Melinda Gates Foundation (BMGF) and the United Kingdom’s Foreign, Commonwealth & Development Office. It is implemented by Columbia University’s Center for International Earth Science Information Network (CIESIN), the United Nations Population Fund (UNFPA), WorldPop at the University of Southampton, and the Flowminder Foundation. The primary intended use of these data was aiding the BMGF field teams.The downloadable Metadata provides more information about Source Data, Methods Overview, Assumptions & Limitations and Works and Data CitedContact release@worldpop.org for more information or go to here.

This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative in Guinea.

GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/

Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2020. GRID3 Guinea Settlement Extents Version 01, Alpha. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). Source of building Footprints “Ecopia Vector Maps Powered by Maxar Satellite Imagery”© 2020. DOI: https://doi.org/10.7916/d8-zcrh-cm17. Accessed DAY MONTH YEAR

The data are available for download in OGC Geopackage format contained in a zip file.This data release supersedes the dataset “GRID3 COD - Religious Centers: five provinces v1.0”.This operational dataset has not been fully validated by government officials or ministries.Download province level data:Haut-KatangaKasaïKasaï-OrientalKinshasaLomamiFor more information on the methodology and data sources used during the production of this data, see the Data Release Notes.Dataset citation:Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of the Congo, 2024. GRID3 COD - Religious Centers v1.0. New York: GRID3. https://doi.org/10.7916/hesc-8041. Accessed

NOTE: This version of the Burkina Faso settlement extents has been superseded by "GRID3 Burkina Faso Settlement Extents, Version 01.01", now available here: https://doi.org/10.7916/d8-qfq8-4789 The dataset consists of settlement extents across Burkina Faso, as well as accompanying population estimates for each settlement extent. This data product contains all information contained in the previous GRID3 Burkina Faso Settlement Extents, Version 01 Alpha product, with updates. Updates in this version include: a single settlement extent feature class (Alpha contained the same data in three (3) separate feature class layers: BUAs, SSAs & Hamlets), and new population estimate fields ("Population" and "Pop_UN_adj") for each settlement extent. The population estimate was updated on October 1, 2021 using a high resolution population estimate produced by GRID3. This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Keywords: Settlements, Hamlets, Built-up Areas (BUA), Small Settlement Areas (SSA) The programme is funded by the Bill & Melinda Gates Foundation and United Kingdom's Foreign, Commonwealth, Development Office. It is implemented by Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund (UNFPA), and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

NOTE: This version of the Madagascar settlement extents has been superseded by "GRID3 Madagascar Settlement Extents, Version 01.01", now available here: https://doi.org/10.7916/d8-a40j-1p15 The dataset consists of settlement extents across Madagascar, as well as accompanying population estimates for each settlement extent. This data product contains all information contained in the previous GRID3 Madagascar Settlement Extents, Version 01 Alpha product, with updates. Updates in this version include: a single settlement extent feature class (Alpha contained the same data in three (3) separate feature class layers: BUAs, SSAs & Hamlets), and new population estimate fields ("Population" and "Pop_UN_adj") for each settlement extent . This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Keywords: Settlements, Hamlets, Built-up Areas (BUA), Small Settlement Areas (SSA) The programme is funded by the Bill & Melinda Gates Foundation and United Kingdom's Foreign, Commonwealth, Development Office. It is implemented by Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund (UNFPA), and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

NOTE: This version of the South Sudan settlement extents has been superseded by "GRID3 South Sudan Settlement Extents, Version 01.01", now available here: https://doi.org/10.7916/d8-khpa-pq09 The dataset consists of settlement extents across South Sudan, as well as accompanying population estimates for each settlement extent. This data product contains all information contained in the previous GRID3 South Sudan Settlement Extents, Version 01 Alpha product, with updates. Updates in this version include: a single settlement extent feature class (Alpha contained the same data in three (3) separate feature class layers: BUAs, SSAs & Hamlets), and new population estimate fields ("Population" and "Pop_UN_adj") for each settlement extent . This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Keywords: Settlements, Hamlets, Built-up Areas (BUA), Small Settlement Areas (SSA) The programme is funded by the Bill & Melinda Gates Foundation and United Kingdom's Foreign, Commonwealth, Development Office. It is implemented by Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund (UNFPA), and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The data are available for download in OGC geopackage format packaged in a zip file.This data release supersedes the dataset "GRID3 COD - Schools : five provinces v1.0".This operational dataset has not been fully validated by government officials or ministries.Download province level data:Haut-KatangaKasaïKasaï-OrientalKinshasaLomamiFor more information on the methodology and data sources used during the production of this data, see the Data Release Notes.Dataset citation:Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of the Congo, 2024. GRID3 COD - Schools v1.0. New York: GRID3. https://doi.org/10.7916/5ngz-fr94. Accessed

Social distancing is a public health measure intended to reduce infectious disease transmission, by maintaining physical distance between individuals or households. In the context of the COVID-19 pandemic, populations in many countries around the world have been advised to maintain social distance (also referred to as physical distance), with distances of 6 feet or 2 metres commonly advised. Feasibility of social distancing is dependent on the availability of space and the number of people, which varies geographically. In locations where social distancing is difficult, a focus on alternative measures to reduce disease transmission may be needed. To help identify locations where social distancing is difficult, we have developed an ease of social distancing index. By index, we mean a composite measure, intended to highlight variations in ease of social distancing in urban settings, calculated based on the space available around buildings and estimated population density. Index values were calculated for small spatial units (vector polygons), typically bounded by roads, rivers or other features. This dataset provides index values for small spatial units within urban areas in Comoros. Measures of population density were calculated from high-resolution gridded population datasets from WorldPop, and the space available around buildings was calculated using building footprint polygons derived from satellite imagery (Ecopia.AI and Maxar Technologies. 2020). These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Department for International Development. Project partners included the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation.

NOTE: This version of the Guinea-Bissau settlement extents has been superseded by "GRID3 Guinea-Bissau Settlement Extents, Version 01.01", now available here: https://doi.org/10.7916/d8-g94m-5w33 The dataset consists of settlement extents across Guinea-Bissau, as well as accompanying population estimates for each settlement extent. This data product contains all information contained in the previous GRID3 Guinea-Bissau Settlement Extents, Version 01 Alpha product, with updates. Updates in this version include: a single settlement extent feature class (Alpha contained the same data in three (3) separate feature class layers: BUAs, SSAs & Hamlets), and new population estimate fields ("Population" and "Pop_UN_adj") for each settlement extent . This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/ Keywords: Settlements, Hamlets, Built-up Areas (BUA), Small Settlement Areas (SSA) The programme is funded by the Bill & Melinda Gates Foundation and United Kingdom's Foreign, Commonwealth, Development Office. It is implemented by Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund (UNFPA), and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The Gridded Population of the World, Version 3 (GPWv3): Population Density Grid, Future EstimatesFuture Estimates consists of estimates of human population for the years 2005, 2010, and 2015 by 2.5 arc-minute grid cells. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative Units, is used to assign population values to grid cells. The future estimate population values are extrapolated based on a combination of subnational growth rates from census dates and national growth rates from United Nations statistics. All of the grids have been adjusted to match United Nations national level population estimates. The population density grids are derived by dividing the population count grids by the land area grid and represent persons per square kilometer. The grids are available in various GIS-compatible data formats and geographic extents (global, continent [Antarctica not included], and country levels). GPWv3 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with Centro Internacional de Agricultura Tropical (CIAT).