Natural Resources

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) .

Access to piped water reflects the availability of improved water sources directly delivered to households. This layer shows the percentage of people with access to piped water in 2017. Low coverage may signal the need for targeted interventions, potentially supported by decentralized energy systems to power water pumping and distribution.

Water Footprint in Africa, considered as the sum of both the green and blue WF and defined as the ratio between evapotranspiration (in m3 per hectare) and crop yield (in ton per hectare). The values are expressed in m3/ton.

A placeholder layer to get the legend in the GBIF dataset

In 2020, a group of researchers carried out analysis to examine the importance of Indigenous Peoples’ lands for preserving Intact Forest Landscapes.(Fa et al.2020)They used geospatial data on the extent of Indigenous Peoples’ lands reported by Garnett et al. (2018), and Geospatial data for IFLs were sourced from the Intact Forest Landscapes website (www.intactforests.org) for the years 2000, 2013, and 2016 (Potapov et al. 2017)In the paper they have shown that the proportion of Indigenous Peoples’ lands mapped as IFLs was considerably higher (10.9%) than the proportion of other lands (defined here as all land outside Indigenous Peoples’ lands) mapped as IFLs (6.8%). In this map we reported the percentage of Intact Forest Lansdcapes reduction in Indigenous People Lands for the period 2000-2016. IN the table we reported also the percentage of IFLs reduction in other lands. To explore more IFLs conservation strategies for African, Caribbean and Pacific countries you can check BIOPAMA Geonode Layers Sources: Fa JE, Watson JE, Leiper I, Potapov P, Evans TD, Burgess ND, Molnár Z, Fernández‐Llamazares Á, Duncan T, Wang S, Austin BJ. Importance of Indigenous Peoples’ lands for the conservation of Intact Forest Landscapes. Frontiers in Ecology and the Environment. 2020 Apr;18(3):135-4    

''Intact Forest Landscapes (IFLs) are defined as those with an unfragmented area of at least 500 km2 and which are minimally influenced by human economic activity''.(Thies et al. 2011) IFLs are critical for stabilizing terrestrial carbon storage, harboring biodiversity, regulating hydrological regimes, and providing other ecosystem functions. Researchers, firstly, created a global IFL map using existing fine-scale maps anda global coverage of high spatial resolution satellite imagery (Potapov et al. 2008). Moreover they assessed the distribution and dynamics of IFLs within the extent of present-day forest ecosystems tracking loss of intact forest landscapes from 2000 to 2020. In this layer we show the reduction of the IFL extent for African, Caribbean and Pacific (ACP)countries that decreased by 16,6% since the year 2000. Countries that experienced the largest reduction in intact forest landscape area over the past two decades are Solomon Islands with 66,3 %, Central African Republic with 57% and Equatorial Guinea with 50,4%. Democratic Republic of the Congo still  has the highest proportion of intactness of ACP countries with 59,7Mha. IFL in Democratic Republic of the Congo has an extent of 64,3Mha as the 27,7% of its forest cover.  Country IFL Area in 2000 (sqkm) IFL Area in 2020 (sqkm) Percentage of IFL reduction Angola 2913.32 1752.85 39.83 Belize 4275.28 3598.44 15.83 Cote d'Ivoire 4558.78 3760.48 17.51 Cameroon 52752.96 31968.77 39.40 Central African Republic 8695.96 3727.14 57.14 Congo 138699.28 100215.44 27.75 Cuba 544.02 544.02 0.00 Democratic Republic of the Congo 643864.37 597275.75 7.24 Dominican Republic 795.21 564.89 28.96 Equatorial Guinea 4249.57 2104.83 50.47 Ethiopia 3671.63 3233.76 11.93 Gabon 108838.30 76291.78 29.90 Guyana 144296.97 117327.95 18.69 Liberia 4748.74 2880.65 39.34 Madagascar 17240.16 10799.08 37.36 Nigeria 2959.07 2416.10 18.35 Papua New Guinea 159523.52 127121.71 20.31 Samoa 650.86 643.16 1.18 Solomon Islands 7820.33 2630.05 66.37 Suriname 107282.59 92574.26 13.71 Uganda 984.66 962.06 2.30 United Republic of Tanzania 4081.92 3796.32 7.00 Vanuatu 706.13 688.33 2.52  

The Forest Landscape Integrity Index (FLII) is a composite index created to show the degree of forest integrity for 2019. The authors identified three Forest Integrity categories: “high ”“medium”, and “low”. Here it is presented the % of forested area with High Integrity over the total forested area by country. Source:Grantham, H.S., Duncan, A., Evans, T.D. et al. Anthropogenic modification of forests means only 40% of remaining forests have high ecosystem integrity. Nat Commun 11, 5978 (2020). https://doi.org/10.1038/s41467-020-19493-3

An intact forest landscape (IFL) is a seamless mosaic of forest and naturally treeless ecosystems with no remotely detected signs of human activity and a minimum area of 500 km2. (Potapov et al.2017) Intact forests are complex and diverse ecosystems that if lost, are irreplaceable. Research shows that designating intact forest landscapes as protected areas has proven effective at limiting their fragmentation. Since 2000, around 100 conserved and protected areas were created in intact forests areas in ACP countries, increasing the percentage of IFL protected from 11% in 2000 to 26% in 2020. Differences in countries in terms of IFL area reduction: Cuba has not experienced any reduction in IFLs and nowadays its intact forests are fully protected by PAs (544sqkm). At the contrary Angola still not has any kind of protection for its IFLs and experienced a reduction of 39,83% of its IFL (1160 sqkm) in country.The reduction of IFL area in ACP countries was higher outside PAs (19%) than within PAs (5%).Madagascar is the country where the reduction of IFL areas was very high inside protected areas (2420 sqkm). The IFL loss inside PAs has been more than 40% between 2000 and 2020. Central African Republic experienced 23% of reduction inside PAs (938,13 sqkm). This layer shows the percentage of IFLs protected by country Country IFL protected 2020 (sqkm) IFL unprotected 2020 (sqkm) Percentage of IFL protected 2020  Percentage of IFL unprotected 2020 Angola 0.00 1752.85 0.00 100.00 Belize 3310.17 288.36 91.99 8.01 Cameroon 19181.16 12787.52 60.00 40.00 Central African Republic 3070.21 656.90 82.37 17.62 Congo 67218.88 32997.23 67.07 32.93 Cote d'Ivoire 3759.21 1.27 99.97 0.03 Cuba 544.02 0.00 100.00 0.00 Democratic Republic of the Congo 131588.22 465687.18 22.03 77.97 Dominican Republic 553.86 11.03 98.05 1.95 Equatorial Guinea 1549.39 555.44 73.61 26.39 Ethiopia 0 3233.7 0 100 Gabon 22692.90 53598.80 29.74 70.26 Guyana 15545.93 101781.93 13.25 86.75 Liberia 1573.69 1306.95 54.63 45.37 Madagascar 9931.34 867.74 91.96 8.04 Nigeria 2211.75 204.39 91.54 8.46 Papua New Guinea 5863.48 121258.17 4.61 95.39 Samoa 93.13 550.03 14.48 85.52 Solomon Islands 60.11 2569.93 2.29 97.71 Suriname 17304.85 75269.36 18.69 81.31 Uganda 945.21 16.84 98.25 1.75 United Republic of Tanzania 3627.46 168.85 95.55 4.45 Vanuatu 13.24 675.08 1.92 98.08 Analysis performed by Simona Lippi  

The current version of the GDW database (version 1.0) aims to catalogue all types of anthropogenic instream barriers. While initial mapping efforts prioritize major dams that form reservoirs, as well as run-of-river barriers on larger rivers where more information is readily available, the dataset comprises two distinct but interconnected spatial layers: Barrier and Dam Locations (Point Layer): Contains barrier and dam locations, geospatially referenced as point coordinates and co-registered to the global river network of HydroSHEDS. Reservoir Extents (Polygon Layer): Contains associated reservoir polygons, which includes data representing the maximum storage capacity of the reservoirs measured in million cubic meters.

"This map shows, for each grid cell, the Levelized Cost of Heat [c$/kWh] generated by the following systems: Direct Use; High Temperature Heat Pump; The maps refer to: base case scenario; upside scenario, modelling a better fluid flow; up up side, modelling both better fluid flow and higher underground temperatures. These layers are part of the Geothermal Atlas for Africa developed within the LEAP-RE project"

"This map shows, for each grid cell, the Capacity installed [MW] by potential Direct Use Systems and High Temperature Heat Pumps. The maps refer to: base case scenario; upside scenario; up up side scenario. This layer is part of the Geothermal Atlas for Africa developed within the LEAP-RE project"

"This map shows, for each grid cell, the Capacity installed [MW] by potential Cooling Absorption System and Refrigeration Absorption System. The maps refer to: base case scenario; upside scenario; up up side scenario. This layer is part of the Geothermal Atlas for Africa developed within the LEAP-RE project"

"This map shows, for each grid cell, the Capacity installed [MW] by potential Binary ORC and Flash Power Plants. The maps refer to: base case scenario; upside scenario; up up side scenario. This layer is part of the Geothermal Atlas for Africa developed within the LEAP-RE project"

"This map shows, for each grid cell, the Levelized Cost of Electricity [c$/kWh] generated by the following systems: Binary ORC Power Plant; Flash Power Plant; The maps refer to: base case scenario; upside scenario, modelling a better fluid flow; up up side, modelling both better fluid flow and higher underground temperatures. These layers are part of the Geothermal Atlas for Africa developed within the LEAP-RE project"