GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development)

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

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

The GRID3 COD - Health Zones v1.0 dataset consists of health zone boundaries with names, location, and other related attributes in the following provinces of the Democratic Republic of the Congo (COD): Province group 1: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Province group 2: Haut-Lomami and Tanganyika Province group 3: Ituri and Kwilu Province group 4: Maniema The GRID3 COD - Health Zones v1.0 dataset is one of six datasets (Settlements, Health Facilities, Health Area Boundaries, Health Zone Boundaries, Schools and Religious Centers) included in this Version 1.0 release. This operational dataset has not been fully validated by government officials or ministries. The data are available for download in OGC Geopackage format. NOTE: This data release supersedes the following datasets: "GRID3 DRC Health Zone and Health Area Boundaries - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01" and "GRID3 DRC Haut-Lomami and Tanganyika Health Catchment Area Boundaries Version 01" Funding for the development and dissemination of this dataset was provided by GRID3 Inc, the Bill & Melinda Gates Foundation, and Gavi, the Vaccine Alliance.

The GRID3 COD - Health Areas v1.0 dataset consists of health area boundaries with names and health area attributes in the following provinces of the Democratic Republic of the Congo (COD): Province group 1: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Province group 2: Haut-Lomami and Tanganyika Province group 3: Ituri and Kwilu Province group 4: Maniema The GRID3 COD - Health Areas v1.0 dataset is one of six datasets (Settlements, Health Facilities, Health Area Boundaries, Health Zone Boundaries, Schools and Religious Centers) included in this Version 1.0 release. The data are available for download in OGC Geopackage format. NOTE: This data release supersedes the following datasets: "GRID3 DRC Health Zone and Health Area Boundaries - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces Version 01" and "GRID3 DRC Haut-Lomami and Tanganyika Health Catchment Area Boundaries Version 01". Funding for the development and dissemination of this dataset was provided by GRID3 Inc, the Bill & Melinda Gates Foundation, and Gavi, the Vaccine Alliance.

The GRID3 COD - Health Facilities v1.0 dataset consists consists of health facility points with name, location, health zone, and health area, among other attributes, in the following provinces of the Democratic Republic of the Congo (COD): Province group 1: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Province group 2: Haut-Lomami and Tanganyika Province group 3: Ituri and Kwilu Province group 4: Maniema The GRID3 COD - Health Facilities v1.0 dataset is one of six datasets (Settlements, Health Facilities, Health Area Boundaries, Health Zone Boundaries, Schools and Religious Centers) included in this Version 1.0 release. The data are available for download in OGC Geopackage format. NOTE: This data release supersedes the following datasets: "GRID3 DRC Haut-Lomami and Tanganyika Health Facilities, Version 01" and "GRID3 DRC Health Facilities - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces, Version 01". Funding for the development and dissemination of this dataset was provided by GRID3 Inc, the Bill & Melinda Gates Foundation, and Gavi, the Vaccine Alliance.

The GRID3 COD - Settlement Names v1.0 dataset consists of settlement points with names and attributes in the following provinces of the Democratic Republic of the Congo (COD): Province group 1: Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Province group 2: Haut-Lomami and Tanganyika Province group 3: Ituri and Kwilu Province group 4: Maniema The GRID3 COD - Settlement Names v1.0 dataset is one of six datasets (Settlements, Health Facilities, Health Area Boundaries, Health Zone Boundaries, Schools and Religious Centers) included in this Version 1.0 release. The data are available for download in OGC Geopackage format. NOTE: This data release supersedes the following datasets: "GRID3 DRC Settlements - Haut-Katanga, Kasaï, Kasaï-Oriental, Kinshasa, and Lomami Provinces, Version 01" and "GRID3 DRC Haut-Lomami and Tanganyika Settlements, Version 01". Funding for the development and dissemination of this dataset was provided by GRID3 Inc, the Bill & Melinda Gates Foundation, and Gavi, the Vaccine Alliance.

The dataset consists of settlement extents across Ethiopia, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

Designated institutions to provide learning spaces and learning environments for the teaching of students. This data has been extracted from GRID3 Nigeria site

The dataset consists of settlement extents across Mauritius, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The dataset consists of settlement extents across Côte d'Ivoire, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The dataset consists of settlement extents across Republic of the Congo, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The dataset consists of settlement extents across Zimbabwe, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The dataset consists of settlement extents across South Africa, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The dataset consists of settlement extents across Uganda, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The dataset consists of settlement extents across Tanzania, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The dataset consists of settlement extents across Togo, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The dataset consists of settlement extents across Chad, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The dataset consists of settlement extents across Seychelles, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The dataset consists of settlement extents across Eswatini, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The dataset consists of settlement extents across São Tomé and Príncipe, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The dataset consists of settlement extents across South Sudan, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The dataset consists of settlement extents across Somalia, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The dataset consists of settlement extents across Senegal, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The dataset consists of settlement extents across Sudan, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.

The dataset consists of settlement extents across Rwanda, as well as accompanying settlement type based on the degrees of urbanization, place codes, and confidence level for each settlement extent. Updates in this version include: (1) The degree of urbanisation has replaced the previous classifications of built-up areas, small settlement areas, and hamlets (2) Boundary names have been removed, since the OCHA dataset is not an official set of boundaries and may not be accurate (3) Building count ranges have been included (4) Predicted false positives have been included (5) Population data have been removed until new constrained population numbers are available (6) Settlement status has been included, as it pertains to Version 01 of the settlement extents 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 Project at the University of Southampton, the United Nations Population Fund, and the Center for International Earth Science Information Network (CIESIN) at Columbia University.