The GRID3 COM - Settlement Extents v3.0 consists of a geographic representation of settlements in Comoros, in two forms: (1) settlement polygons, and (2) spatial points depicting the centroids of settled grid cells at 3-arc seconds (or ~100 meters) contained within settlement polygons.

Both layers include attributes as described in the codebooks.

The current version supersedes GRID3 Comoros Settlement Extents, Version 02; the following changes were made: (1) Development of a new methodology to derive building counts and settlement polygons with open data. (2) Estimation of a probability value for settlement polygons (3) Addition of a building-area measure (4) Replacement of degree of urbanization with classification based on built-up areas, small settlement areas, and hamlets (5) Elimination of building-count ranges (6) Elimination of variable comparing to previous versions

Recommended Citation: Center for International Earth Science Information Network (CIESIN), Columbia University. 2024. GRID3 COM - Settlement Extents v3.0. New York: GRID3. [URL]. Accessed [DAY MONTH YEAR].

The two layers contained within the GRID3 UGA - Settlement Extents v3.0 include:GRID3_UGA_settlement_extents_v3.gpkg: a spatial layer representing settlement polygons.GRID3_UGA_settlement_grid_v3.gpkg: a spatial layer representing the centroids of settled grid cells.The current version supersedes GRID3 UGA - Settlement Extents v2.0; the following changes were made:Development of a new methodology to derive building counts and settlement polygons with open data.Estimation of a probability value for settlement polygonsAddition of a building-area measureReplacement of degree of urbanization with classification based on built-up areas, small settlement areas, and hamletsElimination of building-count rangesElimination of variable comparing to previous versionsFor 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 UGA - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/zgzd-6t74. 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 COM - Settlement Extents v3.0 consists of a geographic representation of settlements in Comoros, in two forms: 1) settlement polygons, and 2) spatial points depicting the centroids of settled grid cells at 3-arc seconds (or ~100 meters) contained within settlement polygons. Both layers include attributes as described in the codebooks. Data inputs and methodology are described in the DataRelease Notes (PDF). The current version supersedes GRID3 Comoros Settlement Extents, Version 02; the following changes were made: - Development of a new methodology to derive building counts and settlement polygons with open data. - Estimation of a probability value for settlement polygons - Addition of a building-area measure - Replacement of degree of urbanization with classification based on built-up areas, small settlement areas, and hamlets - Elimination of building-count ranges - Elimination of variable comparing to previous versions Keywords: settlements

Government building locations and names in Nigeria. Released in September 2020. Dataset is incomplete for the country.

NOTE: This data release supersedes the dataset "GRID3 DRC Schools - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces, Version 01". The GRID3 COD - Schools v1.0 dataset consists of school points with names and attributes in the following provinces of the Democratic Republic of the Congo (COD): Province group 1: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami The GRID3 COD - Schools v1.0 dataset is one of six datasets (Settlements, Health Facilities, Health Area Boundaries, Health Zone Boundaries, Schools and Religious Centers) included in this Version 1.0 release. This operational dataset has not been fully validated by government officials or ministries. The data are available for download in OGC Geopackage format. Funding for the development and dissemination of this dataset was provided by GRID3 Inc, the Bill & Melinda Gates Foundation, and Gavi, the Vaccine Alliance. Keywords: Schools

Energy and electricity substation locations and names in Nigeria. Released in September 2020. Dataset is incomplete for the country.

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

Nigeria country-wide operational state boundaries (administrative level 1). Released in September 2020.

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

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 Tanzania 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-ve7a-dm77 . Accessed DAY MONTH YEAR

Water points and names in Nigeria. Released in September 2020. Dataset is incomplete for the country.

NOTE: This version of the Cameroon settlement extents has been superseded by "GRID3 Cameroon Settlement Extents, Version 01.01", now available here: https://doi.org/10.7916/d8-1a2h-t505 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 Cameroon. 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 zip files contain the following files:SEN_population_v1_0_gridded.tifThis geotiff raster, at a spatial resolution of 3 arc-seconds (approximately 100m at the equator), contains estimates of the total population size per grid cell across Senegal. NA values represent areas that were mapped as unsettled based on gridded building patterns derived from building footprints (Dooley and Tatem, 2020). These data are stored as floating-point numbers rather than integers to avoid rounding errors in aggregated population totals for larger areas.SEN _population_v1_0_agesex.zipThis zip file contains the following two raster files:SEN_population_v1_0_gridded_female.tif This geotiff raster, at a spatial resolution of 3 arc-seconds (approximately 100m at the equator), contains estimates of the total female population size per grid cell across Senegal. NA values represent areas that were mapped as unsettled based on gridded building patterns derived from building footprints (Dooley and Tatem, 2020). These data are stored as floating-point numbers rather than integers to avoid rounding errors in aggregated population totals for larger areas.SEN_population_v1_0_gridded_male.tif This geotiff raster, at a spatial resolution of 3 arc-seconds (approximately 100m at the equator), contains estimates of the total male population size per grid cell across Senegal. NA values represent areas that were mapped as unsettled based on gridded building patterns derived from building footprints (Dooley and Tatem, 2020). These data are stored as floating-point numbers rather than integers to avoid rounding errors in aggregated population totals for larger areas.Note, these data are operational population estimates and are not official government statistics.The downloadable Metadata provides more information about Source Data, Methods Overview, Assumptions & Limitations and Works and Data Cited.Contact release@worldpop.org for more information or go here.Data Citation: Qader S. H., Abbott T., Boytinck, E., Kuepie, M., Lazar A. N., Tatem A. J. 2022. Census disaggregated gridded population estimates for Senegal (2020), version 1.0. University of Southampton. doi:10.5258/SOTON/WP00730These data were produced by the WorldPop Research Group at the University of Southampton. 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.

Internally Displaced Persons (IDP) sites and names in Nigeria. IDP sites are makeshift shelter provided for people who have been forced to leave their native homes and still within their respective country geographical boundary to find temporary refuge till their homes are safe to return. Downloaded from geodatabase (GDB) version 1.75 (released in March 2021). Dataset is incomplete for the country.

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.

This score ranks the percentage of the population living in a household that does not have a radio or television and where no adult household members are regular consumers of newspapers, radio, television, or the internet. Regular consumers are defined as adults who use the media at least once a week. Adults are defined as individuals aged 15-49. Ranks are determined by quintiles in the data distribution.This feature layer aggregates scores to the state boundaries from GRID3 GDB v1.69. Population estimate from WorldPop's Bottom-up gridded population layer. Access for the WorldPop population estimates full methodology visit https://wopr.worldpop.org/

NOTE: This version of the Comoros settlement extents has been superseded by "GRID3 Comoros Settlement Extents, Version 01.01", now available here: https://doi.org/10.7916/d8-t1yz-k248 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 Comoros. 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

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 Zambia. 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 GRID3 NGA - Health Facilities v2.0 dataset is a non-exhaustive, non-validated geographic representation of health facility points in Nigeria. The dataset incorporates recent updates from both the Nigerian Health Facility Registry (HFR) and GRID3. This dataset is considered operational. Keywords: health facilities

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 Niger. 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.