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This dataset represents a geographic clip to Africa of the World Database on Protected Areas (WDPA), which is the authoritative and most complete global dataset on terrestrial and marine protected areas. The parent database is a joint initiative between the UN Environment Programme (UNEP) and the International Union for Conservation of Nature (IUCN), managed by the UNEP World Conservation Monitoring Centre (UNEP-WCMC). Information is submitted and verified by international secretariats, national and regional governments, NGOs, communities, and landowners. This spatial dataset has been specifically filtered and clipped to include only protected areas located within the terrestrial and marine boundaries of the African continent and its associated island nations. The dataset comprises both spatial data (GIS boundaries) and attribute data (descriptive information) for protected sites across Africa. Key attributes include site name, designation type (national, regional, or international), governance model, IUCN management category, marine/terrestrial status, and legal establishment date. The WDPA is the primary global mechanism used to track progress toward international area-based conservation targets. This African subset is widely used across various sectors for: Conservation & Science: Ecological research, protected area monitoring, and biodiversity assessments specific to African biomes. Corporate & Financial Risk: Environmental impact assessments and supply chain risk analyses for infrastructure and commercial projects operating in Africa. Policy & Reporting: Informing national and international decision-making and tracking regional progress toward the UN Sustainable Development Goals and the Kunming-Montreal Global Biodiversity Framework. The global WDPA dataset is updated and released on a monthly basis through the Protected Planet platform. This clip was extracted on May 2026.

This spatial dataset contains the geographic boundaries and ecological evaluations of 45 Key Landscapes for Conservation and Development (KLCDs) across Sub-Saharan Africa. Building on the Key Landscapes for Conservation (KLCs) identified in the EU report “Larger than elephants”, the NaturAfrica initiative is rolled out across these key biodiversity and development landscapes. NaturAfrica's efforts are concentrated on ‘mega-landscapes’—biogeographical regions identified as crucial for both conservation and development. These regions encompass: The forest ecosystems of the Congo Basin; Landscapes of transhumance pastoralists in North Cameroon, the Central African Republic, and Chad; Guinean forests of West Africa; Savannahs in the Sudano-Sahelian zone of West Africa; Savannahs and watersheds of the East Africa rift; Transfrontier conservation areas of Southern Africa. The layer was developed to support the prioritization of intervention areas for the second phase of this initiative, which combines conservation with sustainable job creation. It provides a spatially explicit characterization of ecological value across these landscapes, evaluated and attributed based on five core ecological and environmental dimensions: Threatened Species Richness: Concentration and diversity of threatened species. Species Endemicity: Presence of endemic species unique to the specific geographic region. Ecosystem Integrity: The integrity of protected and conserved areas, accounting for degrees of human modification and habitat fragmentation. Ecological Connectivity: The degree of connectivity and spatial linkages between protected and conserved areas. Ecosystem Services: Provisioning and regulating services, with a specific focus on carbon storage and water services. Purpose The layer was created to inform the EC Directorate General for International Partnerships (DG INTPA) and policymakers in selecting and prioritizing funding intervention areas based on specific targets (e.g., species conservation, connectivity, or water security) within different biogeographical regions. It serves as a spatial decision-support tool to align with the European Green Deal and the EU Biodiversity Strategy for 2030. Geographic Extent Region: Sub-Saharan Africa Coverage: 45 distinct Key Landscapes for Conservation and Development (KLCDs) Keywords Thematic: Biodiversity Conservation, NaturAfrica, Ecosystem Services, Protected Areas, Habitat Connectivity, Species Endemicity, European Green Deal, Ecosystem Integrity, Transfrontier Conservation, Mega-landscapes. Spatial: Sub-Saharan Africa, Congo Basin, West Africa, East Africa, Southern Africa, Sudano-Sahelian zone. Lineage / Data Source This dataset is derived from the technical assessment conducted for the European Commission Knowledge Centre for Biodiversity (KCBD) .

The dataset is the result of a crop simulation and machine learning exercise to evaluate the irrigation potentials in sub-Saharan Africa. Samples of points (representative for each Agro-ecological zone in Africa) have been selected from a cropland map (from Tubliello et al., 2023) and, by using the DSSAT crop model fed with soil information from the ISRIC project (https://isric.org/projects/soil-information-system-for-africa-soils4africa/) and 10 years of daily climate data (from NASAPOWER), simulations have been conducted in each location under rainfed conditions and optimal irrigation. This last has been achieved y letting the crop model add irrigation water each time a water stress was perceived. Other management practices have been set as realistic as possible, particularly the amount of provided fertilization has been kept low to represent current conditions. Yields have been finally averaged along the different years of simulations to generate expected yields. Finally, by using the XGboost algorithm fed with the same soil and climatic variables used for the crop model, yields under both rainfed and irrigation conditions have been imputed to all remaining cropland locations in Sub-Saharan Africa. What is presented here are the yield increases, as percentages over rainfed yields, obtainable in each location for the four simulated cereals: maize, millet, rice and sorghum.

This layer shows the percentage of children under 6 months who are exclusively breastfed, meaning they receive only breast milk without any additional food or drink. Exclusive breastfeeding is a key determinant of child survival, growth, and development.

This layer provides estimates of the percentage of children aged 2 to 10 years (PfPR2–10) with detectable Plasmodium falciparum parasites in 2022. The estimates are generated using geostatistical models based on point prevalence surveys, routine surveillance data, and a wide range of geospatial covariates representing mosquito habitat and environmental conditions. The data are available annually from 2000 onward, covering all malaria-endemic countries, at a spatial resolution of 5 × 5 km.

This layer represents the estimated travel time (in hours) by foot to the nearest primary school. The accessibility map is generated using a well-established geospatial methodology that integrates road and rail networks, land cover, and topographic features. The resulting gridded "friction surface" represents the time required to traverse each ~1 km × 1 km pixel of Africa.

This layer represents the estimated travel time (in hours) by foot to the nearest healthcare facility. The underlying methodology is described in Weiss et al. (2020), which leverages major data collection efforts from OpenStreetMap, Google Maps, and academic sources to compile the most comprehensive global inventory of healthcare facility locations to date. The approach is based on the creation of friction surfaces that quantify the time required to traverse each ~1 km × 1 km pixel of the Earth's surface.

This layer shows the estimated number of deaths per 1,000 live births among children under 5 years of age (in 2017) — a key indicator of child survival and overall health system performance. High under-5 mortality rates often reflect limited access to essential health services, clean water, sanitation, and adequate nutrition. Expanding decentralized systems can play a key role in improving child survival outcomes in underserved areas.

This layer shows the percentage of children under 5 experiencing severe wasting (in 2019) — the most critical form of acute malnutrition. These children face a significantly higher risk of mortality and require immediate therapeutic support. This indicator helps prioritize emergency nutrition interventions and monitor high-risk areas in need of health and food system strengthening.

This layer shows the percentage of children under 5 years of age (in 2019) who are underweight, based on low weight-for-age. Underweight is a composite indicator capturing both chronic and acute undernutrition. It is useful for identifying vulnerable populations and informing multisectoral strategies to improve child health, food access, and caregiving practices.