GRID3 (Geo-Referenced Infrastructure and Demographic Data for Development) works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and boundaries. GRID3 combines the expertise of partners in government, United Nations, academia, and the private sector to design adaptable and relevant geospatial solutions based on capacity and development needs of each country.
The programme provides countries with a unique package of tools with which to generate open-source data, support for data applications to ensure effective impact, and training to strengthen the national geospatial foundation for future evidence-based development and humanitarian decision making.
The programme offers a unique and efficient approach, combining the highest-resolution and most recent satellite imagery, dynamic modelling and newest scientific methods, and capacity-strengthening services to ensure sustainable use of geospatial data nationally.
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Updated
September 2, 2020
| Dataset date: Aug 31, 2020
This dataset updates: As needed
The dataset consists of health facility points with name, location, health zone and health area attributes in the provinces of Haut-Lomami and
Tanganyika in the Democratic Republic of the Congo (DRC).
This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative.
GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/
Updated
September 2, 2020
| Dataset date: Aug 31, 2020
This dataset updates: As needed
GRID3 DRC Haut-Lomami and Tanganyika Health Catchment Area Boundaries Version 01 (Beta) dataset consists of two layers: health area boundaries and health zone boundaries.
This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative.
GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/
Updated
September 2, 2020
| Dataset date: Aug 31, 2020
This dataset updates: As needed
The GRID3 DRC Haut-Lomami and Tanganyika Settlements Version 01 (Beta) dataset consists of settlement points with names and health catchment area attributes in the two provinces of Haut-Lomami and Tanganyika, in the Democratic Republic of the Congo (DRC).
This work has been undertaken as part of the Geo-referenced Infrastructure and Demographic Data for Development (GRID3) initiative.
GRID3 works with countries to generate, validate and use geospatial data on population, settlements, infrastructure, and subnational boundaries. For more information, see https://grid3.org/
Updated
August 12, 2020
| Dataset date: Mar 19, 2020
This dataset updates: As needed
The "GRID3 DRC Kongo Central Settlements Points, Version 1" provides a comprehensive dataset of settlements and their names to help target service delivery and development investments. The Kongo Central settlement layers contain settlement points and name attribute data that fall within the Kongo Central boundary and are divided into built up areas, small settlement areas, and hamlets.
Data Set Citation:
Bureau Central du Recensement (BCR), Democratic Republic of the Congo, and Center for International Earth Science Information Network (CIESIN), Columbia University. 2020. GRID3 DRC Kongo Central Settlement Point, Version 1. Palisades NY: Geo-Referenced Infrastructure and Demographic Data for Development (GRID3). DOI: https://doi.org/10.7916/d8-42f6-7v44. Accessed DAY MONTH YEAR
