Organisms and non-living elements of the environment such as climate, soil, and water are connected through the movement of nutrients and energy in ecosystems. Ecosystems represent specific areas where organisms and environmental conditions create a network of interactions and are affected by forces such as disturbance (temporary change in environmental conditions that causes a pronounced change) and succession (process of change in the species structure of an ecological community over time). This layer maps the Ecosystems of Africa, based on Africa's climate regions, topography and lithology (bedrock), with a 100m spatial resolution.

This dataset shows Regional locations and general geologic setting of known deposits of major nonfuel mineral commodities in Africa

The Africa Topographic Potisiont layer classifies the African landscape (including Madagascar, Comoros Islands, and other coastal Islands near continenal Africa) into uplands and lowlands/depressions at a 100m resolution. Published by the USGS in 2009, this dataset was created for the Africa Terrestrial Ecosystems mapping project. The classification is derived from the Compound Topographic Index (CTI) , which integrates slope (from SRTM elevation data) and flow accumulation (from HydroSHEDS data) to model potential water flow.

The map is based on Copernicus Global Land Cover data which shows actual land cover (what physically covers land across the globe—forests, grasslands, croplands, lakes, wetlands, built-up area, etc) at 100m x 100m resolution. The land cover data for Africa was overlaid on (high resolution) satellite imagery of Africa, which is then used to determine the land use (by visual interpretation) associated with the various land cover patterns on the Copernicus Global Land Cover map.

Copernicus land cover data offers several advantages: it is of high quality, has a high resolution (100m x 100m), and offers time series satellite imagery. More importantly, the Copernicus Global Land Service is a continuous process and its datasets are updated annually. This means that the Soils4Africa map of agricultural land can be updated every time the land cover data for the new year becomes available (the map is currently based on 2019 data).

The Copernicus dataset already includes the category ‘cropland,’ which by definition is part of agricultural land. The Soils4Africa map broadens the scope of that dataset by infering information on agricultural use and including other kinds of agricultural land use such as grazing pastures and plantations.

When land is mapped as other than ‘cropland'-- like ‘shrubland’ for example-- it is more difficult to interpret and determine whether it is under agricultural use. The Copernicus dataset includes information about ‘fractional cover’-- or the percentage of a particular pixel under a particular kind of land cover (for example, 30% of a 100m x 100m pixel could be forest and 20% could be shrubland). The Soils4Africa map takes into account how fractional cover varies over an area to establish rules for interpreting its land cover data to determine whether it is under agricultural use and for what purpose. These rules were validated by comparing it with ground level information on land use (or land use pattern) for specific areas drawn from the interpretation of satellite imagery from Google Earth.

For example, ground-level observation shows that forest cover upwards of 30% in a given area when matched by shrubland cover of over 30%, is characterized by woody vegetation with a smooth canopy. Therefore, such area is more likely to be under plantations rather than natural forest. Thus, such an area should be counted as agricultural land, even if less than 15% of it is under crops.

Critical natural assets are defined as the natural and semi-natural terrestrial and aquatic ecosystems required to maintain 12 of nature’s ‘local’ contributions to people (local NCP) on land. 12 Local NCP for key benefits like security in food, water, hazards, material and culture. as follows: for food, pollinator habitat sufficiency ofr pollination dependent crop production, fodder production for livestock, wild riverine and marine fish catch ; for water, water quality regulation, via sediment retention and nutrient retention; for natural hazards, flood risk reduction and coastal risk reduction. For materials, timber production, fuelwood production and access to nature. For cultural benefits, coral reef tourism and access to nature for recreation or other uses. Criticality of the natural assets was defined on the basis of the highest value areas across all NCPs, the magnitude of benefits and the number of beneficiaries. Cropland, urban areas, bare areas and permanent snow and ice are excluded from the analysis.

The RESOLVE Ecoregions dataset, updated in 2017, offers a depiction of the 846 terrestrial ecoregions that represent our planet.

This map provides a spatially explicit characterization of 47 terrestrial habitat types, as defined in the International Union for Conservation of Nature (IUCN) habitat classification scheme, which is widely used in ecological analyses, including for quantifying species’ Area of Habitat. The map broadens our understanding of habitats globally, assist in constructing area of habitat refinements, and are relevant for broad-scale ecological studies and future IUCN Red List assessments. Periodic updates are planned as better or more recent data becomes available.

This map provides a spatially explicit characterization of 47 terrestrial habitat types, as defined in the International Union for Conservation of Nature (IUCN) habitat classification scheme, which is widely used in ecological analyses, including for quantifying species’ Area of Habitat. The map broadens our understanding of habitats globally, assist in constructing area of habitat refinements, and are relevant for broad-scale ecological studies and future IUCN Red List assessments. Periodic updates are planned as better or more recent data becomes available.

This dataset provides a continent-wide, raster-based spatial representation of Earth's surface heat flow across the African tectonic plate for the year 2013, modeled under a historical baseline scenario. The data quantifies the amount of thermal energy moving from the Earth's interior to its surface, with values explicitly expressed in watts per square meter (W/m²). This resource is critical for identifying geothermal potential, understanding tectonic anomalies, and supporting broader geoscientific and energy research.

This layer is part of the Geothermal Atlas for Africa developed within the LEAP-RE project

This dataset comprises a collection of shapefiles detailing the geographical locations and attributes of various wells across Africa, with a strong focus on geothermal exploration and assessment. Together, these layers offer a valuable resource for geothermal energy planning, subsurface geological analysis, and infrastructure mapping. The collection includes the following spatial data layers:

• Wells: Maps the locations of various existing well types and provides critical geothermal metrics where available, including well names, temperature correction states, thermal gradients, heat flow, and heat production data.
• BGS Well: A compiled spatial layer derived from scientific literature that categorizes well locations and types.
• Planned wells: Highlights the prospective locations of future geothermal wells across the continent.

These layers are part of the Geothermal Atlas for Africa developed within the LEAP-RE project"

This dataset compiles geophysical models detailing the thickness of the Earth's outer layers, ranging from surface sedimentary basins down to the base of the lithosphere. The collection serves a dual purpose: it provides broad, global baseline data for sediment distribution, while also offering high-resolution, integrated regional models specifically focused on the African plate.

Dataset Contents:

I. Global Baselines

• Global Sediment Thickness (Laske & Masters, 2013): The global sediment thickness baseline extracted from the CRUST1.0 model. This provides broad, foundational coverage across both continental and oceanic domains. (Values expressed in km).
• Global Oceanic Sediment Thickness (Straume et al., 2019): A high-resolution, 5-arc-minute grid detailing total sediment thickness specifically for the world's oceans and marginal seas, compiled from extensive new data and previous work. (Values expressed in m).

II. African Regional Models

• Combined Sediment Thickness (Africa): A synthesized, optimized sedimentary thickness map for Africa and its surrounding regions. This layer intelligently merges the Laske & Masters (2013) and Straume et al. (2019) maps, prioritizing the Straume data wherever overlaps occur to maximize resolution. (Values expressed in m).
• Crustal Thickness (Globig et al., 2016): An Africa-specific crustal thickness map derived from the integrated modeling of elevation, geoid data, and rigorous thermal analysis. (Values expressed in km).
• Lithosphere Thickness (Globig et al., 2016): An Africa-specific lithospheric thickness map, complementing the crustal layer, derived using the same integrated elevation, geoid, and thermal modeling approach. (Values expressed in km).

These layers are part of the Geothermal Atlas for Africa developed within the LEAP-RE project

This dataset shows the location of hydrocarbon provinces with proven petroleum reserves. This data was compiled as part of the USGS's World Energy Project (WEP).

This dataset is part of the LEAP-RE project collection. For more information visit https://www.leap-re.eu/

Development test dataset: random 0-100 values on the 0.35° Nature Africa grid clipped to the DRC. Not real data.