This version has been superseded by Version 4.0.
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 Nigeria Health Facility Registry (HFR) and GRID3. This dataset is considered operational.
This current version supersedes the GRID3 NGA - Health Facilities dataset; the following changes were made:
For more information on the methodology and data sources used during the production of this data, see the Data Release Notes.
Dataset citation
Center for Integrated Earth System Information (CIESIN), Columbia University 2024. GRID3 NGA - Health Facilities v2.0. New York: GRID3. https://doi.org/10.7916/kv1n-0743. Accessed [DAY MONTH YEAR].
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 NGA - Travel Time Friction Surface v1.0 dataset is a spatial data layer in tiff format. The datasets contain 2 layers:
The resolution is 30 m. The unit of measurement in both surfaces is minutes per meter.
For more information on the methodology and data sources used during the production of this data, click here.
Dataset citation:
Center for Integrated Earth System Information (CIESIN), Columbia University. 2025. GRID3 NGA - Travel Time Friction Surface v1.0. New York: Columbia University. https://doi.org/10.7916/tw5k-ys98. Accessed <DAY MONTH YEAR>
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
For more information on the methodology and data sources used during the production of this data, click here.
Dataset citation:
Center for Integrated Earth System Information (CIESIN), Columbia University. 2025. GRID3 NGA - Roads v1.0.New York: Columbia University. https://doi.org/10.7916/b42r-6w17. Accessed <DAY MONTH YEAR>.
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 data are provided in geodatabase file formats.
File name: GRID3_SLE_settlement_names_v1.0.gdb with the following layers:
Extent: Sierra Leone
Coordinate system: GCS WGS 1984
For full methodological details, please see data release notes available for download here.
Download the data as a zip file.
Dataset citation:
Center for International Earth Science Information Network (CIESIN), Columbia University, Statistics Sierra Leone, and Sierra Leone Ministry of Basic and Senior Secondary Education. 2023. GRID3 SLE - Settlement Names v1. 0. New York: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/bxa4-bv46. 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.
For 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 <DAY MONTH YEAR>.
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 two layers contained within the GRID3 AGO - Settlement Extents v3.0 include:
The current version supersedes GRID3 AGO - Settlement Extents v2.0; the following changes were made:
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 AGO - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/hmgn-9b91. 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 zip files contain the following files:
MOZ_population_v1_1_gridded.tif
This GeoTIFF raster (.tif), at a spatial resolution of 3 arc-seconds (approximately 100m at the equator), contains estimated population counts per grid cell across Mozambique. The projection is the geographic coordinate system WGS84 (World Geodetic System 1984). ‘NoData’ values represent areas that were mapped as unsettled based on building footprints from “Digitize Africa data © 2020 Maxar Technologies, Ecopia.AI”. These data are stored as floating-point numbers rather than integers to avoid rounding errors in aggregated populations for larger areas.
MOZ_population_v1_1_agesex.zip
This zip file contains 40 rasters in GeoTIFF format. Each raster provides gridded population estimates for an age-sex group. We provide 36 rasters for the commonly reported age-sex groupings of sequential age classes for males and females separately. The files 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 additional four rasters that represent aggregated demographic groups of special interest for development 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 using the peanutButter R package (Leasure et al. 2020b) which multiplied the gridded population estimates (MOZ_population_v1_1_gridded.tif) by gridded age-sex proportions that differ by region (WorldPop et al. 2018, Pezzulo et al. 2017).
While each data file represents population counts, individual values contain decimals, i.e. fractions of people. This is because we do not estimate which grid cell each individual in a given age group occupies. For example, if four grid cells next to each other have values of 0.25 this indicates that there is one person of that age group somewhere in those four grid cells
This work provides an estimate of the geographic distribution of the population of Mozambique in 2017. The outputs are intended as an interim population product to support ongoing development and operations work until such time as the official 2017 Population and Housing Census results are available in a spatial gridded format. At that time, this interim gridded population layer will be superseded and users will be advised to use the official gridded population release from INE.
Data Citation: Bondarenko M, Jones P, Leasure D, Lazar AN, Tatem AJ. 2020. Census disaggregated gridded population estimates for Mozambique (2017), version 1.1. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00672 CREDITS: Patricia Jones and Donna Clarke (WorldPop) supported the generation of inputs for the application of the random forest-based dasymetric mapping approach developed by Stevens et al. (2015). The population disaggregation was done by Maksym Bondarenko (WorldPop), using the random forest population modelling R scripts (Bondarenko et al., 2020). The age-sex rasters, SQL database, and map tileswere created by Doug Leasure (WorldPop). The administrative boundaries and population totals were provided by Arlindo Charles, at INE (National Institute of Statistics) in Mozambique. Claire Dooley and Chris Jochem reviewed the population raster and its documentation, and provided comments and suggestions. Attila N. Lazar (WorldPop) coordinated the work with substantial engagement and translation support from Sandra Baptista (CIESIN). The whole WorldPop group and GRID3 partners are acknowledged for overall project support.
These 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.
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.
", "dcat:contactPoint": { "@id": "https://africa.maps.arcgis.com/sharing/rest/community/users/mlukang_GRID3?f=json", "@type": "vcard:Kind", "vcard:fn": "mlukang_GRID3", "vcard:hasEmail": "https://grid3.org/about-us/contact" }, "dct:publisher": { "@type": "foaf:Agent", "foaf:name": "Africa GeoPortal" }, "dcat:theme": { "@type": "skos:Concept", "skos:prefLabel": "Geospatial" }, "dct:accessRights": { "@type": "dct:RightsStatement", "@label": { "@value": "public" } }, "dct:identifier": "https://www.arcgis.com/home/item.html?id=440b60b7b81c4de5a74594cd6fe58ab4&sublayer=0", "dcat:keyword": [ "population", "MOZ", "Mozambique" ], "dct:provenance": { "@type": "dct:ProvenanceStatement", "@label": { "@value": "CITATION:\nBondarenko M, Jones P, Leasure D, Lazar AN, Tatem AJ. 2020. Census disaggregated gridded population estimates for Mozambique (2017), version 1.1. WorldPop, University of Southampton. doi:10.5258/SOTON/WP00672\n\nCREDITS:\nPatricia Jones and Donna Clarke (WorldPop) supported the generation of inputs for the application of the random forest-based dasymetric mapping approach developed by Stevens et al. (2015). The population disaggregation was done by Maksym Bondarenko (WorldPop), using the random forest population modelling R scripts (Bondarenko et al., 2020). The age-sex rasters, SQL database, and map tileswere created by Doug Leasure (WorldPop). The administrative boundaries and population totals were provided by Arlindo Charles, at INE (National Institute of Statistics) in Mozambique. Claire Dooley and Chris Jochem reviewed the population raster and its documentation, and provided comments and suggestions. Attila N. Lazar (WorldPop) coordinated the work with substantial engagement and translation support from Sandra Baptista (CIESIN). The whole WorldPop group and GRID3 partners are acknowledged for overall project support." } }, "dct:issued": "2025-09-15T19:22:16.000Z", "dct:modified": "2025-09-15T19:29:22.000Z", "dct:language": { "@id": "lang/" }, "dct:spatial": { "@type": "dct:Location", "dct:bbox": [ { "@value": "POLYGON((30.2179,-10.4704,40.8396,-10.4704,40.8396,-26.8687,30.2179,-26.8687,30.2179,-10.4704))", "@type": "opengis:wktLiteral" } ] }, "dcat:distribution": [ { "@type": "dcat:Distribution", "dcat:accessURL": { "@id": "https://grid3.africageoportal.com/maps/GRID3::grid3-moz-populationv1-1" }, "dct:format": { "@id": "ftype/HTML" }, "dct:description": "Web Page", "dct:title": "ArcGIS Hub Dataset" }, { "@type": "dcat:Distribution", "dcat:accessURL": { "@id": "https://tiles.arcgis.com/tiles/BU6Aadhn6tbBEdyk/arcgis/rest/services/MOZ_gridded_population_estimate_v1/MapServer/0" }, "dct:format": { "@id": "ftype/JSON" }, "dct:description": "Esri REST", "dct:title": "ArcGIS GeoService" } ] }, { "@type": "dcat:Dataset", "@id": "https://grid3.africageoportal.com/datasets/GRID3::grid3-sen-settlement-extents-v3-0", "dct:title": "GRID3 SEN - Settlement Extents v3.0", "dct:description": "The two layers contained within the GRID3 SEN - Settlement Extents v3.0 include:
The current version supersedes GRID3 SEN - Settlement Extents v2.0; the following changes were made:
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 SEN - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/4z4e-8x52. 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 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.
The zip files contain the following files:
The zip files contain the following files:
KEN_population_v1_0_gridded.tif
This 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 Kenya. 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.
KEN_population_v1_0_agesex.zip
This zip file contains 40 GeoTIFF rasters representing estimated population counts for specific age and sex groups within grid cells of approximately 100m. 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 four additional 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 “f1549” (all females between the ages of 15 and 49, inclusive).
These data were produced post-hoc by multiplying the total population counts provided in the KEN_population_v1_0_gridded.tif raster and age and sex proportions derived the US Census bureau age-sex projections for each sub-county. While this data represents population counts, values contain decimals, i.e. fractions of people. This is because both the input population data and age-sex proportions contain decimals. For this reason, it is advised to aggregate the rasters at a coarser scale. For example, if four grid cells next to each other have values of 0.25 this indicates that there is 1 person of that age group somewhere in those four grid cells.
Data Citation
Gadiaga A. N., Abbott T. J., Chamberlain H., Lloyd C. T., Lazar A. N., Darin E., Tatem A. J. 2022. Census-disaggregated gridded population estimates for Kenya (2021), version 1.0. University of Southampton. doi:10.5258/SOTON/WP00747.
The downloadableMetadataprovides more information about Source Data, Methods Overview, Assumptions & Limitations and Works and Data Cited.
Contact release@worldpop.org for more information or gohere.
The zip files contain the following files:
The downloadableMetadataprovides more information about Source Data, Methods Overview, Assumptions & Limitations and Works and Data Cited
Contact release@worldpop.org for more information or gohere.
Church locations and names in Nigeria. Released in September 2020. Dataset is incomplete for the country.
Farm locations and names in Nigeria. Released in September 2020. Dataset is incomplete for the country.
Energy and electricity substation locations and names in Nigeria. Released in September 2020. Dataset is incomplete for the country.
Factory and industrial site locations and names in Nigeria. Released in September 2020. Dataset is incomplete for the country.
Filling station locations and names in Nigeria. Released in September 2020. Dataset is incomplete for the country.
Government building locations and names in Nigeria. Released in September 2020. Dataset is incomplete for the country.
Fire station locations and names in Nigeria. Released in September 2020. Dataset is incomplete for the country.
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.
Nigeria country-wide market locations and names. Released in September 2020.
Mosque locations and names in Nigeria. Released in September 2020. Dataset is incomplete for the country.
Police station locations and names in Nigeria. Released in September 2020. Dataset is incomplete for the country.
Nigeria country-wide primary, secondary, tertiary, private, public, and religious school locations and names. Released in September 2020.
Nigeria country-wide settlement points and names. Released in March 2021.
Nigeria country-wide operational LGA boundaries (administrative level 2). The LGA boundaries dataset was released in March 2021.
The index equally weights three risk profiles (co-morbidities, health facilities access, and exposure) at a 1km squared resolution, which are then aggregated to the ward boundary level.
Source: Fraym 2020
The Fraym platform weaves together the latest satellite imagery and geostatistical datasets with professionally enumerated household surveys. This allows for the disaggregation and re-aggregation of large datasets to cover any geographically bounded area. Indicators are drawn and harmonized from a wide variety of household surveys and other data sources.
These include the following sources:
USAID: Demographic and health surveys
United Nations: UN population division database
World Bank: Enterprise surveys, living standards, global index surveys, and respective country statistics
National Statistical Offices: National censuses and surveys covering population, businesses, health, housing, agriculture, and other areas
International Monetary Fund: World economic outlook databases and respective country statistics
National Air and Space Administration: Remote sensing satellite data, such as vegetation, temperature, and precipitation
USGS: Landscan, Google Earth, GeoData Institute, OSM
WorldPop: Population density by age groups
Water points and names in Nigeria. Released in September 2020. Dataset is incomplete for the country.
Post office locations and names in Nigeria. Released in September 2020. Dataset is incomplete for the country.
The “NSDI Zambia Operational School Points and Names, Version 01 (Beta)” provides school and school affiliated point locations, names, types, and source of the data. The dataset was developed by compiling and standardizing existing government data sources of school point locations and names data from the 2010 census cartography from Zambia Statistics Agency (ZamStats), the Ministry of General Education (MoGE) and the Ministry of Water Development Sanitation and Environmental Protection (MWDSEP).
The dataset is available for download in shapefile format and can be viewed in Geographic Information Systems(GIS) such as ArcMap, QGIS, or Google Earth (Pro). The data is available for all of Zambia. It has the following attributes: Name, Original Name (from original dataset), Type, Sub Type, Source, Province (Code), District (Code), Ward (Code), Constituency (Code), Global ID
For more information about the settlement data and methodology, see the data release notes here.
The "NSDI Zambia Operational Health Facility Layer, Version 01 (Beta)" provides health facility and health affiliated infrastructure point locations, names, types, and source of the data. The dataset was developed by compiling and standardizing existing government data sources of health facility and affiliated infrastructure locations and names data from the Ministry of Health (MoH) obtained in 2019 and from the 2010 census cartography from Zambia Statistics Agency (ZamStats).
The dataset is available for download in shapefile format and can be viewed in Geographic Information Systems(GIS) such as ArcMap, QGIS, or Google Earth (Pro). The data is available for all of Zambia. It has the following attributes: Name, Original Name (from original dataset), Type, Sub Type, Source, Province (Code), District (Code), Global ID. The dataset also includes a Label column which can be used for labeling.
For more information about the settlement data and methodology, see the data release notes here.
The administrative district boundaries were generated at a scale of 1:10,000 and validated against official district narratives provided by the Government of the Republic of Zambia, using high resolution imagery and 1:50,000 topographic maps. The shapefile covers the National, 10 Provincial and 116 District Boundaries.
This data provides gridded population estimates (at spatial resolution of 3 arc-seconds, approximately 100-metre grid cells) for Nigeria, along with the estimates of the number of people belonging to various age and sex groups. Using robust Bayesian statistical hierarchical modelling framework, population modelling and estimation experts from WorldPop (www.worldpop.org) at the University of Southampton combined ‘headcount’ (input population) datasets obtained from the 2022-23 National Malaria Elimination Program (NMEP) with settlement footprint and geospatial covariates to estimate population numbers at high-resolution grid cells. The approach facilitated accounting for the multiple levels of variability within the data, while simultaneously quantifying uncertainties in the parameter estimates. After capturing the spatial variability of population, the modelled estimates were scaled based on the UN WPP July 2025 median national population projections.
This data also contains mastergrid for gridded population estimates.
Population totals for administrative units are also available.
SUGGESTED CITATIONS
Nnanatu C.C., Gadiaga A., Abbott T. J., Chamberlain H., Lazar A. N., Tatem A. J. (2025). Modelled gridded population estimates for Nigeria 2025 version 3.0. WorldPop, University of Southampton. (https://dx.doi.org/10.5258/SOTON/WP00782)
The two layers contained within the GRID3 ZWE - Settlement Extents v3.0 include:
The current version supersedes GRID3 ZWE - Settlement Extents v2.0; the following changes were made:
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 ZWE - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/ws6e-pb92. 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 two layers contained within the GRID3 ZMB - Settlement Extents v3.0 include:
The current version supersedes GRID3 ZMB - Settlement Extents v2.0; the following changes were made:
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 ZMB - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/0pet-p051. 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 two layers contained within the GRID3 ZAF - Settlement Extents v3.0 include:
The current version supersedes GRID3 ZAF- Settlement Extents v2.0; the following changes were made:
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 ZAF - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/tzre-w692. 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 two layers contained within the GRID3 UGA - Settlement Extents v3.0 include:
The current version supersedes GRID3 UGA - Settlement Extents v2.0; the following changes were made:
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 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 two layers contained within the GRID3 TZA - Settlement Extents v3.0 include:
The current version supersedes GRID3 TZA - Settlement Extents v2.0; the following changes were made:
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 TZA - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/asej-zz08. 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 two layers contained within the GRID3 TGO - Settlement Extents v3.0 include:
The current version supersedes GRID3 TGO - Settlement Extents v2.0; the following changes were made:
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 TGO - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/yz03-8697. 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 two layers contained within the GRID3 TCD - Settlement Extents v3.0 include:
The current version supersedes GRID3 TCD - Settlement Extents v2.0; the following changes were made:
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 TCD - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/e6j5-2141. 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 two layers contained within the GRID3 SYC - Settlement Extents v3.0 include:
The current version supersedes GRID3 SYC - Settlement Extents v2.0; the following changes were made:
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 SYC - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/pfbj-h371. 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 two layers contained within the GRID3 STP - Settlement Extents v3.0 include:
This is the settlement extents layer.
The current version supersedes GRID3 STP - Settlement Extents v2.0; the following changes were made:
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 STP - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/zfp5-pv42. 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 two layers contained within the GRID3 SSD - Settlement Extents v3.0 include:
The current version supersedes GRID3 SSD - Settlement Extents v2.0; the following changes were made:
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 SSD - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/2nth-xx70. 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 two layers contained within the GRID3 SOM - Settlement Extents v3.0 include:
The current version supersedes GRID3 SOM - Settlement Extents v2.0; the following changes were made:
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 SOM - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/3yy0-tt77. 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 two layers contained within the GRID3 SLE - Settlement Extents v3.0 include:
The current version supersedes GRID3 SLE - Settlement Extents v2.0; the following changes were made:
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 SLE - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/p7mq-nr26. 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 two layers contained within the GRID3 RWA - Settlement Extents v3.0 include:
The current version supersedes GRID3 RWA - Settlement Extents v2.0; the following changes were made:
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 RWA - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/fs4k-jr23. 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 two layers contained within the GRID3 REU - Settlement Extents v3.0 include:
GRID3_REU_settlement_extents_v3.gpkg: a spatial layer representing settlement polygons.
GRID3_REU_settlement_grid_v3.gpkg: a spatial layer representing the centroids of settled grid cells.
The current version supersedes GRID3 REU - 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 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
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 REU - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/k4z8-ha20. 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 two layers contained within the GRID3 NER - Settlement Extents v3.0 include:
The current version supersedes GRID3 NER - Settlement Extents v2.0; the following changes were made:
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 NER - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/9w2b-5m53. 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 two layers contained within the GRID3 NAM - Settlement Extents v3.0 include:
The current version supersedes GRID3 NAM - Settlement Extents v2.0; the following changes were made:
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 NAM - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/tpag-pg11. 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 two layers contained within the GRID3 MWI - Settlement Extents v3.0 include:
The current version supersedes GRID3 MWI - Settlement Extents v2.0; the following changes were made:
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 MWI - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/n8ge-tc24. 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 two layers contained within the GRID3 MUS - Settlement Extents v3.0 include:
The current version supersedes GRID3 MUS - Settlement Extents v2.0; the following changes were made:
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 MUS - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/bhc9-9j70. 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 two layers contained within the GRID3 MRT - Settlement Extents v3.0 include:
The current version supersedes GRID3 MRT - Settlement Extents v2.0; the following changes were made:
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 MRT - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/e4n2-8443. 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 two layers contained within the GRID3 MOZ - Settlement Extents v3.0 include:
The current version supersedes GRID3 MOZ - Settlement Extents v2.0; the following changes were made:
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 MOZ - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/d3vh-qz17. 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 two layers contained within the GRID3 MLI - Settlement Extents v3.0 include:
The current version supersedes GRID3 MLI - Settlement Extents v2.0; the following changes were made:
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 MLI - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/8hjv-tj96. 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 two layers contained within the GRID3 MDG - Settlement Extents v3.0 include:
The current version supersedes GRID3 MDG - Settlement Extents v2.0; the following changes were made:
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 MDG - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/q6ye-pn21. 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 two layers contained within the GRID3 LSO - Settlement Extents v3.0 include:
The current version supersedes GRID3 LSO - Settlement Extents v2.0; the following changes were made:
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 LSO - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/rxdw-w473. 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 two layers contained within the GRID3 LBR - Settlement Extents v3.0 include:
The current version supersedes GRID3 LBR - Settlement Extents v2.0; the following changes were made:
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 LBR - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/12ar-zg98. 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 two layers contained within the GRID3 KEN - Settlement Extents v3.0 include:
The current version supersedes GRID3 KEN - Settlement Extents v2.0; the following changes were made:
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 KEN - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/6hnz-fr54. 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 two layers contained within the GRID3 GNQ - Settlement Extents v3.0 include:
The current version supersedes GRID3 GNQ - Settlement Extents v2.0; the following changes were made:
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 GNQ- Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/wr0f-sp79. 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 two layers contained within the GRID3 GNB - Settlement Extents v3.0 include:
The current version supersedes GRID3 GNB - Settlement Extents v2.0; the following changes were made:
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 GNB - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/vp9v-f744. 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 two layers contained within the GRID3 GMB - Settlement Extents v3.0 include:
The current version supersedes GRID3 GMB - Settlement Extents v2.0; the following changes were made:
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 GMB - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/yyyg-g140. 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 two layers contained within the GRID3 GIN - Settlement Extents v3.0 include:
The current version supersedes GRID3 GIN - Settlement Extents v2.0; the following changes were made:
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 GIN - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/7nqp-pj27. 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 two layers contained within the GRID3 GHA - Settlement Extents v3.0 include:
The current version supersedes GRID3 GHA - Settlement Extents v2.0; the following changes were made:
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 GHA - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/9scv-2v68. 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 two layers contained within the GRID3 GAB - Settlement Extents v3.0 include:
The current version supersedes GRID3 GAB - Settlement Extents v2.0; the following changes were made:
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 GAB - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/zmc2-r660. 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 two layers contained within the GRID3 ETH - Settlement Extents v3.0 include:
The current version supersedes GRID3 ETH - Settlement Extents v2.0; the following changes were made:
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 ETH - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/2hhy-yd24. 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 two layers contained within the GRID3 ERI - Settlement Extents v3.0 include:
The current version supersedes GRID3 ERI - Settlement Extents v2.0; the following changes were made:
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 ERI - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/1r2n-0j10. 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 two layers contained within the GRID3 DJI - Settlement Extents v3.0 include:
The current version supersedes GRID3 DJI - Settlement Extents v2.0; the following changes were made:
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 DJI - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/hwps-jn87. 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 two layers contained within the GRID3 CPV - Settlement Extents v3.0 include:
GRID3_CPV_settlement_extents_v3.gpkg: a spatial layer representing settlement polygons.
GRID3_CPV_settlement_grid_v3.gpkg: a spatial layer representing the centroids of settled grid cells.
The current version supersedes GRID3 CPV - 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 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
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 CPV - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/nrt8-am44. 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 two layers contained within the GRID3 COM - Settlement Extents v3.0 include:
The current version supersedes GRID3 COM - Settlement Extents v2.0; the following changes were made:
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 COM - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/5v9f-tm89. 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 two layers contained within the GRID3 COG - Settlement Extents v3.0 include:
The current version supersedes GRID3 COG - Settlement Extents v2.0; the following changes were made:
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 COG - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/pt06-ef20. 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 two layers contained within the GRID3 CMR - Settlement Extents v3.0 include:
The current version supersedes GRID3 CMR - Settlement Extents v2.0; the following changes were made:
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 CMR - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/hsw1-e629. 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 two layers contained within the GRID3 CIV - Settlement Extents v3.0 include:
The current version supersedes GRID3 CIV - Settlement Extents v2.0; the following changes were made:
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 CIV - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/5f1x-1356. 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 two layers contained within the GRID3 CAF - Settlement Extents v3.0 include:
The current version supersedes GRID3 CAF - Settlement Extents v2.0; the following changes were made:
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 CAF - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/b3h7-2k33. 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 two layers contained within the GRID3 BWA - Settlement Extents v3.0 include:
This is the settlement extents layer.
The current version supersedes GRID3 BWA - Settlement Extents v2.0; the following changes were made:
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 BWA - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/yk00-pw68. 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 two layers contained within the GRID3 BFA - Settlement Extents v3.0 include:
The current version supersedes GRID3 BFA - Settlement Extents v2.0; the following changes were made:
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 BFA - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/4z03-2v66. 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 two layers contained within the GRID3 BEN - Settlement Extents v3.0 include:
The current version supersedes GRID3 BEN - Settlement Extents v2.0; the following changes were made:
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 BEN- Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/yen9-aj46. 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 two layers contained within the GRID3 BDI - Settlement Extents v3.0 include:
The current version supersedes GRID3 BDI - Settlement Extents v2.0; the following changes were made:
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 BDI - Settlement Extents v3.0. New York: GRID3. https://doi.org/doi:10.7916/hgbb-ec60. 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 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 two layers contained within the GRID3 MYT - Settlement Extents v3.0 include:
GRID3_MYT_settlement_extents_v3.gpkg: a spatial layer representing settlement polygons.
GRID3_MYT_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 MYT - Settlement Extents v3.0. New York: GRID3. https://doi.org/10.7916/8vx3-fh25. 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
Variable name in shapefile | Title | Interpretation |
pop | Estimated population | Number of people per 1x1 square kilometer |
water30 | Need more than 30 minutes to get water | Percent of people who live in a household that takes more than 30 minutes to fetch and retrieve water |
toilet | Share toilets with others or do not have a toilet | Proportion of people who live in a household that shares toilets with other households or do not have a toilet |
no_piped | Have no piped-in drinking water | Percent of people who live in a household that does not have piped-in drinking water in the home |
hiv | Self report positive HIV result | Percent of adults (15-49) that self report a positive HIV result |
edu_no | Household head has no education | Percent of people living in a household whose head has no education |
edu_prim | Household head has some or complete primary education | Percent of people living in a household whose head has some or complete primary education |
edu_sech | Household head has at least some secondary education | Percent of people living in a household whose head has at least some secondary education |
radio | Have access to radio or have regular adult radio listeners at home | Percent of people in a household that owns a radio or has at least one adult (15-49) that listens to radio at least once per week |
tv | Have access to TV or have regular adult TV viewers at home | Percent of people in a household that owns a TV or has at least one adult (15-49) that watches TV at least once per week |
news | Regularly read newspaper | Percent of adults (15-49) that reads newspaper at least once per week |
pop1549 | Estimated adult population (15-49) | Number of adults (15-49) per 1x1 square kilometer |
exp_* | Exposure Risk Profile | This profile is an index representing risk of exposure to COVID-19. Columns exp_1 to exp_5 show the number of people in an area at different risk levels. Column exp_s shows the average risk score at the administrative level of interest. |
comor_* | Co-morbidities Risk Profile | This profile identifies population that may be at-risk of severe COVID-19 infection or hospitalization. Columns comor_1 to comor_5 show the number of people in an area at different risk levels. Column comor_s shows the average risk score at the administrative level of interest. |
socio_* | Socio-economic Vulnerability Risk | This profile is an index of socio-economic vulnerability to COVID-19, highlighting poor populations with limited options to cope with economic shocks. Columns socio_1 to socio_5 show the number of people in an area at different risk levels. Column socio_s shows the average risk score at the administrative level of interest. |
com_* | Communication Access Risk Profile | This profile identifies populations with limited access to communications media. Columns com_1 to com_5 show the number of people in an area at different risk levels. Column com_s shows the average risk score at the administrative level of interest. |
access_* | Health Facility Access Risk | This profile identifies population facing high risk resulting from limited access to health facilities. Columns access_1 to access_5 show the number of people in an area at different risk levels. Column access_s shows the average risk score at the administrative level of interest. |
total_* | Total COVID-19 Risk | This profile is an index of the total COVID-19 Risk combining the comorbidities profile, the health facilities access risk profile, and the exposure risk profile. Columns total_1 to total_5 show the number of people in an area at different risk levels. Column total_s shows the average risk score at the administrative level of interest. |
These data feature gridded population estimates (~100 m grid cells) and population estimates for specific age groups, with national coverage for Zambia.
The zipfiles contain the following files:
ZMB_population_v1_0_gridded.tif
This geotiff raster contains estimates of total population size for each approximately 100m grid cell (0.0008333 decimal degrees grid) across Zambia. The values are the mean of the posterior probability distribution for the predicted population size in each grid cell. NA values represent areas that were mapped as unsettled according to building footprints data [8]. Note: This raster is accompanied by one ancillary file that contains metadata (ZMB_population_v1_0_gridded.tif.xml).
ZMB_population_v1_0_uncertainty.tif
This geotiff raster contains estimates of uncertainty in the population estimates within each approximately 100m grid cell across Zambia. The uncertainty values are the difference between the upper and lower 95% credible intervals of the posterior prediction divided by the mean of the posterior prediction: (upper – lower)/mean. These numbers provide a comparable measure of uncertainty in population estimates across the country. Uncertainty estimates cannot be summed across grid cells to produce an uncertainty measure for a multi-cell area. Uncertainty for multiple cells can be calculated using the cells’ posterior predictions. Note: This raster is accompanied by one ancillary file that contains metadata (ZMB_population_v1_0_uncertainty.tif.xml).
ZMB_population_v1_0_agesex.zip
This zip file contains 40 rasters in geotiff format. Each raster provides gridded population estimates for an age-sex group. 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 using the gridded age-sex proportions from Carioli et al. [1] by multiplying the gridded population estimates(ZMB_population_v1_0_gridded.tif) by the gridded age-sex proportions which differ by region. While this data represents population counts, values contain decimals, i.e. fractions of people. This is because we do not estimate which grid cell each individual in a given age group occupies. For example, if four grid cells next to each other have values of 0.25 this indicates that there is 1 person of that age group somewhere in those four grid cells.
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 gohere.
Data Citation: WorldPop (School of Geography and Environmental Science, University of Southampton). 2020. Bottom-up gridded population estimates for Zambia, version 1.0. https://dx.doi.org/10.5258/SOTON/WP00662 CREDITS: The modelling work was led by Claire A. Dooley with support from Douglas R. Leasure. Geospatial data processing was carried out by Heather R. Chamberlain, Claire A. Dooley and Oliver Pannell. Coordination and stakeholder engagement was led by Heather R. Chamberlain and Claire A. Dooley with support from Polly Marshall. Oversight was provided by Andrew J. Tatem and Attila N. Lazar.
These 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 and 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.
Nigeria country-wide operational state boundaries (administrative level 1). Released in September 2020.
The index equally weights the comorbidities profile, the health facilities access risk profile, and the exposure risk profile. This feature layer aggregates scores to the LGA 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/
Source: Fraym 2020
The Fraym platform weaves together the latest satellite imagery and geostatistical datasets with professionally enumerated household surveys. This allows for the disaggregation and re-aggregation of large datasets to cover any geographically bounded area. Indicators are drawn and harmonized from a wide variety of household surveys and other data sources.
These include the following sources:
USAID: Demographic and health surveys
United Nations: UN population division database
World Bank: Enterprise surveys, living standards, global index surveys, and respective country statistics
National Statistical Offices: National censuses and surveys covering population, businesses, health, housing, agriculture, and other areas
International Monetary Fund: World economic outlook databases and respective country statistics
National Air and Space Administration: Remote sensing satellite data, such as vegetation, temperature, and precipitation
USGS: Landscan, Google Earth, GeoData Institute, OSM
WorldPop: Population density by age groups
The data is available in both spatial and tabular file formats.
Coordinate system: GCS WGS 1984
For full methodological details, please see data release notes available for download here.
Download the data as a zip file.
Copyright\n 2023. Sierra Leone Ministry of Health and Sanitation (MoHS) and \nTrustees of Columbia University in the City of New York.
Dataset citation:
Sierra Leone Ministry of Health and Sanitation (MoHS) and Center for International Earth Science Information Network (CIESIN), Columbia University. 2023. Sierra Leone National Health Facilities Dataset Version 01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/ag19-s334. Accessed DAY MONTH YEAR
Proportion of people who live in a household that does not have water for handwashing in the home. The higher the value, the greater proportion of people that live in a household with no water for handwashing per 1x1 square kilometer. Grids with less than 30 people are replaced with a value of NA.
Source: Fraym; Base Survey: Zambia DHS 2018
Population estimate from WorldPop's Bottom-up gridded population layer. Access for the WorldPop population estimates full methodology visit https://wopr.worldpop.org/
Proportion of people who live in a household that takes more than 30 minutes to fetch and retrieve water. The higher the value, the greater proportion of people that live in a household that takes more than 30 minutes to fetch and retrieve water per 1x1 square kilometer. Grids with less than 30 people are replaced with a value of NA.
Source: Fraym; Base Survey: Zambia DHS 2018
Population estimate from WorldPop's Bottom-up gridded population layer. Access for the WorldPop population estimates full methodology visit https://wopr.worldpop.org/
Proportion of people who live in a household that does not have piped-in drinking water in the home. The higher the value, the greater proportion of people that live in a household with no piped-in drinking water per 1x1 square kilometer. Grids with less than 30 people are replaced with a value of NA.
Source: Fraym; Base Survey: Zambia DHS 2018
Population estimate from WorldPop's Bottom-up gridded population layer. Access for the WorldPop population estimates full methodology visit https://wopr.worldpop.org/
Proportion of adult men (15-49) that are literate in Zambia. The higher the value, the greater percentage of adult men (15-49) that are able to read at least parts of sentence per 1x1 square kilometer. Grids with less than 30 population are replaced with a value of NA.
Source: Fraym; Base Survey: Zambia DHS 2018
Population estimate from WorldPop's Bottom-up gridded population layer. Access for the WorldPop population estimates full methodology visit https://wopr.worldpop.org/
Proportion of adults (15-49) that listen to radio at least once per week. The higher the value, the greater percentage of adults (15-49) that listen to radio at least once per week per 1x1 square kilometer. Grids with 30 population are replaced with a value of NA.
Source: Fraym; Base Survey: Zambia DHS 2018
Population estimate from WorldPop's Bottom-up gridded population layer. Access for the WorldPop population estimates full methodology visit https://wopr.worldpop.org/
This layer is an index based on sum of Z-scores that represent WASH risk in the 1km squared grid. Five indicators are equally weighted within the WASH component: soap for handwashing inside the home is unavailable, water for handwashing inside the home is unavailable, household must walk 30 or more minutes roundtrip to collect drinking water, household shares toilet with other households or does not have a toilet, and household does not have piped-in drinking water. Indicators are combined with z-scores at the 1km squared grid level. Grids with population less than 30 are replaced with a value of NA.
Source: Fraym; Base Survey: Zambia DHS 2018
Population estimate from WorldPop's Bottom-up gridded population layer. Access for the WorldPop population estimates full methodology visit https://wopr.worldpop.org/
This layer is an index of socio-economic vulnerability to COVID-19 in the 1km squared grid, highlighting poor populations with limited options to cope with economic shocks. This layer classifies the raw PCA scores into quintles, with 1 defined as lowest risk and 5 defined as highest risk. Grids with less than 0 population are replaced with a value of NA.
Source: Fraym; Base Survey: Zambia DHS 2018
Population estimate from WorldPop's Bottom-up gridded population layer. Access for the WorldPop population estimates full methodology visit https://wopr.worldpop.org/
This score ranks the percentage of population, at the LGA level, 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.
Source: Fraym 2020
The Fraym platform weaves together the latest satellite imagery and geostatistical datasets with professionally enumerated household surveys. This allows for the disaggregation and re-aggregation of large datasets to cover any geographically bounded area. Indicators are drawn and harmonized from a wide variety of household surveys and other data sources.
These include the following sources:
USAID: Demographic and health surveys
United Nations: UN population division database
World Bank: Enterprise surveys, living standards, global index surveys, and respective country statistics
National Statistical Offices: National censuses and surveys covering population, businesses, health, housing, agriculture, and other areas
International Monetary Fund: World economic outlook databases and respective country statistics
National Air and Space Administration: Remote sensing satellite data, such as vegetation, temperature, and precipitation
USGS: Landscan, Google Earth, GeoData Institute, OSM
WorldPop: Population density by age groups
GRID3 Health Facilities
This score is created via a principal component analysis (PCA) with a list of indicators of socio-economic status:
Household level (non-farm employment, hectares of farmland owned, number of livestock owned, educational attainment)
Housing type (material for roof, floor, and walls)
Food security (proxied by child wasting)
Financial inclusion (household member has a bank account)
Domestic violence (household experienced physical, sexual, or emotional abuse of women at last once in a year)
This index takes into account urban and rural differences by conducting the PCA for urban and rural settings and combining results for a national index.
This feature layer aggregates scores to the LGA boundaries from GRID3 GDB v1.70.
Population estimate from WorldPop's Bottom-up gridded population layer. Access for the WorldPop population estimates full methodology visit https://wopr.worldpop.org/
Source: Fraym 2020
The Fraym platform weaves together the latest satellite imagery and geostatistical datasets with professionally enumerated household surveys. This allows for the disaggregation and re-aggregation of large datasets to cover any geographically bounded area. Indicators are drawn and harmonized from a wide variety of household surveys and other data sources.
These include the following sources:
USAID: Demographic and health surveys
United Nations: UN population division database
World Bank: Enterprise surveys, living standards, global index surveys, and respective country statistics
National Statistical Offices: National censuses and surveys covering population, businesses, health, housing, agriculture, and other areas
International Monetary Fund: World economic outlook databases and respective country statistics
National Air and Space Administration: Remote sensing satellite data, such as vegetation, temperature, and precipitation
USGS: Landscan, Google Earth, GeoData Institute, OSM
WorldPop: Population density by age groups
This score equally weights two components:
Female Adult Obesity Rate
Elderly Population
Female adult obesity rate is defined as the percentage of female adults aged 15 to 49 with a body mass index of over 30. This indicator is only available for females. Elderly population is defined as the number of people over the age of 50. Indicators are combined with z-scores at the 1km squared grid level.
This feature layer aggregates scores to the LGA 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/
Source: Fraym 2020
The Fraym platform weaves together the latest satellite imagery and geostatistical datasets with professionally enumerated household surveys. This allows for the disaggregation and re-aggregation of large datasets to cover any geographically bounded area. Indicators are drawn and harmonized from a wide variety of household surveys and other data sources.
These include the following sources:
USAID: Demographic and health surveys
United Nations: UN population division database
World Bank: Enterprise surveys, living standards, global index surveys, and respective country statistics
National Statistical Offices: National censuses and surveys covering population, businesses, health, housing, agriculture, and other areas
International Monetary Fund: World economic outlook databases and respective country statistics
National Air and Space Administration: Remote sensing satellite data, such as vegetation, temperature, and precipitation
USGS: Landscan, Google Earth, GeoData Institute, OSM
WorldPop: Population density by age groups
The proportion of people having access to a radio or television were aggregated to the district sanitaire level. The district sanitaire is an operation administrative level used by the Ministry of Health created from groupings of administrative level 3 (commune) subnational boundaries. A higher value indicates better population-level radio or television access by district sanitaire. Interpolated MIS survey data 2017. The proportion of people having access to radio or television is derived from Fraym raster layers at 1 square kilometer grid cell resolution.
Suggested Data Citation: Fraym. 2021. GRID3 Burkina Faso Media Access Indicators as Proportion of Population with Access to Radio or Television Aggregated by District Sanitaire. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). URL. Accessed DAY MONTH YEAR
Variable name in shapefile | Title | Interpretation |
pop | Estimated population | Number of people per 1x1 square kilometer |
water30 | Need more than 30 minutes to get water | Percent of people who live in a household that takes more than 30 minutes to fetch and retrieve water |
toilet | Share toilets with others or do not have a toilet | Proportion of people who live in a household that shares toilets with other households or do not have a toilet |
no_piped | Have no piped-in drinking water | Percent of people who live in a household that does not have piped-in drinking water in the home |
hiv | Self report positive HIV result | Percent of adults (15-49) that self report a positive HIV result |
edu_no | Household head has no education | Percent of people living in a household whose head has no education |
edu_prim | Household head has some or complete primary education | Percent of people living in a household whose head has some or complete primary education |
edu_sech | Household head has at least some secondary education | Percent of people living in a household whose head has at least some secondary education |
radio | Have access to radio or have regular adult radio listeners at home | Percent of people in a household that owns a radio or has at least one adult (15-49) that listens to radio at least once per week |
tv | Have access to TV or have regular adult TV viewers at home | Percent of people in a household that owns a TV or has at least one adult (15-49) that watches TV at least once per week |
news | Regularly read newspaper | Percent of adults (15-49) that reads newspaper at least once per week |
pop1549 | Estimated adult population (15-49) | Number of adults (15-49) per 1x1 square kilometer |
exp_* | Exposure Risk Profile | This profile is an index representing risk of exposure to COVID-19. Columns exp_1 to exp_5 show the number of people in an area at different risk levels. Column exp_s shows the average risk score at the administrative level of interest. |
comor_* | Co-morbidities Risk Profile | This profile identifies population that may be at-risk of severe COVID-19 infection or hospitalization. Columns comor_1 to comor_5 show the number of people in an area at different risk levels. Column comor_s shows the average risk score at the administrative level of interest. |
socio_* | Socio-economic Vulnerability Risk | This profile is an index of socio-economic vulnerability to COVID-19, highlighting poor populations with limited options to cope with economic shocks. Columns socio_1 to socio_5 show the number of people in an area at different risk levels. Column socio_s shows the average risk score at the administrative level of interest. |
com_* | Communication Access Risk Profile | This profile identifies populations with limited access to communications media. Columns com_1 to com_5 show the number of people in an area at different risk levels. Column com_s shows the average risk score at the administrative level of interest. |
access_* | Health Facility Access Risk | This profile identifies population facing high risk resulting from limited access to health facilities. Columns access_1 to access_5 show the number of people in an area at different risk levels. Column access_s shows the average risk score at the administrative level of interest. |
total_* | Total COVID-19 Risk | This profile is an index of the total COVID-19 Risk combining the comorbidities profile, the health facilities access risk profile, and the exposure risk profile. Columns total_1 to total_5 show the number of people in an area at different risk levels. Column total_s shows the average risk score at the administrative level of interest. |
This score equally weights two components:
Female Adult Obesity Rate
Elderly Population
Female adult obesity rate is defined as the percentage of female adults aged 15 to 49 with a body mass index of over 30. This indicator is only available for females. Elderly population is defined as the number of people over the age of 50. Indicators are combined with z-scores at the 1km squared grid level.
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/
Source: Fraym 2020
The Fraym platform weaves together the latest satellite imagery and geostatistical datasets with professionally enumerated household surveys. This allows for the disaggregation and re-aggregation of large datasets to cover any geographically bounded area. Indicators are drawn and harmonized from a wide variety of household surveys and other data sources.
These include the following sources:
USAID: Demographic and health surveys
United Nations: UN population division database
World Bank: Enterprise surveys, living standards, global index surveys, and respective country statistics
National Statistical Offices: National censuses and surveys covering population, businesses, health, housing, agriculture, and other areas
International Monetary Fund: World economic outlook databases and respective country statistics
National Air and Space Administration: Remote sensing satellite data, such as vegetation, temperature, and precipitation
USGS: Landscan, Google Earth, GeoData Institute, OSM
WorldPop: Population density by age groups
This score ranks the percentage of population, at the ward level, 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.
Source: Fraym 2020
The Fraym platform weaves together the latest satellite imagery and geostatistical datasets with professionally enumerated household surveys. This allows for the disaggregation and re-aggregation of large datasets to cover any geographically bounded area. Indicators are drawn and harmonized from a wide variety of household surveys and other data sources.
These include the following sources:
USAID: Demographic and health surveys
United Nations: UN population division database
World Bank: Enterprise surveys, living standards, global index surveys, and respective country statistics
National Statistical Offices: National censuses and surveys covering population, businesses, health, housing, agriculture, and other areas
International Monetary Fund: World economic outlook databases and respective country statistics
National Air and Space Administration: Remote sensing satellite data, such as vegetation, temperature, and precipitation
USGS: Landscan, Google Earth, GeoData Institute, OSM
WorldPop: Population density by age groups
GRID3 Health Facilities
The index equally weights the comorbidities profile, the health facilities access risk profile, and the exposure risk profile. 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/
Source: Fraym 2020
The Fraym platform weaves together the latest satellite imagery and geostatistical datasets with professionally enumerated household surveys. This allows for the disaggregation and re-aggregation of large datasets to cover any geographically bounded area. Indicators are drawn and harmonized from a wide variety of household surveys and other data sources.
These include the following sources:
USAID: Demographic and health surveys
United Nations: UN population division database
World Bank: Enterprise surveys, living standards, global index surveys, and respective country statistics
National Statistical Offices: National censuses and surveys covering population, businesses, health, housing, agriculture, and other areas
International Monetary Fund: World economic outlook databases and respective country statistics
National Air and Space Administration: Remote sensing satellite data, such as vegetation, temperature, and precipitation
USGS: Landscan, Google Earth, GeoData Institute, OSM
WorldPop: Population density by age groups
Proportion of people who live in a household that does not have soap or detergent in the home in Zambia. The higher the value, the greater proportion of people that live in a household with no soap or detergent per 1x1 square kilometer. Grids with less than 30 people are replaced with a value of NA.
Source: Fraym; Base Survey: Zambia DHS 2018
Population estimate from WorldPop's Bottom-up gridded population layer. Access for the WorldPop population estimates full methodology visit https://wopr.worldpop.org/
Source: Fraym 2020
The Fraym platform weaves together the latest satellite imagery and geostatistical datasets with professionally enumerated household surveys. This allows for the disaggregation and re-aggregation of large datasets to cover any geographically bounded area. Indicators are drawn and harmonized from a wide variety of household surveys and other data sources.
These include the following sources:
Each of the 5 malaria risk elements is included as both an estimated proportion of relevant population and as an estimated count aggregated to the region level (admin 1). These values are malaria incidence in children under 5; bed net use in children under 5, adult female bed net use, general population bed net use; and general population bed net access. The 1km x 1km Fraym raster data products based on the MIS2017 survey data were aggregated to admin 1 level (region). The number of survey clusters in each region from the original MIS2017 survey are also included.
Data Citation: Fraym. 2021.GRID3 Burkina Faso Malaria Risk Indicators by Region (Admin1). Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). URL. Accessed DAY MONTH YEAR
bfa_child_ | Population of children less than 5 years old of the administrative area |
bfa_access | Proportion of people living in households that have a mosquito net for sleeping in the the administrative area |
bfa_bednet | Proportion of people who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_bedn_1 | Proportion of female adults (15-49) who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_bedn_2 | Proportion of children less than 5 years old who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_incide | Malaria incidence among children less than 5 years old in the administrative area |
bfa_acce_1 | Number of people living in households that have a mosquito net for sleeping in the the administrative area |
bfa_bedn_3 | Number of people who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_bedn_4 | Number of female adults (15-49) who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_bedn_5 | Number of children less than 5 years old who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_inci_1 | Malaria incidence in terms of number of children less than 5 years old in the administrative area |
Cluster_co | Count of survey clusters within the polygon |
Each of the 5 malaria risk elements is included as both an estimated proportion of relevant population and as an estimated count aggregated to the province level (admin 2). These values are malaria incidence in children under 5; bed net use in children under 5, adult female bed net use, general population bed net use; and general population bed net access. The 1km x 1km Fraym raster data products based on the MIS2017 survey data were aggregated to administrative level 2 (province). The number of survey clusters in each province from the original MIS2017 survey are also included.
Data Citation: Fraym. 2021. GRID3 Burkina Faso Malaria Risk Indicators by Province (Admin2). Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). URL. Accessed DAY MONTH YEAR
bfa_child_ | Population of children less than 5 years old of the administrative area |
bfa_access | Proportion of people living in households that have a mosquito net for sleeping in the the administrative area |
bfa_bednet | Proportion of people who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_bedn_1 | Proportion of female adults (15-49) who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_bedn_2 | Proportion of children less than 5 years old who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_incide | Malaria incidence among children less than 5 years old in the administrative area |
bfa_acce_1 | Number of people living in households that have a mosquito net for sleeping in the the administrative area |
bfa_bedn_3 | Number of people who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_bedn_4 | Number of female adults (15-49) who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_bedn_5 | Number of children less than 5 years old who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_inci_1 | Malaria incidence in terms of number of children less than 5 years old in the administrative area |
Cluster_co | Count of survey clusters within the polygon |
Each of the 5 malaria risk elements is included as both an estimated proportion of relevant population and as an estimated count aggregated to the commune level (admin 3). These values are malaria incidence in children under 5; bed net use in children under 5, adult female bed net use, general population bed net use; and general population bed net access. The 1km x 1km Fraym raster data products based on the MIS2017 survey data were aggregated to administrative level 3 (commune). The number of survey clusters in each region from the original MIS2017 survey are also included.
Data Citation: Fraym. 2021.GRID3 Burkina Faso Malaria Risk Indicators by Commune (Admin3). Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). URL. Accessed DAY MONTH YEAR
bfa_child_ | Population of children less than 5 years old of the administrative area |
bfa_access | Proportion of people living in households that have a mosquito net for sleeping in the the administrative area |
bfa_bednet | Proportion of people who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_bedn_1 | Proportion of female adults (15-49) who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_bedn_2 | Proportion of children less than 5 years old who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_incide | Malaria incidence among children less than 5 years old in the administrative area |
bfa_acce_1 | Number of people living in households that have a mosquito net for sleeping in the the administrative area |
bfa_bedn_3 | Number of people who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_bedn_4 | Number of female adults (15-49) who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_bedn_5 | Number of children less than 5 years old who sleep under an ever-treated or LLIN bed-net in the administrative area |
bfa_inci_1 | Malaria incidence in terms of number of children less than 5 years old in the administrative area |
Cluster_co | Count of survey clusters within the polygon |
This score equally weights two components:
accessibility to health facilities
usage of health facilities
Accessibility is defined as time to travel to health facilities. This approach assumes that individuals will travel via vehicle if there is a road and will walk if there is no road. Vulnerability is ranked into five categories by type of health facility (primary or secondary) and accessibility. Areas less than 30 minutes away from a secondary facility are the least vulnerable and areas further than one hour from either a primary or secondary facility are the most vulnerable. Health facility locations are from a 2017 dataset published by ALHASAN Systems Private Limited through the Humanitarian Data Exchange (HDX). Usage of health facilities is proxied by percentage of women that do not visit health facilities and do not see field workers in a year. Vulnerability from limited usage is ranked into five categories by quintile. Areas in the highest quintile are considered to be the most vulnerable.
This feature layer aggregates scores to the state boundaries from GRID3 GDB v1.69.
Source: Fraym 2020
The Fraym platform weaves together the latest satellite imagery and geostatistical datasets with professionally enumerated household surveys. This allows for the disaggregation and re-aggregation of large datasets to cover any geographically bounded area. Indicators are drawn and harmonized from a wide variety of household surveys and other data sources.
These include the following sources:
USAID: Demographic and health surveys
United Nations: UN population division database
World Bank: Enterprise surveys, living standards, global index surveys, and respective country statistics
National Statistical Offices: National censuses and surveys covering population, businesses, health, housing, agriculture, and other areas
International Monetary Fund: World economic outlook databases and respective country statistics
National Air and Space Administration: Remote sensing satellite data, such as vegetation, temperature, and precipitation
USGS: Landscan, Google Earth, GeoData Institute, OSM
WorldPop: Population density by age groups
Population estimate from WorldPop's Bottom-up gridded population layer. Access for the WorldPop population estimates full methodology visit https://wopr.worldpop.org/
This score equally weights two components:
Accessibility to health facilities
Usage of health facilities
Accessibility is defined as time to travel to health facilities. This approach assumes that individuals will travel via vehicle if there is a road and will walk if there is no road. Vulnerability is ranked into five categories by type of health facility (primary or secondary) and accessibility. Areas less than 30 minutes away from a secondary facility are the least vulnerable and areas further than one hour from either a primary or secondary facility are the most vulnerable. Health facility locations are from a 2017 dataset published by ALHASAN Systems Private Limited through the Humanitarian Data Exchange (HDX). Usage of health facilities is proxied by percentage of women that do not visit health facilities and do not see field workers in a year. Vulnerability from limited usage is ranked into five categories by quintile. Areas in the highest quintile are considered to be the most vulnerable.
This feature layer aggregates the index values by ward 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/
Source: Fraym 2020
The Fraym platform weaves together the latest satellite imagery and geostatistical datasets with professionally enumerated household surveys. This allows for the disaggregation and re-aggregation of large datasets to cover any geographically bounded area. Indicators are drawn and harmonized from a wide variety of household surveys and other data sources.
These include the following sources:
USAID: Demographic and health surveys
United Nations: UN population division database
World Bank: Enterprise surveys, living standards, global index surveys, and respective country statistics
National Statistical Offices: National censuses and surveys covering population, businesses, health, housing, agriculture, and other areas
International Monetary Fund: World economic outlook databases and respective country statistics
National Air and Space Administration: Remote sensing satellite data, such as vegetation, temperature, and precipitation
USGS: Landscan, Google Earth, GeoData Institute, OSM
WorldPop: Population density by age groups
GRID3 Health Facilities
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/
Source: Fraym 2020
The Fraym platform weaves together the latest satellite imagery and geostatistical datasets with professionally enumerated household surveys. This allows for the disaggregation and re-aggregation of large datasets to cover any geographically bounded area. Indicators are drawn and harmonized from a wide variety of household surveys and other data sources.
These include the following sources:
USAID: Demographic and health surveys
United Nations: UN population division database
World Bank: Enterprise surveys, living standards, global index surveys, and respective country statistics
National Statistical Offices: National censuses and surveys covering population, businesses, health, housing, agriculture, and other areas
International Monetary Fund: World economic outlook databases and respective country statistics
National Air and Space Administration: Remote sensing satellite data, such as vegetation, temperature, and precipitation
USGS: Landscan, Google Earth, GeoData Institute, OSM
WorldPop: Population density by age groups
The exposure risk score equally weights three components:
population density
proximity to others in the household
water, sanitation, and hygiene.
Three indicators are equally weighted within the proximity to others in the household component: intergenerational households (household has a child less than eleven years old and a person above 60 years old), average number of household members per sleeping room, and adults aged 15 to 49 employed in essential occupations (health professions, construction, manufacturing, transport, sales, textiles, protective services). Five indicators are equally weighted within the water, sanitation, and hygiene component: soap for hand-washing inside the home is unavailable, water for hand-washing inside the home is unavailable, household must walk 30 or more minutes roundtrip to collect drinking water, household shares toilet with other households or does not have a toilet, and household does not have piped-in drinking water. Population density is defined as population at the 1km squared level. Indicators within components are combined with z-scores at the 1km squared grid level. This feature layer aggregates scores to the states 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/
The Fraym platform weaves together the latest satellite imagery and geostatistical datasets with professionally enumerated household surveys. This allows for the disaggregation and re-aggregation of large datasets to cover any geographically bounded area. Indicators are drawn and harmonized from a wide variety of household surveys and other data sources.
These include the following sources:
USAID: Demographic and health surveys
United Nations: UN population division database
World Bank: Enterprise surveys, living standards, global index surveys, and respective country statistics
National Statistical Offices: National censuses and surveys covering population, businesses, health, housing, agriculture, and other areas
International Monetary Fund: World economic outlook databases and respective country statistics
National Air and Space Administration: Remote sensing satellite data, such as vegetation, temperature, and precipitation
USGS: Landscan, Google Earth, GeoData Institute, OSM
WorldPop: Population density by age groups
This shapefile provides HIV statistics by state that can be used in conjunction with the co-morbidities risk profile to provide more nuance on levels of risk by state.
Note that values of 0 mean there is no data for that particular state.
The source of data for HIV prevalence rates is the Nigeria Institute for Health Metrics and Evaluation (IHME), HIV Prevalence Geospatial Estimates 2000-2017.
The settlements’ extents are derived from Ecopia’s building footprints. Data analysis and processing were achieved entirely using Rust, Python, GDAL, LibGEOS. Building footprint features within .001 decimal degrees of each other, approximately 130 meters, are converted to multipart polygons. The multipart polygons are then buffered by 50 meters. All polygons are then unioned and dissolved. Finally, any inner rings caused by open areas, such as parks or sports fields, are filled.
The data sets include the following themes: Administration, Agriculture and Mining, Built and Settled Environment, Government, Religion, Landmark/Infrastructure. In addition to categorization by theme, the “Type” field provides further classification for each point. Each point includes the standardized “Name” field which can be used for data labeling.
The schools and health facilities are not included in this data and are provided as two separate data layers.
The dataset is available for download in shapefile format and can be viewed in Geographic Information Systems(GIS) such as ArcMap, QGIS, or Google Earth (Pro).
The data is available for all of Zambia.
It has the following attributes: Name, Original Name, Type, Sub Type, Source, Province (Code), District (Code), Ward (Code), Constituency (Code), Global ID, LAT, LONG
This shapefile provides 2014 TB statistics by state that can be used in conjunction with the co-morbidities risk profile to provide more nuance on levels of risk by state. TB rates are calculated as total cases divided by the population.
Note that values of 0 mean there is no data for that particular state.
The source of data for TB rates is the Nigeria Ministry of Health National Tuberculosis & Leprosy Control Programme Annual Report for 2014, Institute for Health Metrics and Evaluation (IHME), Ministry of Health.