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New dataset released for one of the most populous provinces in the Democratic Republic of the Congo

May 7, 2020

GRID3 released a new dataset featuring thousands of new settlement points and place names for the expansive Kongo Central province in the Democratic Republic of the Congo (DRC). This dataset is an extension of the work that University of California, Los Angeles-DRC (UCLA-DRC) started in collaboration with the National Programme against Human African Trypanosomiasis (PNLTHA) in the former Bandundu province.

“The DRC has been facing political instability and crisis since the 1990s. The last census, normally the cornerstone of population data collection, was conducted in 1984. As a consequence, the statistical system is facing many challenges, especially as high resolution data are concerned,” said Mathias Kuepie, one of the GRID3 programme’s experts working in the country. “For example, the most comprehensive dataset in the Kongo Central province had only about 500 villages named and located. In comparison, the settlement layer produced by GRID3 now contains more than 9,000 named locations which is a considerable increase.” 

In addition to the currently 9,077 settlements that have been named, a total of 22,745 settlement extents were identified. Kevin Tschirhart, another GRID3 expert, explains the GRID3 approach:

“To create these comprehensive datasets, we gathered settlement points with names from different sources, such as government entities, private companies or citizen communities, and compared the data from each dataset. We first performed some data-cleaning steps to remove duplicates or inaccuracies, such as white spaces or special characters in the data. We then generated a master list, where we matched data points (names) with settlement locations. We used settlement extents to check that these points were falling on actual settlements. This method allows us to identify data gaps such as missing names or settlements above a certain size threshold. We then worked with UCLA-DRC to collect data on the ground. UCLA-DRC had teams of enumerators in the province for a population survey so we used that opportunity to contract them to collect missing settlement names in the targeted areas and close the main data gaps.”

The GRID3 DRC team collaborated with the Bureau Central du Recensement/Institut National de la Statistique and the Ministry of Health/Division of the National Health Information System to review the quality of the data.

“The dataset offers several opportunities to strengthen evidence-based decision making for health policy and programmes in the DRC,” said Dr. Julie H. Hernandez, research assistant professor in the Department of Health Policy and Management at Tulane University’s School of Public Health and Tropical Medicine, “especially when combined with other existing layers for health and service delivery points, environmental elements, or transportation systems. In particular, it can be used to estimate existing health service coverage and identify underserved settlements and populations. The new GRID3 dataset can make a significant contribution to strengthening access to essential health services and improving infrastructure in Kongo Central.”

The programme used two types of input data to develop the Kongo Central Settlement Point dataset: settlement polygons, representing a settlement’s boundaries, and settlement points. Settlement polygons were produced by Oak Ridge National Laboratory (ORNL) and settlement point data was obtained from various secondary data sources: Bureau Central du Recensement, Cellule d’Analyses es Indicateurs de Développement, OpenStreetMap Foundation, National Health Information System, and United Nations Children’s Fund (UNICEF). The gaps observed in the original data compilation were completed by the UCLA-DRC Research Programme, who led data collection in the province.

The dataset can be downloaded through our website and Columbia University’s Academic Commons. For details about the GRID3 approach to mapping settlements, please watch our webinar.

Featured photo credit: MONUSCO/Myriam Asmani

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