Higher energy demands in Africa has led to a wide expansion of the number of hydropower sites, mainly between the 1960s and 1980s. The construction of dams causes impoundments of rivers and reservoirs in the regions of dam influence, with higher evaporation and water temperatures due to increased water surfaces. This map shows the he surface area (sqkm) of African reservoirs subject to hydropower production for the year 2016. It includes reservoirs of associated hydropower plants with installed capacities above 5MW. Apart from this, only reservoirs with a detected dam-caused impoundment of water surface are considered.

The hydropower installed capacity indicates the amount of energy a hydropower plant can produce in its turbines. In 2016, hydropower accounted for 54% of the installed capacity in Eastern Africa, 58% in Central Africa and 30% in Western Africa with fourteen countries having a hydropower share above 50% and eight countries above 70%. These highly hydropower-dependent countries are particularly prone to electricity cuts due to the lack of water caused by severe droughts. This map shows the location and installed capacities of hydropower plants above 5MW installed capacity in Africa for year 2016, representing 95% of the total hydropower installed capacity in Africa.

Priority areas are identified using local coefficients estimated through Geographically Weighted Regression (GWR), which measures the spatially varying relationship between access to piped water and four nutrition indicators among children under five: stunting, wasting, severe wasting, and underweight.

The tool highlights locations where the local association between piped water access and the selected nutrition indicator is both negative and statistically significant. In this application, priority areas are further restricted to locations where piped water access is below 80%, ensuring that the results remain relevant for policy intervention.

The identified areas are classified as having strong, moderate, or mild associations according to the magnitude of the local GWR coefficient. This classification helps users determine the appropriate intensity of intervention. The spatially varying coefficients therefore allow users to identify areas where limited piped water access is most strongly associated with poorer nutritional outcomes among children under five, supporting targeted interventions, programme planning, and place-based development strategies.

Many African countries, especially in the Sub-Saharan region highly depend on hydropower which is one of the energy sources that are most affected by droughts. At the same time hydropower has a huge impact on water consumption (mainly through evaporation from reservoir surfaces) in comparison with other fuel types despite having higher densities of plants and installed capacities. Hydropower accounts for 15% of Africa’s energy production. This map shows the energy production (GWh) of hydropower plants with an installed capacity above 5MW, aggregated for each hydropower-generating country in Africa for year 2016.

African countries have an evident potential for solar energy. Knowing what amount of solar radiation reaches the earth's surface is of particular interest for solar photovoltaic (PV) installations. It can be represented by the average annual potential energy production (or yield): the total amount of electricity (kWh) produced in one year by a 1 kWp PV system at optimal angle, expressed in kWh/kWp.

Increasing water scarcity and water quality issues are serious constraints, especially for Northern Africa. A comprehensive assessment of spatial and temporal precipitation frequency is the initial step for defining public policies relating to water resources management and environmental monitoring. In the agricultural sector, a detailed knowledge of precipitation patterns is necessary to identify the most appropriate crop varieties for the region and to effectively manage climate related uncertainties. Precipitation frequency is also a central source of information for hazard mitigation and management. This layer represents the average variability of precipitation (L-CV) around the annual mean value for the period 1981-2017. The larger the L-CV, the more variable the annual precipitation is from year to year.

Increasing water scarcity and water quality issues are serious constraints, especially for Northern Africa. A comprehensive assessment of spatial and temporal precipitation frequency is the initial step for defining public policies relating to water resources management and environmental monitoring. In the agricultural sector, a detailed knowledge of precipitation patterns is necessary to identify the most appropriate crop varieties for the region and to effectively manage climate related uncertainties. Precipitation frequency is also a central source of information for hazard mitigation and management. This layer shows the average annual precipitation (mm/year) for the period 1981-2017 across the continent.

''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 and
a 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. 

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.

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.

Substantial crop losses occur at various stages along the postharvest value chain. Losses result from poor handling and storage practices combined with limited awareness, infrastructure, and knowledge. The African Postharvest Losses Information System (APHLIS) (www.aphlis.net) is the foremost international effort to collect, analyse and disseminate data on postharvest losses of cereal grains in sub-Saharan Africa. The cumulative % loss in weight incurred during harvesting, drying, threshing/shelling, winnowing, household-level storage, transport and market-level storage for the selected crop, location, and year is presented. Complimentary data sets are collected and used to convert this % loss into absolute loss values in tonnes, US$ and nutrients, along with the nutritional and financial impacts of these losses by province and country. Understanding the magnitude of postharvest loss, the points in the value chain where losses occur, and the causes and impacts of loss helps decision-makers formulate effective policies and invest in successful postharvest loss programmes.

Substantial crop losses occur at various stages along the postharvest value chain. Losses result from poor handling and storage practices combined with limited awareness, infrastructure, and knowledge. The African Postharvest Losses Information System (APHLIS) (www.aphlis.net) is the foremost international effort to collect, analyse and disseminate data on postharvest losses of cereal grains in sub-Saharan Africa. The cumulative % loss in weight incurred during harvesting, drying, threshing/shelling, winnowing, household-level storage, transport and market-level storage for the selected crop, location, and year is presented. Complimentary data sets are collected and used to convert this % loss into absolute loss values in tonnes, US$ and nutrients, along with the nutritional and financial impacts of these losses by province and country. Understanding the magnitude of postharvest loss, the points in the value chain where losses occur, and the causes and impacts of loss helps decision-makers formulate effective policies and invest in successful postharvest loss programmes.

Substantial crop losses occur at various stages along the postharvest value chain. Losses result from poor handling and storage practices combined with limited awareness, infrastructure, and knowledge. The African Postharvest Losses Information System (APHLIS) (www.aphlis.net) is the foremost international effort to collect, analyse and disseminate data on postharvest losses of cereal grains in sub-Saharan Africa. The cumulative % loss in weight incurred during harvesting, drying, threshing/shelling, winnowing, household-level storage, transport and market-level storage for the selected crop, location, and year is presented. Complimentary data sets are collected and used to convert this % loss into absolute loss values in tonnes, US$ and nutrients, along with the nutritional and financial impacts of these losses by province and country. Understanding the magnitude of postharvest loss, the points in the value chain where losses occur, and the causes and impacts of loss helps decision-makers formulate effective policies and invest in successful postharvest loss programmes.

Substantial crop losses occur at various stages along the postharvest value chain. Losses result from poor handling and storage practices combined with limited awareness, infrastructure, and knowledge. The African Postharvest Losses Information System (APHLIS) (www.aphlis.net) is the foremost international effort to collect, analyse and disseminate data on postharvest losses of cereal grains in sub-Saharan Africa. The cumulative % loss in weight incurred during harvesting, drying, threshing/shelling, winnowing, household-level storage, transport and market-level storage for the selected crop, location, and year is presented. Complimentary data sets are collected and used to convert this % loss into absolute loss values in tonnes, US$ and nutrients, along with the nutritional and financial impacts of these losses by province and country. Understanding the magnitude of postharvest loss, the points in the value chain where losses occur, and the causes and impacts of loss helps decision-makers formulate effective policies and invest in successful postharvest loss programmes.

Substantial crop losses occur at various stages along the postharvest value chain. Losses result from poor handling and storage practices combined with limited awareness, infrastructure, and knowledge. The African Postharvest Losses Information System (APHLIS) (www.aphlis.net) is the foremost international effort to collect, analyse and disseminate data on postharvest losses of cereal grains in sub-Saharan Africa. The cumulative % loss in weight incurred during harvesting, drying, threshing/shelling, winnowing, household-level storage, transport and market-level storage for the selected crop, location, and year is presented. Complimentary data sets are collected and used to convert this % loss into absolute loss values in tonnes, US$ and nutrients, along with the nutritional and financial impacts of these losses by province and country. Understanding the magnitude of postharvest loss, the points in the value chain where losses occur, and the causes and impacts of loss helps decision-makers formulate effective policies and invest in successful postharvest loss programmes.

Forests worldwide are in a state of flux, with accelerating losses in some regions and gains in others. Given the recognized importance of forest ecosystem services, quantification of global forest extent and change is needed. This map displays the forest loss during the period 2000–2018, defined as a stand-replacement disturbance, or a change from forest to non-forest state. It is expressed as either 1 (loss - in red) or 0 (no loss).

Forests are the most biologically diverse land ecosystems and are critical for sustaining local and global livelihoods. Deforestation can be considered a type of land degradation when forest ecosystems, with all of their important provisioning, regulating and cultural services, are exchanged for another land use, such as crop agriculture, with a narrow provisioning service focus. Damages to the land resource include the immediate reduction or loss of biomass productivity with a linked loss in habitat, biodiversity, and carbon stock. Clearance of natural forests accelerates soil erosion and the alteration of soil functioning. This layer displays the areas of concern for tree loss issues, derived from the convergence of global evidence of human-environment interactions that can have consequences on land degradation.

Priority areas are identified using local coefficients estimated through Geographically Weighted Regression (GWR), which measures the spatially varying relationship between access to Water infrastructure and education using the indicator of percentage of population with secondary education. The tool highlights locations where the local association between access to piped water s and the selected education indicator is both negative and statistically significant. The identified areas are classified as having strong, moderate, or mild associations according to the magnitude of the local GWR coefficient. This classification helps users determine the appropriate intensity of intervention. The spatially varying coefficients therefore allow users to identify areas where limited sanitation access is most strongly associated with lower education, supporting targeted interventions, programme planning, and place-based development strategies.

Priority areas are identified using local coefficients estimated through Geographically Weighted Regression (GWR), which measures the spatially varying relationship between access to water infrastructure and gender using the indicator of percentage of women with secondary education. The tool highlights locations where the local association between access to piped water and the selected gender indicator is both negative and statistically significant. The identified areas are classified as having strong, moderate, or mild associations according to the magnitude of the local GWR coefficient. This classification helps users determine the appropriate intensity of intervention. The spatially varying coefficients therefore allow users to identify areas where limited water access is most strongly associated with lower women education, supporting targeted interventions, programme planning, and place-based development strategies.

Priority areas are identified using local coefficients estimated through Geographically Weighted Regression (GWR), which measures the spatially varying relationship between access to water infrastructure and health using the indicator of under 5 mortality. The tool highlights locations where the local association between access to piped water and the selected health indicator is both negative and statistically significant. The identified areas are classified as having strong, moderate, or mild associations according to the magnitude of the local GWR coefficient. This classification helps users determine the appropriate intensity of intervention. The spatially varying coefficients therefore allow users to identify areas where limited access to piped water is most strongly associated with higher child mortality, supporting targeted interventions, programme planning, and place-based development strategies.

Surface water affects many aspects of our world: the exchange of heat, gas and water vapour between the planet's surface and atmosphere. Water is the engine behind the distribution, movement and migration of Earth's plant and animal life and is just as essential for humans. It affects our capacity to grow crops and manage animal grazing lands, to run our industrial processes, to manufacture goods, it influences the movement of disease-vectors, toxins and pollutants, it generates energy directly (hydroelectric) and indirectly (thermoelectric), it is an essential part of our transport network, and forms part of our recreational, cultural and sporting world. The Water Occurrence dataset shows where surface water occurred between 1984 and 2018. Open water is any stretch of water open to the sky, and includes both freshwater and saltwater. The map displays water surfaces greater than 30m2 that are visible from space, including natural (rivers, lakes, coastal margins and wetlands) and artificial water bodies (reservoirs formed by dams, flooded areas such as opencast mines and quarries, flood irrigation areas such as paddy fields, and water bodies created by hydro-engineering projects such as waterway and harbour construction). This product captures both the intra and inter-annual variability and changes. The permanent water surfaces (100% occurrence over 36 years) are represented in blue, and areas where water sometimes occurs are shown in shades of pink to purple (0% < occurrence < 100%). The paler shades are areas where the water occurs less frequently. The map can support better informed water-management decision-making.

Water is a critical natural resource for both natural ecosystems and human subsistence. Some of the most immediate pressures on land that lead to degradation include diversion of surface waters and the removal of groundwater reserves to meet agricultural, industrial and domestic demands. This layer displays the areas of concern for water use related issues derived from the convergence of global evidence of human-environment interactions that can have consequences on land degradation. It highlights areas where the total water withdrawal (by the agriculture, industrial and domestic sectors) exceeds 40% of the total available annual renewable water supply.

Vegetation fires have become a major concern in Africa because of their negative impacts on the environment and on human welfare. Uncontrolled (and un-prescribed) wildfires cause forest and vegetation degradation and related biodiversity loss, resulting in immediate and long-term impacts on the livelihoods of local communities and upstream impacts on national and regional economies. Fires in the tropical environment are a major contributor to tropical forest degradation and, if too frequent, can lead to savannisation of these areas. Vegetation fires are also a significant source of trace gases and aerosols in the atmosphere and contribute to the anticipated climate change, particularly with emissions of CO2. This layer shows the deviation of dekadal fire occurrences from the long-term average of the same 10-day period. A positive anomaly means more fire events than average for the last full 10-day period (red). A negative anomaly means less fire events than average for the last full 10-day period (green).

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 provides the P50 projections for a geothermal system utilizing a Chiller unit.

Chiller refers to an absorption chiller or heat pump integrated into the geothermal system. It is used to provide cooling (by utilizing the geothermal heat) or to extract additional heat from the return fluid, thereby increasing the system's overall thermal harvest.

P50 is a statistical term used in risk analysis and forecasting. P50 represents the median scenario, meaning there is a 50% probability that the actual outcome will be higher than this value and a 50% probability it will be lower. It serves as the baseline "best estimate."

• Coefficient of Performance (COP) [-]: A measure of efficiency, defined as the ratio of useful heating or cooling provided to the work (energy) required to operate the Chiller. Higher values indicate greater efficiency.

• Doublet Net Production [MW]: The actual useful power output (Megawatts) generated by the "doublet" (one production well + one injection well), subtracting any energy used by pumps or auxiliary equipment.

• Levelized Cost of Energy (LCOE) [US$ct/kWh]: The average revenue per unit of energy needed to recover the cost of building and operating the plant over its entire life cycle. It essentially represents the break-even price.

• Net Present Value (NPV) [million US$]: The current financial value of all future cash flows the project will generate, minus the initial investment costs. A positive NPV generally indicates a profitable project.

• Optimized Depth of the Aquifer [m]: The calculated ideal drilling depth (meters) to reach the geothermal reservoir that balances drilling costs with temperature/flow benefits.

• Pressure needed to drive pumps [Bar]: The total pressure difference required to drive the thermal loop through the reservoir and wellbore.

• Production Flow Rate [m³/h]: The volume of geothermal fluid extracted from the reservoir per hour (cubic meters per hour).

• Temperature at Reservoir [°C]: The natural temperature (Celsius) of the geothermal fluid within the subsurface rock formation before it is brought to the surface.

• Transmissivity [Dm]: A measure of how easily fluid flows through the porous aquifer. It is the product of hydraulic conductivity and aquifer thickness (often measured in Darcy-meters). High transmissivity means easier extraction.

• Well Distance [m]: The physical distance (meters) between the production well (extraction) and the injection well (return). Proper spacing prevents "short-circuiting," where cool injected water lowers the temperature of the production well too quickly.

This dataset provides the P50 projections for a Direct Heat with Heat Pump geothermal system.

Direct Heat with Heat Pump refers to a scenario where a geothermal system is integrated with an industrial heat pump to upgrade low-grade heat. This allows for production from geothermal temperatures as low as 40°C, which are then heated by the pump to a delivery temperature of 80°C. The reinjection temperature is set to the production temperature minus 20°C, with a absolute minimum of 15°C.

P50 is a statistical term used in risk analysis and forecasting. P50 represents the median scenario, meaning there is a 50% probability that the actual outcome will be higher than this value and a 50% probability it will be lower. It serves as the baseline ""best estimate.""

• Coefficient of Performance (COP) [-]: A measure of efficiency, defined as the ratio of useful heating or cooling provided to the work (energy) required to operate the Chiller. Higher values indicate greater efficiency.

• Doublet Net Production [MW]: The actual useful power output (Megawatts) generated by the ""doublet"" (one production well + one injection well), subtracting any energy used by pumps or auxiliary equipment.

• Levelized Cost of Energy (LCOE) [US$ct/kWh]: The average revenue per unit of energy needed to recover the cost of building and operating the plant over its entire life cycle. It essentially represents the break-even price.

• Net Present Value (NPV) [million US$]: The current financial value of all future cash flows the project will generate, minus the initial investment costs. A positive NPV generally indicates a profitable project.

• Optimized Depth of the Aquifer [m]: The calculated ideal drilling depth (meters) to reach the geothermal reservoir that balances drilling costs with temperature/flow benefits.

• Pressure needed to drive pumps [Bar]: The total pressure difference required to drive the thermal loop through the reservoir and wellbore.

• Production Flow Rate [m³/h]: The volume of geothermal fluid extracted from the reservoir per hour (cubic meters per hour).

• Temperature at Reservoir [°C]: The natural temperature (Celsius) of the geothermal fluid within the subsurface rock formation before it is brought to the surface.

• Transmissivity [Dm]: A measure of how easily fluid flows through the porous aquifer. It is the product of hydraulic conductivity and aquifer thickness (often measured in Darcy-meters). High transmissivity means easier extraction.

• Well Distance [m]: The physical distance (meters) between the production well (extraction) and the injection well (return). Proper spacing prevents ""short-circuiting,"" where cool injected water lowers the temperature of the production well too quickly.

This dataset provides the P50 projections for a Direct Heat geothermal system.

Direct Heat refers to the use of geothermal energy for applications such as space heating, industrial processes, or agriculture. In the utilized model, it is assumed a minimum production temperature of at least 60°C and a reinjection temperature of 40°C.

P50 is a statistical term used in risk analysis and forecasting. P50 represents the median scenario, meaning there is a 50% probability that the actual outcome will be higher than this value and a 50% probability it will be lower. It serves as the baseline "best estimate."

• Coefficient of Performance (COP) [-]: A measure of efficiency, defined as the ratio of useful heating or cooling provided to the work (energy) required to operate the Chiller. Higher values indicate greater efficiency.

• Doublet Net Production [MW]: The actual useful power output (Megawatts) generated by the ""doublet"" (one production well + one injection well), subtracting any energy used by pumps or auxiliary equipment.

• Levelized Cost of Energy (LCOE) [US$ct/kWh]: The average revenue per unit of energy needed to recover the cost of building and operating the plant over its entire life cycle. It essentially represents the break-even price.

• Net Present Value (NPV) [million US$]: The current financial value of all future cash flows the project will generate, minus the initial investment costs. A positive NPV generally indicates a profitable project.

• Optimized Depth of the Aquifer [m]: The calculated ideal drilling depth (meters) to reach the geothermal reservoir that balances drilling costs with temperature/flow benefits.

• Pressure needed to drive pumps [Bar]: The total pressure difference required to drive the thermal loop through the reservoir and wellbore.

• Production Flow Rate [m³/h]: The volume of geothermal fluid extracted from the reservoir per hour (cubic meters per hour).

• Temperature at Reservoir [°C]: The natural temperature (Celsius) of the geothermal fluid within the subsurface rock formation before it is brought to the surface.

• Transmissivity [Dm]: A measure of how easily fluid flows through the porous aquifer. It is the product of hydraulic conductivity and aquifer thickness (often measured in Darcy-meters). High transmissivity means easier extraction.

• Well Distance [m]: The physical distance (meters) between the production well (extraction) and the injection well (return). Proper spacing prevents ""short-circuiting,"" where cool injected water lowers the temperature of the production well too quickly.

This dataset provides the P50 projections for an Organic Rankine Cycle (ORC) geothermal power plant.

Organic Rankine Cycle (ORC) refers to a binary power plant configuration where geothermal fluid (brine) is used to heat a secondary organic working fluid. This process allows for efficient electricity generation from medium-to-low temperature resources (typically 90°C to 150°C). The organic fluid vaporizes, drives a turbine, and is then condensed back into a liquid to repeat the cycle. The geothermal brine is reinjected into the reservoir after passing through the heat exchanger.

P50 is a statistical term used in risk analysis and forecasting. P50 represents the median scenario, meaning there is a 50% probability that the actual outcome will be higher than this value and a 50% probability it will be lower. It serves as the baseline ""best estimate.""

• Coefficient of Performance (COP) [-]: A measure of efficiency, defined as the ratio of useful heating or cooling provided to the work (energy) required to operate the Chiller. Higher values indicate greater efficiency.

• Doublet Net Production [MW]: The actual useful power output (Megawatts) generated by the ""doublet"" (one production well + one injection well), subtracting any energy used by pumps or auxiliary equipment.

• Levelized Cost of Energy (LCOE) [US$ct/kWh]: The average revenue per unit of energy needed to recover the cost of building and operating the plant over its entire life cycle. It essentially represents the break-even price.

• Net Present Value (NPV) [million US$]: The current financial value of all future cash flows the project will generate, minus the initial investment costs. A positive NPV generally indicates a profitable project.

• Optimized Depth of the Aquifer [m]: The calculated ideal drilling depth (meters) to reach the geothermal reservoir that balances drilling costs with temperature/flow benefits.

• Pressure needed to drive pumps [Bar]: The total pressure difference required to drive the thermal loop through the reservoir and wellbore.

• Production Flow Rate [m³/h]: The volume of geothermal fluid extracted from the reservoir per hour (cubic meters per hour).

• Temperature at Reservoir [°C]: The natural temperature (Celsius) of the geothermal fluid within the subsurface rock formation before it is brought to the surface.

• Transmissivity [Dm]: A measure of how easily fluid flows through the porous aquifer. It is the product of hydraulic conductivity and aquifer thickness (often measured in Darcy-meters). High transmissivity means easier extraction.

• Well Distance [m]: The physical distance (meters) between the production well (extraction) and the injection well (return). Proper spacing prevents ""short-circuiting,"" where cool injected water lowers the temperature of the production well too quickly.

Increasing water scarcity and water quality issues are serious constraints in Africa and worldwide. Measuring precipitation anomalies is important for detecting and characterizing meteorological droughts, and, in the agricultural sector especially, for effectively managing climate related uncertainties. This layer shows the deviation of the precipitations of the last full month from the long-term average of the same month. A positive anomaly (shades of blue) means there was more rainfall than average during that month. A negative anomaly (yellow to red) means there was less rainfall than average during that month.