GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development)
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  • 40+ Downloads
    Updated 27 January 2021 | Dataset date: May 17, 2020-October 04, 2022
    This dataset updates: As needed
    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) project funded by the Bill and Melinda Gates Foundation (BMGF) and the United Kingdom’s Department for International Development (OPP1182408). Project partners include WorldPop at the University of Southampton, the United Nations Population Fund (UNFPA), Center for International Earth Science Information Network (CIESIN) in the Earth Institute at Columbia University, and the Flowminder Foundation. The Zambia Statistics Agency supported and facilitated this work, and provided the household survey datasets. 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. Note, these data are operational population estimates and are not official government statistics For further details, please, read ZMB_population_v1_0_README.pdf Recommended 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
  • 30+ Downloads
    Updated 16 December 2021 | Dataset date: November 17, 2021-October 04, 2022
    This dataset updates: As needed
    This data release provides gridded population estimates (spatial resolution of 3 arc-seconds, approximately 100 m grid cells) with national coverage for Nigeria, along with estimates of the number of people belonging to various age-sex groups. Version 2.0 is an update to the previous version 1.2 gridded population estimates and is based on more recent and detailed settlement information and a different regional boundary definition. These model-based population estimates most likely represent the time period around 2019, corresponding to the period when the satellite imagery was processed to generate building footprints. Populations are mapped only into areas where residential settlements are predicted. These data were produced by the WorldPop Research Group at the University of Southampton in collaboration with the National Population Commission of Nigeria. This work was part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3 ) programme with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Foreign, Commonwealth & Development Office (INV 009579, formerly OPP 1182425). Project partners included the United Nations Population Fund, Center for International Earth Science Information Network (CIESIN), a center within the Columbia Climate School at Columbia University, and the Flowminder Foundation. Statistical modelling was led by Chris Jochem and Doug Leasure additional support and oversight from Attila Lazar and Andy Tatem. Chris Lloyd provided the residential building classification. The microcensus data were originally collected by eHealth Africa and Oak Ridge National Laboratory with support from the Bill and Melinda Gates Foundation. The WorldPop grou and GRID3 partners are acknowledged for their project support. RELEASE CONTENT NGA_population_v2_0_gridded.zip NGA_population_v2_0_admin.zip NGA_population_v2_0_sql.sql NGA_population_v2_0_mastergrid.tif NGA_population_v2_0_tiles.zip NGA_population_v2_0_agesex.zip LICENSE These data (1-6) may be redistributed using a Creative Commons Attribution 4.0 International (CC BY 4.0) License. Recommended citations WorldPop and National Population Commission of Nigeria. 2021. Bottom-up gridded population estimates for Nigeria, version 2.0. WorldPop, University of Southampton. doi: 10.5258/SOTON/WP00729. For further details, please, read NGA_population_v2_0_README.pdf
  • 20+ Downloads
    Updated 17 February 2022 | Dataset date: July 21, 2021-October 04, 2022
    This dataset updates: As needed
    These data consist of modelled gridded population estimates produced at a spatial resolution of approximately 100m across the Haut-Katanga, Haut-Lomami, Ituri, Kasaï, Kasaï-Oriental, Lomami and Sud-Kivu provinces in the Democratic Republic of the Congo (DRC). The estimates comprise total population counts created using a Bayesian statistical model and post-hoc breakdowns in 40 age and sex groups. The main input data were derived from a dedicated microcensus survey carried out in the targeted provinces throughout March and April 2021. The microcensus was led by the Flowminder Foundation, the École de Santé Publique de Kinshasa, the WorldPop Research Group at the University of Southampton and the Bureau Central du Recensement, which is part of the Institut National de la Statistique of the DRC. Other essential input data include metrics derived from building footprints, which were automatically delineated by Ecopia.AI in 2021 using satellite imagery collected by Maxar Technologies between 2010 and 2021. The modelled population estimates represent the period of the microcensus but their consistency may be impacted by the accuracy of the building footprints, particularly in the areas where the satellite imagery used for automatic delineation was outdated. These data were produced by the WorldPop Research Group at the University of Southampton as part of the GRID3 Mapping for Health Project. This project was delivered under the leadership of the Ministry of Public Health, Hygiene and Prevention of the DRC and funded by Gavi, the Vaccine Alliance (RM 867204 20A2). The project was led by the Flowminder Foundation and the Center for International Earth Science Information Network (CIESIN) at Columbia University, in collaboration with the WorldPop Research Group at the University of Southampton and national partners including, but not limited to, the École de Santé Publique de Kinshasa and both the Bureau Central du Recensement and the Institut National de la Statistique. This work was a continuation 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 (INV 009579, formerly OPP 1182425). The study was approved by the Faculty Ethics Committee of the University of Southampton (ERGO II 62716). The production of these data was led by Gianluca Boo (WorldPop](https://www.worldpop.org/) ) with support from Roland Hosner (Flowminder Foundation), Pierre Z Akilimali (École de Santé Publique de Kinshasa), Edith Darin (WorldPop), Heather R Chamberlain (WorldPop), Warren C Jochem (WorldPop), Patricia Jones (WorldPop), Roger Shulungu Runika (Institut National de la Statistique), Henri Marie Kazadi Mutombo (Bureau Central du Recensement), Attila N Lazar (WorldPop) and Andrew J Tatem (WorldPop). The authors acknowledge the support of their respective institutions in the completion of this work. Recommended citation: G Boo, R Hosner, PZ Akilimali, E Darin, HR Chamberlain, WC Jochem, P Jones, R Shulungu Runika, HM Kazadi Mutombo, AN Lazar and AJ Tatem. 2021. Modelled gridded population estimates for the HautKatanga, Haut-Lomami, Ituri, Kasaï, Kasaï-Oriental, Lomami and Sud-Kivu provinces in the Democratic Republic of the Congo (2021), version 3.0. WorldPop, University of Southampton, Flowminder Foundation, École de Santé Publique de Kinshasa, Bureau Central du Recensement and Institut National de la Statistique. doi:10.5258/SOTON/WP00720
  • 30+ Downloads
    Updated 29 June 2022 | Dataset date: June 29, 2022-October 04, 2022
    This dataset updates: As needed
    The "GRID3 DRC Health Zone and Health Area Boundaries - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces, Version 01" dataset consists of health area boundary polygons with names and attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). To conduct this work, the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support data collection and development for vaccination planning. Local healthcare workers were also directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative delivered in partnership with Flowminder and CIESIN (Columbia University), in collaboration with WorldPop at the University of Southampton, the Kinshasa School of Public Health, UNFPA, UNOPS, and Novel-T. GRID3 Mapping for Health is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of one layer: health catchment area polygon data and a table with the field descriptions for the layers. Filename: GRID3_DRC_health_catchment_area_boundaries_V01.gdb The following layers are included in the gdb: GRID3_DRC_health_catchment_zone_boundaries_5_prov_V01 GRID3_DRC_health_catchment_area_boundaries_5_prov_V01 Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Health Zone and Health Area Boundaries - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/hzrd-yq54. Accessed DAY MONTH YEAR.
  • 30+ Downloads
    Updated 29 June 2022 | Dataset date: June 29, 2022-October 04, 2022
    This dataset updates: As needed
    The "GRID3 DRC Health Facilities - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces, Version 01" dataset consists of health facility points with names and health catchment area attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). To conduct this work, the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support data collection and development for vaccination planning. Local healthcare workers were also directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative, delivered in partnership with Flowminder and CIESIN, and in collaboration with WorldPop at the University of Southampton, Kinshasa School of Public Health, UNFPA, UNOPS, and Novel-T. GRID3 Mapping for Health is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of four layers: health facility point data and a table with the field descriptions for the layer. The data are available for download in Esri file geodatabase format packaged in zip files. File name: GRID3_DRC_health_facilities_V01.gdb The following layers are included in the gdb: codebook_health_facilities GRID3_DRC_bcz_5_prov_V01 (The “BCZ” refers to the Bureau central de la Zone de Santé (Central Office of the Health Zone), which constitutes the framework structure for the organization and operation of the health zone. It is located either within the Hôpital Général de Référence (General Reference Hospital), or outside it but inside the health zone. The BCZ is the operational level of the DRC Health System and level of implementation of strategies from the Ministry of Health.) GRID3_DRC_health_facilities_5_prov_V01 (Government, NGO, or private health facilities that offer vaccination or public health services.) GRID3_DRC_KN_secondary_health_facilities_1_prov_V01 (The main goal of data collection conducted for the EPI was to identify health facilities (public and private) that provided services for public health and routine immunisations. However, at the demand of the DSNIS, all the facilities, public or private, were also geo-referenced. The healthcare services density is such in Kinshasa (with various facilities for private services, specialists, and faith healers opening and closing quite frequently) that GRID3 created a secondary health facilities layer to be able to differentiate the main public structures from others.) Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Health Facilities - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/0bvp-kp75. Accessed DAY MONTH YEAR.
  • 20+ Downloads
    Updated 29 June 2022 | Dataset date: June 29, 2022-October 04, 2022
    This dataset updates: As needed
    The "GRID3 DRC Religious Centres - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01" dataset consists of religious centre points with names and health catchment area attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). This dataset is one of five (5) datasets (along with the Settlements, Health Facilities, Health Catchment Area Boundaries, and Schools datasets)included in this Version 01 release. To conduct this work, the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support of data collection and development for vaccination planning. Local healthcare workers were also directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative, delivered in partnership with Flowminder and CIESIN, and in collaboration with WorldPop at the University of Southampton, Kinshasa School of Public Health, UNFPA, UNOPS, and Novel-T. GRID3 Mapping for Health is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of one geospatial layer: religious centre point data and a table with the field descriptions for the layer. File name: GRID3_DRC_religious_centers_V01.gdb The following layers are included in the gdb: codebook__religious_centers GRID3_DRC_religious_center_5_prov_V01 Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Religious Centres - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces - Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/z4vq-h095. Accessed DAY MONTH YEAR
  • 20+ Downloads
    Updated 29 June 2022 | Dataset date: June 29, 2022-October 04, 2022
    This dataset updates: As needed
    The "GRID3 DRC Schools - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01" dataset consists of school points with names and health catchment area attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). To conduct this work. the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support of data collection and development for vaccination planning. Local healthcare workers were also directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative, delivered in partnership with Flowminder and CIESIN, and in collaboration with WorldPop at the University of Southampton, Kinshasa School of Public Health, UNFPA, UNOPS and Novel-T. GRID3 Mapping for Health in DRC is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of one layer: schools point data and a table with the field descriptions for the layer. File name: GRID3_DRC_schools_V01.gdb The following layers are included in the gdb: codebook_schools GRID3_DRC_schools_5_prov_V01 Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Schools - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces- Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/a3d6-m921. Accessed DAY MONTH YEAR
  • 20+ Downloads
    Updated 29 June 2022 | Dataset date: June 29, 2022-October 04, 2022
    This dataset updates: As needed
    The "GRID3 DRC Settlements - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces, Version 01" dataset consists of settlement points with names and health catchment area attributes in the provinces of Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami in the Democratic Republic of the Congo (DRC). To conduct this work, the Center for International Earth Science Information Network (CIESIN) at Columbia University engaged with the mandated authorities in the DRC’s Ministry of Health who support data collection and development for vaccination planning. Local healthcare workers were directly involved in the mapping of the health catchment area boundaries at participatory events coordinated with in-country provincial coordinators and mappers, and in the collection of data in the field from January to July 2021. This work is part of the GRID3 Mapping for Health in the DRC project. Supported by Gavi through its INFUSE initiative, GRID3 Mapping for Health is a Ministry of Health initiative, delivered in partnership with Flowminder and CIESIN, and in collaboration with WorldPop at the University of Southampton, Kinshasa School of Public Health, UNFPA, UNOPS, and Novel-T. GRID3 Mapping for Health is a continuation of previous work conducted and/or supported in the DRC by the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The dataset consists of one layer: settlement point data and a table with the field descriptions for the layer. The data are available for download in Esri file geodatabase format packaged in zip files. File name: GRID3_DRC_settlements_names_V01.gdb The following layers are included in the gdb: codebook__settlements_names GRID3_DRC_settlements_names_5_prov_V01 Extent: Democratic Republic of the Congo: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami provinces. Dataset citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Ministère de la Santé Publique, Hygiène et Prévention, Democratic Republic of Congo, 2022. GRID3 DRC Settlements - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/pvdz-4x94. Accessed DAY MONTH YEAR.
  • 40+ Downloads
    Updated 4 April 2022 | Dataset date: April 04, 2022-October 04, 2022
    This dataset updates: As needed
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This data product contains all information contained in the previous “GRID3 Democratic Republic of the Congo Settlement Extents, Version 01.01” product, with updates. Updates in this version include: The addition of the WorldPop GRID3 Gridded Population Estimates for Age and Sex in Kinshasa, Kongo-Central, Kwango, Kwilu, and Mai-Ndombe provinces . This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2022. GRID3 Democratic Republic of the Congo Settlement Extents, Version 01.02. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/hbr4-ve53 . Accessed DAY MONTH YEAR
  • 50+ Downloads
    Updated 4 April 2022 | Dataset date: April 04, 2022-October 04, 2022
    This dataset updates: As needed
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This data product contains all information contained in the previous “GRID3 Nigeria Settlement Extents, Version 01.01” product, with updates. Updates in this version include: The addition of the WorldPop GRID3 Gridded Population Estimates for Age and Sex. This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2022. GRID3 Nigeria Settlement Extents, Version 01.02. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/1tb8-bm49 . Accessed DAY MONTH YEAR
  • 50+ Downloads
    Updated 4 April 2022 | Dataset date: April 04, 2022-October 04, 2022
    This dataset updates: As needed
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This data product contains all information contained in the previous “GRID3 Senegal Settlement Extents, Version 01.01” product, with updates. Updates in this version include: The addition of the WorldPop GRID3 Gridded Population Estimates for total population and by sex. This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2022. GRID3 Senegal Settlement Extents, Version 01.02. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/5jy1-7y15 . Accessed DAY MONTH YEAR
  • 10+ Downloads
    Updated 15 February 2022 | Dataset date: February 07, 2022-October 04, 2022
    This dataset updates: As needed
    These data were produced by the WorldPop Research Group at the University of Southampton. This work was part of the GRID3 project with funding from the Bill and Melinda Gates Foundation and the United Kingdom’s Foreign, Commonwealth & Development Office (INV 009579, formerly OPP 1182425). Project partners included the United Nations Population Fund, Center for International Earth Science Information Network in the Columbia Climate School at Columbia University, and the Flowminder Foundation. Thomas Abbott (WorldPop) led the input processing and the modelling work following the Random Forest (RF)-based dasymetric mapping approach developed by Stevens et al. (2015). Heather Chamberlain, Sarchil Qader, and Attila N Lazar advised on the modelling procedure. The Institut National de la Statistique du Niger (INS) released the census-based total population projection using the results of the 2012 census of population and digital Commune boundaries. Engagement with INS was lead by Mathias Kuepie (UNFPA). The work was verseen by Attila N. Lazar and Andy J Tatem. For further details, please, read NER_population_v1_0_README.pdf
  • 40+ Downloads
    Updated 20 December 2021 | Dataset date: December 20, 2021-October 04, 2022
    This dataset updates: As needed
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Republic of the Congo Settlement Extents, Version 01.01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-gzbm-8y12 . Accessed DAY MONTH YEAR.
  • 40+ Downloads
    Updated 20 December 2021 | Dataset date: December 20, 2021-October 04, 2022
    This dataset updates: As needed
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Comoros Settlement Extents, Version 01.01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-t1yz-k248 . Accessed DAY MONTH YEAR.
  • 50+ Downloads
    Updated 20 December 2021 | Dataset date: December 20, 2021-October 04, 2022
    This dataset updates: As needed
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Djibouti Settlement Extents, Version 01.01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-p4yc-bd97. Accessed DAY MONTH YEAR.
  • 30+ Downloads
    Updated 20 December 2021 | Dataset date: December 20, 2021-October 04, 2022
    This dataset updates: As needed
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Eritrea Settlement Extents, Version 01.01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-9m93-hs25. Accessed DAY MONTH YEAR.
  • 100+ Downloads
    Updated 20 December 2021 | Dataset date: December 20, 2021-October 04, 2022
    This dataset updates: As needed
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Ethiopia Settlement Extents, Version 01.01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-jv2a-7446 . Accessed DAY MONTH YEAR.
  • 30+ Downloads
    Updated 20 December 2021 | Dataset date: December 20, 2021-October 04, 2022
    This dataset updates: As needed
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Gabon Settlement Extents, Version 01.01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-bdtg-c209. Accessed DAY MONTH YEAR.
  • 50+ Downloads
    Updated 20 December 2021 | Dataset date: December 20, 2021-October 04, 2022
    This dataset updates: As needed
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Ghana Settlement Extents, Version 01.01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-a1az-ty56 . Accessed DAY MONTH YEAR.
  • 30+ Downloads
    Updated 20 December 2021 | Dataset date: December 20, 2021-October 04, 2022
    This dataset updates: As needed
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Guinea Settlement Extents, Version 01.01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-q6j4-a365 . Accessed DAY MONTH YEAR.
  • 40+ Downloads
    Updated 20 December 2021 | Dataset date: December 20, 2021-October 04, 2022
    This dataset updates: As needed
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 The Gambia Settlement Extents, Version 01.01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-prqp-pe75 . Accessed DAY MONTH YEAR.
  • 30+ Downloads
    Updated 20 December 2021 | Dataset date: December 20, 2021-October 04, 2022
    This dataset updates: As needed
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Guinea-Bissau Settlement Extents, Version 01.01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-g94m-5w33 . Accessed DAY MONTH YEAR.
  • 40+ Downloads
    Updated 20 December 2021 | Dataset date: December 20, 2021-October 04, 2022
    This dataset updates: As needed
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Equatorial Guinea Settlement Extents, Version 01.01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-xc6y-8j33 . Accessed DAY MONTH YEAR.
  • 70+ Downloads
    Updated 20 December 2021 | Dataset date: December 20, 2021-October 04, 2022
    This dataset updates: As needed
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Kenya Settlement Extents, Version 01.01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-323r-bc15 . Accessed DAY MONTH YEAR.
  • 30+ Downloads
    Updated 20 December 2021 | Dataset date: December 20, 2021-October 04, 2022
    This dataset updates: As needed
    Settlement extents are polygons representing areas where there is likely a human settlement based on the presence of buildings detected in satellite imagery. Settlement extents are not meant to represent the boundaries of an administrative unit or locality. A single settlement extent may be made up of multiple localities, especially in urban areas. Each settlement extent has an associated population estimate. Provided is information on the common operational boundary that the extent fully resides within along with their associated place codes (PCodes). The data are in geodatabase format and consist of a single-feature class. This work has been undertaken as part of the Geo-Referenced Infrastructure and Demographic Data for Development (GRID3) programme. The programme is funded by the Bill & Melinda Gates Foundation and the United Kingdom's Foreign, Commonwealth & Development Office. It is implemented by the Flowminder Foundation, WorldPop at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University. Suggested Data Set Citation: Center for International Earth Science Information Network (CIESIN), Columbia University and Novel-T. 2021. GRID3 Liberia Settlement Extents, Version 01.01. Palisades, NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). https://doi.org/10.7916/d8-jv9t-xv16 . Accessed DAY MONTH YEAR.