Datasets

RCoE Action

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Policy

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Title

The CO2 fixed by photosynthesis is one of the most important components of the carbon cycle. Forests play a key role in this process. They represent large and persistent carbon sinks. Tree carbon stocks are important to quantify terrestrial carbon storage and carbon sinks, and to estimate potential emissions from land cover changes (deforestation, reforestation, afforestation) and from biotic (pests, diseases) and abiotic (forest fires, windstorms) disturbances. Spatially explicit data and assessments of forest biomass and carbon are thus paramount to design and implement effective sustainable forest management options and forest related policies. The above-ground carbon index presented in this dataset is expressed in Mg (megagrams or tonnes) of carbon per km2 . It corresponds to the carbon fraction of the oven-dry weight of the woody parts (stem, bark, branches and twigs) of all living trees, excluding stump and roots, as estimated by the GlobBiomass project (globbiomass.org) with 2010 as the reference year.

This layer shows the percentage of people with access to any improved sanitation facility, including both piped systems (such as sewer or septic tanks) and non-piped improved options (like ventilated improved pit latrines or composting toilets), in 2017. Improved sanitation is essential for public health, reducing the spread of waterborne diseases and supporting safe and dignified living conditions. Areas with low access highlight the need for expanded basic services and targeted investments in infrastructure.

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).

The Fire Information for Resource Management System (FIRMS), developed by the National Aeronautics and Space Administration (NASA), utilizes satellite observations to detect active fires and thermal anomalies. This critical information is delivered to decision-makers in near real-time, typically within three hours of the satellite observation.

This dataset consolidates active fire data across multiple rolling timeframes, specifically offering views of the last 24, 48, and 72 hours. Key technical details include:

Spatial Resolution: Each data point represents the center of a high-resolution 375 m pixel where a fire or thermal anomaly was detected.
Update Frequency: The data is refreshed twice daily to ensure the most current ground conditions are represented.

Compared to legacy satellite fire detection products with coarser resolutions (≥ 1km), this 375 m dataset offers significant operational advantages:

Enhanced Detection Capabilities: Delivers improved responsiveness for detecting smaller fires, as well as significantly better detection at night when fire activities frequently occur.
Precise Perimeter Mapping: Provides higher fidelity and accuracy when mapping the perimeters of large fires.
Primary Uses: The data is highly suited for supporting active fire tracking and management (e.g., feeding near real-time alert systems), alongside broader scientific applications that require precise fire mapping fidelity.

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 large-scale expansion of built infrastructure is profoundly reshaping the geographies of Africa, generating lock-in patterns of development for future generations. Understanding the impact of these massive investments can allow development opportunities to be maximised and therefore be critical for attaining the United Nations Sustainable Development Goals and Africa Union Agenda 2063. However, until now information on the types, scope, and timing of investments, how they have evolved, and their spatial-temporal impact was dispersed amongst various agencies. We developed the first comprehensive database of 79 ongoing and planned investment corridors across Africa, synthesizing data from multiple sources covering 184 projects on railways, wet and dry ports, pipelines, airports, techno-cities, and industrial parks. The georeferenced interlinked tabular and spatial database includes 22 attributes with sources provided for each observation. We expect this database will improve coordination, efficiency, monitoring, oversight, strategic planning, transparency, vulnerability risk, and impact assessments, among other uses for inter alia investment banks, governments, impact assessment practitioners, communities, conservationists, economists, and regional economic bodies.

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.

Aridity represents the ‘dryness’ of the climate. Dry areas have a higher potential for land degradation. This layer displays the areas of concern for aridity related issues derived from the convergence of global evidence of human-environment interactions that can lead to land degradation. It highlights dryland areas, where the Aridity Index (ratio of precipitation to evapotranspiration) is inferior to 0.65.

This layer is part of the World Altas of Desertification

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.

Map showing the average continental surface temperature of the year 2022. This map was created by interpolating raw monthly satellite data to fill holes in the grids and subsequently adding and averaging the monthly surface temperatures of the year 2022. The data is clipped to only show the African continental region. The raw data is collected during the daytime by the Moderate Resolution Imaging Spectroradiometer (MODIS), an instrument on NASA's Terra and Aqua satellites. Please note that the type of "surface" MODIS measures varies as a function of location. In some places, the measurement represents the skin temperature of the bare land surface. In other places, the temperature represents the skin temperature of whatever is on the land-including snow and ice, or the leafy canopy of forests and crop fields, or human-made structures such as pavement and building rooftops.
Values are expressed in °C.
This dataset is part of the LEAP-RE project collection. For more information visit https://www.leap-re.eu/

Modern energy services are crucial to human well-being and to a country’s economic development; and yet 1.2 billion people are without access to electricity. It is recognized that the central grid is unlikely to reach many remote areas in the near future: many of these communities will have low electricity consumption, making the costs of extending the grid unaffordable. Given the evident potential of solar energy for African countries, using stand-alone and mini-grid photovoltaic (PV) systems could be an alternative approach to meet the objective of universal electrification.

This dataset presents the ratio between the optimized battery size (kWh) and PV array size (kWp) for PV mini-grids using Li-ion batteries to store electricity (instead of traditional lead-acid batteries). It includes layers modeling two distinct usage behaviors:

Low energy consumption patterns: where the majority of energy is used during the night-time.
High energy consumption patterns: where the majority of energy is used during the day-time.

A higher ratio means that the battery size needed to satisfy the same electricity demand produced by the PV system is larger. Used in combination with other sources, these data can help governments, local authorities, and non-governmental organisations to investigate the suitability of PV mini-grids for the electrification of regions where access to electricity is lacking.

Roots are a long term and stable carbon sink, accounting for about 0.4 of the above ground biomass across biogeographical regions. Well established and developed root systems provide various ecosystem services related to improved soil quality (higher cation exchange capacity and nutrient turnaround) and characteristics (improved soil porosity and aeration). Spatially explicit data and assessments of forest biomass and carbon are paramount to design and implement effective sustainable forest management options and forest related policies. The belowground biomass carbon index (BBCI) presented in this dataset is expressed in Mg (Megagrams or Tonnes) of carbon per km2. It represents an estimation of the carbon stored in the roots of all living trees. Together with the above-ground carbon index (AGCI) and the soil organic content index (SOCI), it provides a complete overview of the total carbon stored in forest areas (trees and soil).

Biodiversity hotspots are the Earth’s most biologically rich—yet heavily threatened—terrestrial regions. These are regions where success in conserving species can have an enormous impact in securing our global biodiversity. To qualify as a biodiversity hotspot, an area must meet two strict criteria: it must contain at least 1,500 species of vascular plants found nowhere else on Earth (known as "endemic" species), and it must have lost at least 70% of its primary native vegetation. 36 regions are identified as hotspots by Conservation International and partners, 9 of which lay (partially or fully) in Africa. This dataset shows their location.

Biomes are distinct biological communities (collection of plants and animals) that have formed in response to a shared physical climate. They are distinguished by characteristic temperatures and amount of precipitation. This map shows the geographic distribution of the eleven major terrestrial biomes found in Africa (out of 14 worldwide). It shows that the same biome can occur in geographically distinct areas with similar climates. Annual precipitations, fluctuations in precipitation and temperature variation (on a daily and seasonal basis) are important abiotic factors influencing the geographic distribution of a biome and the vegetation type in the biome.

Biomes are distinct biological communities (collection of plants and animals) that have formed in response to a shared physical climate. The 11 major terrestrial biomes found in Africa (out of 14 worldwide) are partially covered by Protected Areas. This map shows the percentage of areas protected in each of the terrestrial biomes. For example: in 2020, 12,3% of montane grasslands and shrublands in Africa were covered by Protected Areas.

Some extraordinary changes have occurred across the globe over the past decades regarding human habitation. Globally, between 1975 and 2015 built-up areas increased by approximately 250 %, while population increased by a factor of 1.8. The most considerable changes occurred in Africa where it has nearly quadrupled. The extent of built-up area poses a number of challenges to global sustainable development. As urban clusters expand, productive land and soil is sealed, and natural ecosystems are replaced by land use to support urban centres. This layer highlights the areas of concern for built-up related issues derived from the convergence of global evidence of human-environment interactions that can have land degradation consequences.

This layer is part of the World Altas of Desertification

The Copernicus Global Land Service - Burnt Area products depict burn scars, surfaces which have been sufficiently affected by fire to display significant changes in the vegetation cover (destruction of dry material, reduction or loss of green material) and in the ground surface (temporarily darker because of ash). The monthly products are available at global scale in the spatial resolution of 300 m and cover the period from January 2019 to April 2022. The pixel bears the value of the day of the year in which the burn scars were visible while, if selected for mapping in this platform, the dataset shows the burn scars detected in the selected month.

How do development projects influence the geographic distribution of economic activity within low-income and middle-income countries? Existing research focuses on the effects of Western development projects on inter-personal inequality and inequality across different subnational regions. However, China has become a major financier of economic infrastructure in Africa. This dataset geo-locates Chinese Government-financed projects between 2000 and 2014. It captures 3,485 projects worth $273.6 billion in total official financing. It includes both Chinese aid and non-concessional official financing. Chinese development projects in general, and Chinese transportation projects in particular, appear to reduce economic inequality within and between subnational localities.

Changes in vegetation biomass are critical in assessing land degradation. Climate variations, alone or in combination with human-induced land use and land change, can affect biomass productivity and may trigger changes in vegetation type and structure. Depending on their severity and duration, precipitation anomalies can trigger or aggravate existing land pressures. This layer displays the areas of concern for climate-vegetation trends derived from the convergence of global evidence of human-environment interactions that can have consequences on land degradation. It highlights areas with declining plant productivity in response to climate fluctuations (drought conditions in particular).

This layer is part of the World Altas of Desertification

The Armed Conflict Location & Event Data Project (ACLED) dataset is a disaggregated conflict event dataset designed for real-time monitoring and analysis. It records the specific dates, locations, actors, and types of all reported political violence and protest events to facilitate local and scale-dependant research on war patterns and processes. This layer show the ACLED data relative to the African continent recorded between 2020 and 2025. ACLED updates the dataset every Monday here.

At any given place on Earth, complex human-environment interactions are at play. They include differing rates and magnitudes of drivers (e.g. overgrazing, climate change, agricultural practices) and differing consequences in land degradation (e.g. soil erosion, changes in productivity, loss of biodiversity). The occurrence of multiple global change issues at a location suggests a potential for land degradation, at least in some form. This layer depicts where global change issues relevant to land degradation coincide at a global scale. It helps identifying local or regional areas of concern where land degradation processes may be underway.

This layer is part of the World Altas of Desertification

Whether you’re monitoring crops, modelling green energy installations or soil sealing, combatting loss of natural resources or just helping countries meet their Sustainable Development Goals, chances are high that you’ll need an accurate and spatially detailed map on land cover and land use. Earth Observation satellites, like those from EU’s flagship programme Copernicus, are key to providing such maps, at a global scale, with free and open access. Land cover maps represent spatial information on different types (classes) of physical coverage of the Earth's surface, e.g. forests, grasslands, croplands, lakes, wetlands. Dynamic land cover maps include transitions of land cover classes over time and hence captures land cover changes. This dataset shows the land cover for the baseline year 2019 with a discrete classification in 23 classes aligned with UN-FAO's Land Cover Classification System.

Park managers in many countries across Africa need to monitor and understand their parks features and overall health. They can rely on the highly detailed land cover information offered by the Copernicus Hot Spot Land Cover Change Explorer for specific areas of interest –or hot spots. These areas were selected for their importance in biodiversity preservation (Protected Areas, Key Landscapes for Conservation...). For each land cover class (Natural vegetation, Wetlands, urbane areas, etc.), this layer shows which portions of the areas changed to another class over the period (2000-2019). For a more detailed analysis, compare the layer with the present landcover or refer to the online Explorer. The allows to monitor land cover and land cover change in high detail and make informed decisions based on spatial data.

Copernicus is the European flagship programme for monitoring the Earth. Data is collected by Earth observation satellites and sensors on the earth’s surface. The Copernicus Land Monitoring Service provides geographical information on land use and land cover at European and global scale. Derived from the Copernicus Hot Spot Land Cover Change Explorer, this layer presents detailed land cover information for specific areas of interest –or hot spots– in Africa. These areas were selected as a priority for mapping because of their importance in biodiversity preservation (Protected Areas, Key Landscapes for Conservation...). Park managers in many countries across Africa rely on this Copernicus product to monitor and understand their parks features and overall health. Mapping habitats, assessing pressure on land, identifying prime locations for species reintroduction or new areas to protect are just a few examples of how these data can be exploited.

This dataset is an index that estimates the relative value provided by coral reefs that protect coastlines through reduction of wave height and wave energy. The value as of 2014 is modelled as a function of exposed populations and infrastructure that received some level of protection from coastal and barrier reefs, and is described in relative terms, classified by decile (i.e., grouped into the most valuable ten percent of reefs for protection, the second-most valuable tenth of reefs, etc.). It was calculated at 1 kilometre (km) resolution globally, encompassing all countries and territories containing coral reefs.

Despite a high total population, most parts of the African continent are sparsely populated, with almost 60% living in non-urban areas. Diesel generators have long been the traditional solution to decentralized electrification needs. For off-grid applications, they present lower up-front capital costs per kilowatt installed; however, the dramatic increase of fuel costs in recent years and the cost of transport to remote areas greatly diminish the low capital cost advantage of the diesel option. Even in the cases when the initial investments were subsidized, the high yearly fuel cost are born by the users which often results in early termination of its use. The map shows the spatial variance of the electricity costs per kWh delivered by an off-grid diesel generator.

Modern energy services are crucial to human well-being and to a country’s economic development. Yet 1.2 billion people worldwide live without access to electricity. It is recognized that the central grid is unlikely to reach many remote areas in the near future: many of these communities will have low electricity consumption, making the costs of extending the grid unaffordable. Given the evident potential of solar energy for African countries, using stand-alone and mini-grid photovoltaic (PV) systems could be an alternative approach to meet the objective of universal electrification. This layer compares the costs of electricity produced by solar photovoltaic and diesel systems, the two prevailing off-grid options for rural electrification in Africa. The map shows the difference between solar- and diesel-based electricity production cost (cents USD/kWh) at one square-kilometre resolution. PV minigrid represent the least-cost electrification option in the orange-to-yellow areas, whereas cheaper diesel is depicted in purple. The higher the contrast, the larger the cost difference.

Africa is very rich in biodiversity and is the last place on Earth with a significant assemblage of large mammals. This natural richness, accumulated over millions of years, coupled with the wealth of indigenous and local knowledge on the continent, is central to the pursuit of sustainable development in the region. Yet the decline and loss of biodiversity is reducing nature’s contributions to people in Africa, affecting daily lives and hampering the sustainable social and economic targets set by African countries. This map shows the number of threatened mammal species by country, assessed by the International Union for the Conservation of Nature (IUCN) and documented in the IUCN Red List of Threatened Species. Established in 1964, the IUCN Red List is a critical indicator of the health of the world’s biodiversity that helps inform necessary conservation decisions.

Crop conditions monitoring is highly relevant for food security early warning and response planning in food-insecure areas of the world. GEOGLAM (the Group on Earth Observations' Global Agricultural Monitoring Initiative) aims to reinforce the international community's capacity to produce and disseminate relevant, timely, and accurate forecasts of agricultural production at national, regional, and global scales using Earth Observation data. Copernicus4GEOGLAM, one of the Copernicus Land Monitoring Services managed by the EC Joint Research Centre, aims to produce baseline information that allows countries in Africa to improve their agricultural monitoring systems. Building upon the Joint Research Centre’s frameworks for utilizing Remote Sensing (RS) and Geographic Information System (GIS) resources to evaluate agroecological performance, this spatial dataset provides critical baseline intelligence on cropping systems to support resilience assessment and food security planning for a selected region in Kenya,. The dataset comprises two layers:

Number of Crop Types (Crop Richness): The absolute count of distinct cultivated crop species within a given spatial resolution. Crop richness serves as a fundamental baseline indicator of agricultural variety. It allows analysts to rapidly distinguish between highly vulnerable monoculture landscapes and more traditional, diverse multi-cropping or intercropping systems present in the Kenyan study area.
Crop Diversity (Shannon Diversity Index): Going beyond a simple count, the Shannon Diversity Index evaluates both the abundance (the number of different crop types) and the evenness (the proportional spatial distribution of those crops). A higher index value indicates a highly diverse and balanced cropping ecosystem. Because evenly diverse systems are typically more resilient to climate volatility, pests, and diseases, this layer is a vital proxy for assessing local agroecological health.

Crop conditions monitoring is highly relevant for food security early warning and response planning in food-insecure areas of the world. GEOGLAM (the Group on Earth Observations' Global Agricultural Monitoring Initiative) aims to reinforce the international community's capacity to produce and disseminate relevant, timely, and accurate forecasts of agricultural production at national, regional, and global scales using Earth Observation data.

Copernicus4GEOGLAM, one of the Copernicus Land Monitoring Services managed by the EC Joint Research Centre, aims to produce baseline information that allows countries in Africa to improve their agricultural monitoring systems.

This dataset aggregates crop maps requested by three East African nations, showing the agricultural situation at the end of the long rain season of 2021. The results are made fully and freely accessible, covering the following areas:

Kenya: 98,687 km²
Tanzania: 116,190 km²
Uganda: 89,296 km²

The Dead Wood Carbon and Litter Carbon pools have been estimated at global level as constant fractions of ESA Biomass CCI Above Ground Biomass (AGB), v.3 (2018) using a lookup table based on global ecological zone, elevation and precipitation regime, as proposed by Harris, N.L., Gibbs, D.A., Baccini, A. et al. Global maps of twenty-first century forest carbon fluxes. Nat. Clim. Chang. 11, 234–240 (2021). https://doi.org/10.1038/s41558-020-00976-6

Humans need increasingly more biomass for food, fodder, fibre and energy. Meeting these demands changes global ecosystems. Tracking changes in total biomass production or land productivity is an essential part of monitoring land transformations that are typically associated with land degradation. Land productivity dynamics (LPD) are used as an indicator of change or stability of the land’s capacity to sustain primary production. This layer displays the areas of concern for land productivity related issues, derived from the convergence of global evidence of human-environment interactions that can have consequences on land degradation.

This layer is part of the World Altas of Desertification

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.

Sources and Context

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

Poverty affects billions of people around the globe. On a daily basis, they face low wages and substandard health, education, and living standards. Because of this, poverty must be understood and approached as a multidimensional issue. The Multidimensional Poverty Index (MPI) acknowledges that poverty has many faces. The second dimension in the MIP is the Education dimension. This includes years of schooling and child school attendance. This map shows the percentage contribution of the education dimension to overall poverty. The lower percentages are shown in darker blues while the higher percentages are shown as brighter, lighter blues.

This dataset, part of the Earth Land Information System (ELIS), provides critical measurements of the Effective Leaf Area Index (LAIe) and its anomalies. It is designed to monitor the distribution, seasonal evolution, and rapid changes in vegetation health and ecosystem dynamics across the African continent.

LAIe is a quantitative, non-dimensional measure of the amount of live green leaf material present per unit of ground surface, typically expressed in m2/m2. Unlike "True LAI," which accounts for the total physical leaf area, Effective LAI is derived from canopy gap fraction measurements and assumes a random distribution of foliage. It is a critical parameter for modeling evapotranspiration and carbon fluxes between the biosphere and the atmosphere.

This dataset contains two primary layers, updated every 10 days to capture from January 2003 to February 2023:

Effective LAIe (Absolute): Provides the current distribution and state of foliage density.
Effective LAIe Anomalies: Represents the deviation of current vegetation density against a historical baseline (calculated relative to the average values between 2003 and 2010).

Negative anomalies (reduced foliage density) are primarily driven by climatic factors such as temperature increases and precipitation deficits. Additionally, localized impacts from human activities and animal grazing are captured in these deviations. The combined dataset is widely utilized in agro-meteorology, biogeochemical modeling, and General Circulation Models (GCMs) to parameterize vegetation cover and analyze its complex interactions with the climate and atmosphere.

This layer represents the predicted likelihood that a given settlement is electrified, with values ranging from 0 (no electricity) to 1 (fully electrified). The data are derived from the High Resolution Electricity Access (HREA) dataset, which combines satellite observations of night-time lights with population settlement layers to estimate electricity access. Areas with low predicted electrification can help identify where decentralized renewable energy solutions may be most impactful in closing electricity access gaps.

In Sub-Saharan Africa, medium- and low-voltage data are often non-existent, uncompleted, or unavailable. This is a challenge for practitioners working on the electricity access agenda, power sector resilience or climate change adaptation. This layer presents the spatial extent of the existing and planned electricity grid (high, medium, low voltage level) compiled using multiple sources that enumerate elements of the existing transmission and distribution network.

Displays areas where the geographic range of two or more endemic bird species overlaps. While many bird species are widespread, over 2,500 are endemic and restricted to an area smaller than 5 million hectares (restricted-range species). BirdLife International has mapped every restricted-range species using geo-referenced locality records. Through this process, they identified regions of the world—known as “Endemic Bird Areas” (EBAs)—where the distributions of two or more of these species overlap. Half of all restricted-range species are globally threatened or near-threatened, and the other half remain vulnerable to loss or degradation of habitat. The majority of EBAs are also important for the conservation of restricted-range species from other animal and plant groups. The unique landscapes where these bird species occur, amounting to just 4.5% of the earth's land surface, are high priorities for broad-scale ecosystem conservation. Geographically, EBAs are often islands or mountain ranges, and vary considerably in size, from a few hundred hectares to more than 10,000,000 hectares. EBAs also vary in the number of restricted-range species that they support (from two to 80). EBAs are found around the world, but most (77%) of them are located in the tropics and subtropics.

Estimated number of jobs created directly related to the deployment of PV mini-grids. The indicator was calculated using data on the total MWh of electricity output anticipated if the total number of potential mini-grids were established within each country and the employment factors come from OECD. If the estimated number of jobs created is high, it means that PV mini-grids have a large potential both in terms of deployment and social development.

Reference evapotranspiration (Global - Monthly - ~10 km) August 2025- AQUASTAT (FAO) AgERA5 derived. Reference evapotranspiration per month with a spatial resolution of 0.1 degree. Unit: mm month-1. The dataset contains monthly values for global land areas, excluding Antarctica, since 1979. The dataset has been prepared according to the FAO Penman - Monteith method as described in FAO Irrigation and Drainage Paper 56. https://data.apps.fao.org/catalog/dataset/c91430cc-681e-4ca8-a5f4-8c97dc92c547/resource/ff49908e-2e07-48b3-8deb-0c69af411859

Fire is a natural part of all ecosystems. Wildfires have been burning vegetation and shaping landscapes far longer than people have been on Earth. However, changes in fire frequency and timing can result in degradation if the vegetation is not adapted to the new fire regimes. This can cause long-term damage to land biomass components affecting soil structure, nutrients and water cycling. This layer displays the areas of concern for fires related issues derived from the convergence of global evidence of human-environment interactions that can have consequences on land degradation.

This layer is part of the World Altas of Desertification

This dataset provides fixed broadband performance metrics in zoom level 16 web Mercator tiles (approximately 610.8 meters by 610.8 meters at the equator). Download speed is collected via the Speedtest by Ookla applications for Android and iOS and averaged for each tile. Measurements are filtered to results containing GPS-quality location accuracy. Speedtest data is used today by commercial fixed network operators around the world to inform network buildout, improve global Internet quality, and increase Internet accessibility. This data can be used for rural and urban connectivity development, to help make the internet better, faster, and more accessible for everyone.

River floods are recognized as one of the major causes of economic damages and loss of human lives worldwide. Quantifying flood hazard is an essential component of resilience planning, prevention measures, emergency response, and mitigation, including insurance. This map depicts flood prone areas for flood events with a 100-year return period (i.e. with 1% chance of being exceeded in any one year). Cell values indicate water depth in meters. The map can be used to assess flood exposure and risk for population and assets.

This dataset, part of the Earth Land Information System (ELIS), provides high-resolution, near-real-time measurements of the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) and its historical anomalies. Monitored using space remote sensing techniques, it is essential for observing terrestrial ecosystem dynamics and the impacts of climate change that are otherwise difficult to track from space.

FAPAR is an Essential Climate Variable that serves as an integrated indicator of the status and health of plant canopies. It is used to track the overall primary productivity associated with atmospheric CO2 fixation, playing a critical role in understanding the global carbon cycle and the biosphere's overall productivity.

This dataset is composed of two primary layers:

FAPAR (Absolute): Provides near-real-time measures of the current state, health, and evolution of terrestrial vegetation dynamics.
FAPAR Anomalies: Represents the deviation of current vegetation productivity from the historical average (calculated relative to the 2003–2010 baseline) over 10-day intervals. This layer highlights large surface variations in vegetation conditions across Africa.

Interpreting Anomalies & Applications

Negative Anomalies (Shades of Red): Indicate relative vegetation stress during the 10-day interval (FAPAR value lower than the long-term mean). These are primarily driven by temperature increases and precipitation deficits.
Positive Anomalies (Shades of Green): Indicate relatively favorable vegetation growth conditions during the interval (FAPAR value higher than the long-term mean).
Primary Uses: FAPAR values and their anomalies provide highly actionable information for water management, agricultural planning, and broad environmental monitoring.

Food crisis response planning can save lives if put in place in a timely manner. To do this, decision makers must be warned of climate extreme events impacting agricultural production. The Anomaly hotSpot of Agricultural Production tool (ASAP) is an online decision support system for early warning about hotspots of agricultural production anomaly (crop and rangeland), developed by the JRC for food security crises prevention and response planning anticipation. This map shows the frequency at which countries were classified as hotspots for agricultural production problems between 2004 and 2018. Hotspots are identified on a monthly basis.

Food crisis response planning can save lives if put in place in a timely manner. To do this, decision makers must be warned of climate extreme events impacting agricultural production. The Anomaly hotSpot of Agricultural Production tool (ASAP) is an online decision support system for early warning about hotspots of agricultural production anomaly (crop and rangeland), developed by the JRC for food security crises prevention and response planning anticipation. This map shows the frequency of ASAP anomaly warnings for crop growth for 2004-2018. It highlights the high sensitivity of the main agricultural areas in Northern Africa, the Horn of Africa and the Southern African Development Community to drought conditions.

Food crisis response planning can save lives if put in place in a timely manner. To do this, decision makers must be warned of climate extreme events impacting agricultural production. The Anomaly hotSpot of Agricultural Production tool (ASAP) is an online decision support system for early warning about hotspots of agricultural production anomaly (crop and rangeland), developed by the JRC for food security crises prevention and response planning anticipation. This map shows the frequency of ASAP anomaly warnings for rangeland growth for 2004-2018. It highlights the high sensitivity of the main agricultural areas in Northern Africa, the Horn of Africa and the Southern African Development Community to drought conditions.

"This map shows, for each grid cell, the environmental impact in terms of CO₂-equivalent emissions per kilowatt-hour [g CO2 eq/kWh] generated by by the following systems:

Cooling Absorption System;
Refrigeration Absorption System;
Binary ORC Power Plant;
Flash Power Plant;
Heat for Direct Use;
Heat for 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.

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 Cold [c$/kWh] generated by the following systems:

Cooling Absorption System;
Refrigeration Absorption System;

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 dataset maps regions across Africa with high geothermal energy exploration potential, identifying areas where further research and investment are most likely to yield significant returns. The mapping represents a synthesis of the Indicator Analysis performed by TNO (Hofstra, 2023), specifically selecting the most and least favorable technical outcomes under the assumption of a clay-poor sandstone (CP) compaction model.

To ensure structural robustness and account for geological uncertainty, the indicator results have been projected onto four distinct geological basin models:

BGS TARGET Model: Projecting indicator values onto basin shapefiles defined by the British Geological Survey.
Evenick Model: Utilizing sedimentary basin structures characterized by surface porosity and thickness according to Evenick’s framework.
Getech Model: Integrating regional basin delineations to refine spatial prospectivity based on gravity and crustal structure data.
Robertson CGG Model: Applying indicator analysis to high-resolution basin geometries to evaluate technical performance.

Key Indicators & Methodology

The favorable results displayed in these maps are derived from a multi-criteria evaluation which includes:

Thermal Performance: Integration of the 3D conductive thermal model to identify viable reservoir temperatures at depth.
Reservoir Quality: Assessment of potential hydraulic transmissivity based on depth-dependent porosity and permeability for sedimentary aquifers.
Economic Viability: Calculations involving the Levelized Cost of Energy (LCOE) to distinguish areas where energy extraction is most cost-effective.

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

This dataset maps the critical structural and tectonic features across Africa that serve as key indicators for geothermal resource potential. These layers delineate "fault/fracture zones" which are considered a primary geothermal resource play type for both magmatic and non-magmatic settings.

The layers in the dataset are:

Active faults (BGS) – derived from the Trans-African Regional Geo-data for the Energy Transition (TARGET) model of the British Geological Survey;
Active Faults GEM) – compilled as part of the GEM's global Probablistic Seismic Hazard modeling efforts;
Major faults – derived from the Trans-African Regional Geo-data for the Energy Transition (TARGET) model of the British Geological Survey;
Major faults - East-African Rift System - showing the location of major faults in the East-African Rift System, derived from Chrowicz (2005), part of the East African Rift Temperature and Heat flow model (EARTH).

These fault layers are crucial for characterizing subsurface hydraulic properties. Specifically, the dataset's features are utilized to:

Determine Permeability and Transmissivity: Active fault zones are modeled to have high fault/fracture permeability, accounting for a hydraulic transmissivity of 20 Darcy-meters up to a depth of 3 km.
Define Reservoir Thickness: For performance calculations, the corresponding "aquifer" permeability within these active fault zones is set to 10,000 mDarcy with an assumed thickness of 20 meters.
Model Geothermal Production: These structural features are integrated into the "resource fast model" as thin reservoirs for geothermal doublet systems (systems with at least one production and one injection well) situated in fractured basement or sedimentary rock.
Support Spatial Analysis: The locations of these active faults are rasterized and combined with 3D temperature grids (where magmatic areas and active volcanoes exhibit elevated heat production) to calculate local geothermal energy conversion scenarios across the continent.

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

This layer maps the distribution of diverse geothermal play types categorized by:

Location: Precise spatial boundaries of geothermal provinces.
Geodynamic Setting: Classification by tectonic regime.
Play Type: Categorization based on heat source and fluid transport mechanisms.
Energy Application: Indication of suitability for power production or direct-use applications.

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."

Metrics Definitions

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.

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

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.

Metrics Definitions

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

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.

Metrics Definitions

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

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.

Metrics Definitions

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

Based on the Geothermal Atlas for Africa , the temperature models at 1 km, 2 km, 3 km, and 4 km depth are part of a 3D conductive thermal model of the African lithosphere.

These layers can be described as follows:

Model Basis: The layers are derived from a 3D grid with a vertical resolution of 250 meters down to 15 km, constructed using a lithosphere-scale conductive mode. This model incorporates sediment thickness, heat flow, crustal structure, and the depth of the Lithosphere-Asthenosphere Boundary (LAB).
Calibration: The models are calibrated using a dataset of 923 filtered temperature observations from the British Geological Survey, which were averaged per model grid cell to improve data assimilation.
Environmental Adjustments:
- Surface Reference: The ETOPO surface level is used as the top reference level.
- Magmatic Areas: Magmatic areas have been treated as loci of elevated heat production at a depth range of 3 to 8 km, resulting in temperatures exceeding 200°C at 2 km depth.
Application: These depth-specific temperature grids serve as primary inputs for assessing the technical performance of geothermal production scenarios across Africa, including direct heating, chilling, and power production (ORC).

These layers are 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 layer presents the spatial distribution of the building heights generalized at the resolution of 100m, and referred to the year 2018. It was extracted from the filtering of a composite of global digital elevation models (DEM) and the filtering of satellite imagery using linear regression techniques.

The used input DEMs are the ALOS World 3D - 30m (AW3D30, 2006-2011) and the Shuttle Radar Topography Mission 30m (SRTM30, 2000). The building heights extracted from these sources are updated using the support of the shadow markers extracted from the Sentinel2 image data composite of the year 2018 (GHS-composite-S2 R2020A).

This raster dataset depicts the distribution of the building heights, as Average of the Net Building Height (ANBH), generalized at the resolution of 100m, and referred to the year 2018. The input data used to predict the building heights are the ALOS Global Digital Surface Model "ALOS World 3D - 30m (AW3D30)25, the NASA Shuttle Radar Topographic Mission data - 30m (SRTM30)26 , and the Sentinel-2 global pixel based image composite from L1C data for the period 2017-201827 that is the support of the year 2018 in this release.

This data represents the total BU surface (square meters) between 1975 and 2030 in 5 year intervals over cells of 1x1 km size.

It derives from the GHS-BUILT-S R2023A spatial raster dataset, that depicts the distribution of the built-up (BU) surfaces estimates between 1975 and 2030 in 5 year intervals and two functional use components a) the total BU surface and b) the non-residential (NRES) BU surface.

The dataset is part the Global Human Settlement Layer , Global, high-resolution, multi-temporal gridded data on built-up environment (built-up surface, built-up volume, residential vs. non-residential function), resident population, and settlement classification by the UN-recommended methodology “degree of urbanisation”. The complete information about the GHSL main products can be found in the GHSL Data Package 2023 report

This data represents the total BU surface (square meters) between 1975 and 2030 in 5 year intervals over cells of 100x100 m size.

This data represents the total built-up volume between 1975 and 2030 in 5 year intervals over cells of 1x1 km size.

It derives from the GHS-BUILT-V - R2023A spatial raster dataset, that depicts the distribution of built-up volumes, expressed as number of cubic metres. The data report about the total built-up volume and the built-up volume allocated to dominant non-residential (NRES) uses.

This data represents the distribution of human population between 1975 and 2030 in 5 year intervals over cells of 1x1 km size.

It derives from the GHS-POP - R2023A. Residential population estimates between 1975 and 2020 in 5-year intervals and projections to 2025 and 2030 derived from CIESIN GPWv4.11 were disaggregated from census or administrative units to grid cells, informed by the distribution, volume, and classification of built-up as mapped in the Global Human Settlement Layer (GHSL) global layer per corresponding epoch.

The dataset is part the Global Human Settlement Layer, that provide global, high-resolution, multi-temporal gridded data on built-up environment (built-up surface, built-up volume, residential vs. non-residential function), resident population, and settlement classification by the UN-recommended methodology “degree of urbanisation”. The complete information about the GHSL main products can be found in the GHSL Data Package 2023 report.

This data represents the distribution of human population between 1975 and 2030 in 5 year intervals over cells of 100x100 m size.

These layers present the application of the Degree of Urbanisation stage I methodology recommended by UN Statistical Commission to the global population grid generated by the JRC in the epochs 1975-2030 (5 years timestep).

They derive from the GHS-SMOD - R2023A.

The layers have been generated by integration of built-up surface extracted from Landsat and Sentinel-2 image data processing (GHS-BUILT-S R2023), and population data derived from the CIESIN GPW v4.11 (GHS-POP R2023).

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

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 dataset shows the global distribution of coral reefs in tropical and subtropical regions. It is the most comprehensive global dataset of warm-water coral reefs to date, acting as a foundation baseline map for future, more detailed, work. This dataset was compiled from a number of sources by UNEP World Conservation Monitoring Centre (UNEPWCMC) and the WorldFish Centre, in collaboration with WRI (World Resources Institute) and TNC (The Nature Conservancy). Data sources include the Millennium Coral Reef Mapping Project (IMaRS-USF and IRD 2005, IMaRS-USF 2005) and the World Atlas of Coral Reefs (Spalding et al. 2001).

This dataset provides the global geographic distribution of key livestock species—cattle, sheep, and goats—for the year 2010, sourced from the Gridded Livestock of the World (GLW 3) database. Expressed as the total number of animals per pixel at a spatial resolution of 5 minutes of arc, these layers are essential for diverse applications in agricultural socio-economics, food security, environmental impact assessments, and epidemiology.

This dataset provides a continent-wide, raster-based spatial representation of groundwater resources across Africa for the year 2011, modeled under a historical baseline climate scenario. It is designed to support researchers, policymakers, and practitioners in mapping water availability, understanding baseline hydrogeological conditions, and assessing the intersection of natural water resources with climate and energy planning.

Sources and Context

This layer was extracted from the Africa Groundwater Atlas of the British Geological Survey (BGS) in collaboration with the International Association of Hydrogeologists (IAH). The Atlas provides the expert continent-scale evidence base—including aquifer type, productivity, and groundwater status across 51 African countries—that makes robust spatial modeling of this kind possible.

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

Africa is considered one of the most vulnerable regions to weather and climate variability. Extreme events such as heat waves have important impacts on public health, water supplies, food security, and more generally on both regional economies and natural ecosystems. A prolonged period of hot days can feed wildfires, inhibit crop yields, or produce algae blooms with consequences on lakes oxygenation and, ultimately, fish mortality. Understanding of temperature extreme regime in Africa is necessary to assess the impacts of climate change on human and natural systems and to develop suitable adaptation and mitigation strategies at country level. A way to quantify heath waves is to use the Heat Wave Magnitude Index daily (HWMId). The HWMId is defined as the maximum magnitude of the heat waves in a year. Computed annually, this index takes into account both the duration and the intensity of extreme temperature events, and enables a comparison between heat waves with different timing and location. This dataset presents the number of years in the period 1981-2018 with a HWMId equal or superior to 4. It gives a general idea of the spatial distribution of heat waves with moderate intensity.

The application of fertiliser is a key component in increasing agricultural production. However, there are thresholds beyond which the cost of inputs fails to lead to corresponding increases in yield. Beyond economic inefficiency, overuse of commercial inorganic fertiliser can also result in a decline in soil condition and structure, including reduced soil carbon content, water-holding capacity and porosity, and to environmental pollution. This layer displays the areas of concern for high-input agriculture related issues derived from the convergence of global evidence of human-environment interactions that can have land degradation consequences.

This layer is part of the World Altas of Desertification

Number of deaths attributable to household air pollution resulting from solid fuels for cooking. Evidence from epidemiological studies have shown that exposure to smoke from incomplete combustion of solid fuels is linked with a range of conditions including acute and chronic respiratory diseases. Of these, evidence for three have been assessed on sufficiently strong basis for inclusion in the burden of disease estimates: acute lower respiratory infections in young children (under 5 years); chronic obstructive pulmonary disease in adults (above 25 years); lung cancer in adults (above 25 years).

This dataset provides the hydrological boundaries for major river basins and sub-basins across the African continent. Developed by the FAO Land and Water Division under the AQUASTAT program, the data delineates Africa’s drainage systems based on a hydrologically corrected Digital Elevation Model (DEM) at a 1 km resolution. Designed for use within GIS-based water resource information systems, this dataset serves as a foundational layer for analyzing African hydrology. It was originally published as part of the FAO Land and Water Digital Media Series #13: "Atlas of Water Resources and Irrigation in Africa."

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.

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.

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.

HydroRIVERS represents a vectorized line network of all global rivers that have a catchment area of at least 10 km² or an average river flow of at least 0.1 m³/sec, or both. HydroRIVERS only includes a limited amount of (mostly geometric) attribute information, such as the river reach length, the distance from upstream headwaters and ocean outlet, the river order, and an estimate of long-term average discharge. Every river reach is also co-registered to the sub-basin of the HydroBASINS database in which it resides (via a shared ID). Extracted from HydroSHEDS at 15 arc-second resolution, this layer is part of the HydroATLAS collection..

The IUCN IMMA layer identifies specific habitat areas crucial for one or more marine mammal species, which may be suitable for conservation through delineation and management. IMMAs represent regions that could benefit from targeted protection and/or monitoring. They serve as a marine mammal data layer highlighting important biodiversity, and potentially ecosystem health, which can be prioritized for protection and management by governments, intergovernmental organizations, conservation groups, and the public.

The INFORM Risk Index 2021 is a composite model structured into a hierarchy of dimensions, categories, and components. All scores are normalized on a scale of 0 to 10 (10 being the highest risk).

Below is the clear breakdown of the index's architecture based on your descriptions:

The Composite Index

The top-level score representing a country's overall risk of humanitarian crisis. It is used to assign countries into Risk Classes:

Low: ≤3.5
Medium: 3.5−5.0
High: 5.0−6.5
Very High: ≥6.5

Dimension: Vulnerability

This dimension measures the predisposition of a population to be affected by a hazard based on economic, political, and social characteristics.

Sub-Index: Socio-Economic Vulnerability

An aggregate index covering three main components of systemic instability:

Development Deprivation: Measures poverty using the Human Development Index (HDI) and Multidimensional Poverty Index (MPI).
Inequality: Captures the dispersion of human development, including the Gender Inequality Index and the Gini Coefficient.
Aid Dependency: Measures economic instability through reliance on public aid, development assistance, and remittances.

Sub-Index: Vulnerable Groups

Captures social groups with limited access to care and heightened susceptibility:

Uprooted People: Tracks refugees, IDPs, and returnees.
Children Under 5: Specifically monitors child malnutrition and mortality rates.
Recent Shocks: Factors in populations already affected by natural disasters in the last 3 years.
Food Security: Captures trends in chronic hunger and nutritional balance.
Health Conditions: Monitors the prevalence of pandemics (HIV, TB, Malaria) and neglected tropical diseases.

Dimension: Lack of Coping Capacity

This dimension measures the ability of a country to manage and recover from disasters through its infrastructure and government effort.

Sub-Index: Institutional Capacity

Measures the "soft" infrastructure of a country's disaster management:

Governance: Captures government effectiveness, resilience-building, and political integrity (lack of corruption).
DRR Implementation: Quantifies how well Disaster Risk Reduction activities are actually put into practice.

Sub-Index: Infrastructure

Measures the "hard" assets and systems available during a crisis:

Communication: Evaluates the efficiency of early warning dissemination and the literacy/education of the recipients.
Physical Connectivity: Assesses the accessibility of transport and the quality/availability of water and sanitation services.
Access to Healthcare: Captures health system strength, including physician density and maternal/infant health services.

Irrigation enables farmers to increase crop production by reducing their dependence on natural rainfall. It is considered a vital part of ensuring food security in the future. Yet it also causes extensive environmental damage and undermines human resilience to water scarcity. Irrigation is responsible for 70 % of all freshwater withdrawals in the globe. Human induced salinisation is a widespread problem as around 30 % of irrigated land are affected and becoming commercially unproductive. This layer displays the areas of concern for irrigation related issues, derived from the convergence of global evidence of human-environment interactions that can have land degradation consequences.

This layer is part of the World Altas of Desertification

Key Biodiversity Areas (KBAs) are the most important places in the world for species and their habitats. Faced with a global environmental crisis we need to focus our collective efforts on conserving the places that matter most. The KBA Programme supports the identification, mapping, monitoring and conservation of KBAs to help safeguard the most critical sites for nature on our planet – from rainforests to reefs, mountains to marshes, deserts to grasslands and to the deepest parts of the oceans. By providing the precise location of places that contribute significantly to the global persistence of biodiversity, KBAs can accelerate efforts to reverse the loss of nature, by ensuring conservation efforts are focussed in the places that matter most, and by enabling entities that may have negative impacts on nature to avoid or reduce those impacts in the places they would be most damaging. This layer shows the location of the KBAs, identified and mapped by the KBA partnership.

Some areas in Africa represent spectacular, still viable examples of Africa’s wildlife and wild places. They are of such outstanding importance and value that they should be conserved at all costs and in principle forever. Those areas are referred to as Key Landscapes for Conservation or KLCs. A suitable network of KLCs has the potential to protect the well-known wildlife species within natural ecosystems and to stimulate rural economic growth.

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 <a href="https://africa-knowledge-platform.ec.europa.eu/dataset/key-landscapes-c…; Key Landscapes for Conservation (KLCs) </a> identified in the EU report <a href="https://op.europa.eu/sl/publication-detail/-/publication/d76ac7eb-bc4a-…;“Larger than elephants”</a>, 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:
<ul>
<li>The forest ecosystems of the Congo Basin;</li>
<li>Landscapes of transhumance pastoralists in North Cameroon, the Central African Republic, and Chad;</li>
<li>Guinean forests of West Africa;</li>
<li>Savannahs in the Sudano-Sahelian zone of West Africa;</li>
<li>Savannahs and watersheds of the East Africa rift;</li>
<li>Transfrontier conservation areas of Southern Africa.</li>
</ul>

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:
<ul>
<li>Threatened Species Richness: Concentration and diversity of threatened species.</li>
<li>Species Endemicity: Presence of endemic species unique to the specific geographic region.</li>
<li>Ecosystem Integrity: The integrity of protected and conserved areas, accounting for degrees of human modification and habitat fragmentation.</li>
<li>Ecological Connectivity: The degree of connectivity and spatial linkages between protected and conserved areas.</li>
<li>Ecosystem Services: Provisioning and regulating services, with a specific focus on carbon storage and water services.</li>
</ul>

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
<ul>
<li>Region: Sub-Saharan Africa</li>
<li>Coverage: 45 distinct Key Landscapes for Conservation and Development (KLCDs)</li>
</ul>

Keywords
<ul>
<li>Thematic: Biodiversity Conservation, NaturAfrica, Ecosystem Services, Protected Areas, Habitat Connectivity, Species Endemicity, European Green Deal, Ecosystem Integrity, Transfrontier Conservation, Mega-landscapes.</li>
<li>Spatial: Sub-Saharan Africa, Congo Basin, West Africa, East Africa, Southern Africa, Sudano-Sahelian zone.</li>
</ul>

Lineage / Data Source
This dataset is derived from the <a href="https://publications.jrc.ec.europa.eu/repository/handle/JRC145021"> technical assessment conducted for the European Commission Knowledge Centre for Biodiversity (KCBD) </a>.

Land cover is defined as the physical material at the surface of the earth, usually documented via the interpretation of earth observations. Common land cover types include trees, grass, bare ground, built up areas, water, etc. How well are different ecosystem types (as indicated by land cover) preserved and how strong are anthropogenic changes affecting their distribution in a given area? Human pressures are constantly increasing and it is important to monitor the consequences of the associated changes on the environment. This map shows the changes in land cover between 1995 and 2015.

Humans need increasingly more biomass for food, fodder, fiber and energy. In Africa, circa 22% of the vegetated land surface showed a decline or unstable land productivity between 1999 and 2013. Persistent reduction of land productivity points to long-term alteration of the health and productive capacity of the land, which are characteristic of land degradation. It has impact on ecosystem services and benefits, thus on the sustainable livelihoods of human communities. This map shows the dynamics of (vegetated) land productivity over a time period, in other terms the trajectories of above-ground biomass. It reflects changes in ecosystem functioning e.g. vegetation growth cycles due to natural variation and/or human intervention, and can be associated with processes of land degradation or recovery. The 5 classes depict two levels of persistent productivity decline, one level of instability or stress in capacity, one level of stable productivity and one level of increased productivity.

Habitat fragmentation occurs when natural habitat is broken up by non-natural land uses. For this layer, land fragmentation is expressed as the Natural Land Cover Pattern Index (NLPI), which classifies natural or semi-natural landcover into six spatial pattern classes: core, edge, perforation, islet, margin, and core-opening. Natural landcover pixels from Climate Change Initiative Land Cover (CCI-LC) raster maps are classified as ‘core’ habitat. Non-natural land cover pixels within core habitat are classified as ‘core openings’ as these represent openings from within natural habitat. External interfaces between core and non-natural landcover are classified as ‘edges’ (i.e. exposed to outside-in habitat loss pressures), while internal interfaces between core and core-openings are classified as ‘perforations’ (i.e. exposed to inside-out habitat loss pressure). Collections of isolated natural landcover pixels that are too small to contain core habitat are classified as ‘islets’, while similarly small collections of pixels are classified as ‘margins’ when they are connected to core habitats.

Percentage of women who are literate. This indicator highlights the importance of electricity for women, who spend the majority of their time taking care of the households. Electricity can ease girls and young women from houdeholds duties and allow them to attend schools. Thus, the lower the number of households with access to electricity the greater the potential for decentralised renewable energies to improve literacy levels among women.

Adult literacy rate is the percentage of people ages 15 and above who can both read and write with understanding a short simple statement about their everyday life. Literacy statistics for most countries cover the population ages 15 and older, but some include younger ages or are confined to age ranges that tend to inflate literacy rates. The youth literacy rate for ages 15-24 reflects recent progress in education. It measures the accumulated outcomes of primary education over the previous 10 years or so by indicating the proportion of the population who have passed through the primary education system and acquired basic literacy and numeracy skills.

Poverty affects billions of people around the globe. On a daily basis, they face low wages and substandard health, education, and living standards. Because of this, poverty must be understood and approached as a multidimensional issue. The Multidimensional Poverty Index (MPI) acknowledges that poverty has many faces. The third and last dimension in the MPI is the Living Standard dimension. This includes access to electricity, improved sanitation services and safe drinking water, flooring, cooking fuel, and assets ownership. This map shows the percentage contribution of the Living Standards Dimension to the overall poverty index. The lower percentages are shown in darker greens while the higher percentages are shown as brighter, lighter greens.

Given the massive scale of livestock production systems, it is unlikely that any other single human activity has a larger environmental impact on the terrestrial land mass of the planet. As the world’s largest user of land, livestock production has a huge footprint, affecting many components of the global environment. In many developing countries, the per-capita consumption of livestock foodstuffs is projected to continue to rise. This layer displays the areas of concern for livestock density related issues, derived from the convergence of global evidence of human-environment interactions. The density of livestock is related to environmental pressures from livestock related land use change, grazing lands and fodder production, and greenhouse gas emissions.

This layer is part of the World Altas of Desertification

Smallholder farmers have limited access to capital and are reluctant to trade their low-risk system (low input and low yield) to a high-risk system (high input and potentially higher yields). But Insufficient application of fertilizer on agricultural land may lead to soil nutrients depletion, lower yields, and eventually land abandonment. This layer displays the areas of concern for low-input agriculture related issues derived from the convergence of global evidence of human-environment interactions that can have land degradation consequences.

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.

Mangroves are trees or shrubs adapted to saline and brackish environments. They are found in the intertidal zone of tropical and sub-tropical coastlines. Mangrove forests are among the most productive ecosystems on earth. They serve many important functions, including water filtration, prevention of coastal erosion, carbon storage, food, timber and livelihood provision, and biodiversity protection (as they provide habitat, nurseries, and feeding grounds for a vast array of organisms). Despite their incredible value, mangrove forests are destroyed and degraded at a rate of about 1% per year as a result of land use change, exploitation, coastal development and climate change. This layer shows the change in mangrove extent -either stable, gain or loss- between 1996 and 2016.

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) in the ocean (blue). 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.

This dataset provides mobile (cellular) network performance metrics in zoom level 16 web Mercator tiles (approximately 610.8 meters by 610.8 meters at the equator). Download speed is collected via the Speedtest by Ookla applications for Android and iOS and averaged for each tile. Measurements are filtered to results containing GPS-quality location accuracy. Speedtest data is used today by commercial mobile network operators around the world to inform network buildout, improve global Internet quality, and increase Internet accessibility. This data can be used for rural and urban connectivity development, to help make the internet better, faster, and more accessible for everyone.

Chlorophyll-a concentrations (Chla) are an indicator of phytoplankton abundance and biomass in open waters. They can be an effective measure of trophic status and are commonly used to measure water quality. This layer compares the Chla value from the last full month with the long-term mean Chla. A positive anomaly (warm colours) means the monthly Chla is higher than the long-term average for that month; a negative anomaly (cool colours) means it is lower than the average.

This dataset compiles global and regional models of the Mohorovičić discontinuity (Moho) depth from 2019 to 2022, providing key insights into crustal thickness and lithospheric boundaries. All layer values are expressed in kilometers (km). It includes the Moho Depth (Finger et al., 2022) map, which details the boundary derived from S-wave seismic tomography data, alongside its corresponding Moho Depth Uncertainty layer to highlight spatial confidence and data reliability. Additionally, it features the Global Moho Depth (Szwillus et al., 2019) map, derived using a nonstationary kriging algorithm (Risser & Calder, 2017), which serves as an excellent comparative baseline for structural, geophysical, and tectonic analysis.

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

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.

The United Nations Educational, Scientific and Cultural Organization (UNESCO) seeks to encourage the identification, protection and preservation of natural heritage around the world considered to be of outstanding value to humanity. This is embodied in an international treaty called the Convention concerning the Protection of the World Cultural and Natural Heritage, adopted by UNESCO in 1972. What makes the concept of World Heritage exceptional is its universal application. World Heritage sites belong to all the peoples of the world, irrespective of the territory on which they are located.

Net official development assistance (ODA) is government aid designed to promote the economic development and welfare of developing countries. Aid may be provided bilaterally, from donor to recipient, or channelled through a multilateral development agency such as the United Nations or the World Bank. Net official aid (OA) refers to aid flows from official donors to more advanced (developing) countries and territories. Official aid is provided under terms and conditions similar to those for ODA. This map shows the aggregated figure (sum of ODA and OA) for African countries. Data are in current U.S. dollars.

Oil seed crops, especially oil palm, are among the most rapidly expanding agricultural land uses, and their expansion is known to cause significant environmental damage. Accordingly, these crops often feature in public and policy debates, which are hampered or biased by a lack of accurate information on environmental impacts. This dataset presents a global crop map. It covers areas where oil palm plantations were detected at global scale, and includes industrial and smallholder mature oil palm plantations.

The human imprint on the planet has a major impact on the functioning of the Earth system. Because the impact on the environment is closely intertwined with population dynamics, it is important to monitor and include these in the evaluation of land degradation. This layer displays the areas of concern for population change related issues derived from the convergence of global evidence of human-environment interactions that can lead to land degradation. It reflects the dynamics of increasing number of people in a certain area.

This layer is part of the World Altas of Desertification

According to UN estimates, the global population will increase by 2.4 billion between 2015 and 2050. Of this, an overwhelming 50 % will be concentrated in Africa (1.3 billion). There could be up to four times as many people in sub-Saharan Africa by the end of the century. The human imprint on the planet has a major impact on the functioning of the Earth system. Because the impact on the environment is closely intertwined with population dynamics, it is important to monitor and include these in the evaluation of land degradation. This layer displays the areas of concern for population density related issues derived from the convergence of global evidence of human-environment interactions that can lead to land degradation.

This layer is part of the World Altas of Desertification

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.

This dataset provides projections of global rainfall erosivity changes, a critical metric representing the erosive force of rainfall that drives worldwide soil and nutrient loss. These maps serve as essential inputs for global and regional soil erosion assessment models. The collection details the geographical distribution of projected erosivity changes across two primary periods: 2010–2050 and 2050–2070. To account for different climate trajectories, the dataset includes models for three distinct Representative Concentration Pathway (RCP) scenarios for both timeframes: RCP 2.6 (stringent mitigation), RCP 4.5 (intermediate emissions), and RCP 8.5 (high emissions). By combining these temporal and climatic variables, users can evaluate and compare potential future soil erosion risks under varying degrees of global climate change.

Raw materials are essential for the sustainable functioning of modern societies and their industries. The European Commission's Raw Materials Information System (RMIS) is developed by the Joint Research Centre (JRC) in cooperation with the DG for Internal Market, Industry, Entrepreneurship and SMEs (GROWTH). The RMIS is the Commission’s reference web-based knowledge platform on non-fuel, non-agricultural raw materials from primary and secondary sources. From gold to natural rubber, including cobalt, cooking coal, construction aggregates (sand, gravel...) and many more, it focuses on both abiotic and biotic materials, covering the entire value chain. This map shows the amount (in USD) of the main non-food, non-energy raw material commodities exported by each African country in 2017.

All known formal and informal settlements of forcibly displaced and stateless people in Africa from UNHCR’s GIS database as of November 2025. Population in the settlement. It may include several categories: Refugees, Returnees, IDP, Asylum-seeker, Stateless and Mixed.Formal Settlement: Formal settlements are places where official land is allocated for a group of asylum seekers, refugees, or IDPs. They are accommodated in purpose-built settlements with access to facilities and services. An official management entity is assigned. Camps are a type of formal settlement. Informal Settlement: In an informal settlement, a group of asylum-seekers, refugees, or IDPs choose to settle in self-identified spontaneous sites. Self-settled settlements are often located on state-owned, private, or communal land, with or without negotiations with the local population or private landowners.

The dataset depicts the total energy demand per settlement (kWh/day) at year 5 under scenario with household consumption raised to 1000 Wh/day (at year 0). This dataset is part of the e Refugee Settlements Electricity Access (RSEA) database, designed and developed to gather the multidimensional factors that can determine a refugee settlement's energy dimension. These factors were chiefly environmental (such as variability of solar radiation and avoided GHG emissions), technical (electrification status, distance to grid), social (population, electricity demand, social infrastructure), and economic (e.g., PV mini-grid component prices) considerations that can influence a stakeholder decision on the deployment of a PV and battery storage mini-grid in a displacement setting.

The Regional Economic Communities (RECs) are regional groupings of African states. The 1980 Lagos Plan of Action for the Development of Africa and the 1991 Abuja Treaty proposed the creation of RECs as the basis for wider African integration. Each with their own role and structure, the RECs aim to facilitate regional economic integration between members of the region and through the wider African Economic Community (AEC), established under the Abuja Treaty. They are increasingly involved in coordinating African Union Member States’ interests in wider areas such as peace and security, development and governance. This map shows how many and which RECs each African country belongs to. The African Union recognises eight RECs: the Arab Maghreb Union (UMA), the Common Market for Eastern and Southern Africa (COMESA), the Community of Sahel–Saharan States (CEN–SAD), the East African Community (EAC), the Economic Community of Central African States (ECCAS), the Economic Community of West African States (ECOWAS), the Intergovernmental Authority on Development (IGAD), and the Southern African Development Community (SADC).

Tensions over freshwater use and management in international river basins are one of the main concerns in political relations. They may exacerbate existing tensions, increase regional instability and social unrest. Hydro-political interactions are here defined as episodes of cooperation or conflict between countries over transboundary water resources. The probability index presented in this map is based on past hydro-political issues in international river basins and a selection of biophysical and socioeconomic indicators (for the period 1997-2012). Areas are more (red) or less (blue) likely to experience transboundary water-related issues. A higher likelihood identifies areas where hydro-political interactions are more probable, due to lack of water supply and/or human pressure in a more vulnerable institutional and socioeconomic context. This data driven index can help policy makers identify areas where cooperation over water should be actively pursued to avoid possible tensions, especially under changing environmental conditions.

The Rule of Law Index, generated by the World Justice Project, illustrates the perceived adherence to the Rule of Law per country. Rule of law is defined here as a durable system of laws, institutions, norms, and community commitment that delivers accountability, just laws, open government, and accessible justice. These principles are measured across eight factors:

Constraints on Government Powers
Absence of Corruption
Open Government
Fundamental Rights
Order and Security
Regulatory Enforcement
Civil Justice
Criminal Justice

The Rule of Law Index aggregate the scores across factors. A high ranking (a low numerical rank) means that perceived adherence to the Rule of Law is higher. 0=weakest, 1=strongest.

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

The Sahel is a region that has historically had multiple definitions—climatic-botanical and political—with limits traced in vastly different ways. By rethinking the foundations of cartography and the tools typically "taken for granted" (such as static isohyets or rigid political boundaries), this dataset renders the definition of the Sahel visible and fluid. The research converges fieldwork expertise with the processing of satellite and geo-referenced data to represent the following layers:

Sahel Breadth: This layer represents the minimum and maximum extension of the Sahel area over the last 30 years. While the region is technically defined as the sub-Saharan area between the isohyetal lines of 150mm and 850mm of annual rainfall, these limits shift depending on the period, season, and drought conditions. This data captures that "breath"—the movement of the climatic strip over three decades.
Sahel Boundaries: This layer addresses the contested nature of the region's delimitation. It challenges traditional cartographic representation and political jurisdictions, providing a spatial analysis of the shifting botanical and climatic limits that define the transition from the desert to the Sudanese regions.

These layers are part of the Atlas of the Sahel, a project that proposes a cartography capable of mapping the incessant movement of conditions, limits, and possibilities characterizing the strip between the Sahara and the humid Sudanese regions.

This dataset comprises three distinct layers delineating the boundaries of sedimentary basins across Africa. In particular

Basins (greater than 2km): Boundaries of sedimentary basins in Africa with sedimentary thicknesses of at least 2 km. Contains geological information about the sedimentary basins such as basin name, class/type and age. Created by extracting data from open sources into a series of shapefiles and rasters containing information on culture, geology, geothermal and geophysical data.
Basins Nyberg & Howell (2015): Boundaries active sedimentary basin/depositional centers of Africa categorised by basin structure and climate-zone.
Basins Robertson (2019): Boundaries of sedimentary basins in Africa. Part of the Robertson new ventures product suite. Includes information on the name, geometry, type and the hydrocarbon exploration status of a given basin.
Basins Evenick (2021): Boundaries of sedimentary basins in Africa compiled from previous work. The sedimentary basins have been revised to simplify the borders of sedimentary basins, as the definition of a basin (boundary) is often contested. Includes the name, geometry, type, age and evaporite content of a given basin.

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

In most people's mind, soil would not figure highly in a list of the natural resources of Africa. However, healthy and fertile soils are the cornerstones of food security, key environmental services, social cohesion and the economies of most African countries. Unfortunately, soil in Africa tends to reach public awareness only when it fails – often with catastrophic consequences as seen by the famine episodes of the Sahel in the 1980s and more recently in Niger and the Horn of Africa. In the context of major global environmental challenges such as food security, climate change, fresh water scarcity and biodiversity loss, the protection and the sustainable management of soil resources in Africa are of paramount importance. This layer presents the diversity of soil types across Africa. This map was produced by the Joint Research Centre of the European Commission for the Soil Atlas of Africa.

Agricultural drought events can affect large regions across the world. Soil moisture (or soil water content) is an important variable for plant growth, and - together with precipitation and evapotranspiration - is a basic component of the hydrological cycle. The Soil Moisture Anomaly (SMA) indicator is used to detect and monitor agricultural drought, that is when there is reduced crop production due to insufficient soil moisture. It is computed as a deviation from the climatological reference period, and is updated 3 times a month (after the 10th, the 20th and the last day of the month). This layer displays the map for the last full decade of the current month. Negative anomalies (shades of brown) represent dry conditions.

Soil organic carbon (SOC) is the carbon that remains in the soil after partial decomposition of any material produced by living organisms. It constitutes a key element of the global carbon cycle through atmosphere, vegetation, soil, rivers and the ocean. It is a crucial contributor to food production, mitigation and adaption to climate change. Soils represent the largest terrestrial organic carbon reservoir. Depending on local geology, climatic conditions and land use and management (amongst other environmental factors), soils hold different amounts of SOC. This map shows the amount of carbon stored in the soil (from 0 to 30 cm depth), expressed in Mg (megagrams or tonnes) per km2.

African countries have an evident potential for solar energy. Knowing the amount of solar radiation reaching the earth's surface is of particular interest for photovoltaic installations. It can be represented by the Global Horizontal Irradiation: the total amount of energy received from the Sun by a surface horizontal to the ground during a period of time, expressed in Wh/m2. This map shows the yearly average (2005-2015) global horizontal irradiation (kWh/m2).

The availability and quantity of observational species occurrence records have greatly increased due to technological advancements and the rise of online portals, such as the Global Biodiversity Information Facility (GBIF), coalescing occurrence records from multiple datasets. Funded by the world's governments, this international network and data infrastructure is aimed at providing anyone, anywhere, open access to data about all types of life on Earth. This map displays all the observations reported to the GBIF from 1600 to present. This knowledge derives from many sources, including everything from museum specimens collected in the 18th and 19th century to geotagged smartphone photos shared by amateur naturalists in recent days and weeks. Individual records are available at https://www.gbif.org

Droughts affect millions of people in the world each year and have long-lasting socioeconomic impacts. They can occur over most parts of the world, even in wet and humid regions, and can profoundly impact agriculture, basic household welfare, tourism, ecosystems and the services they provide. The Standardized Precipitation Index (SPI) is the most commonly used indicator worldwide for detecting and characterizing meteorological droughts, which are prolonged periods of less than average rainfall in a given region. It measures precipitation anomalies at a given location, based on a comparison of observed total precipitation amounts for an accumulation period of interest (in this case, 3 months), with the long-term rainfall record for that period. SPI values below ‒1.0 indicate rainfall deficits (drier than normal – yellow to red), while SPI values above 1.0 indicate excess rainfall (wetter than normal – purple to blue). The lower the SPI, the more intense is the drought. The layer show the SPI-3 from the month second to last and is updated monthly.

This layer shows the percentage of stunting among children under 5 years of age, a form of chronic undernutrition reflected in low height-for-age. Stunting can result from prolonged food insecurity, poor maternal health, or inadequate early childhood care. Areas with high stunting rates indicate long-term development challenges and can help guide interventions aimed at improving nutrition, health services, and water and sanitation infrastructure.

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.

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 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.

The Africa Topographic Moisture Potential layer classifies the landscape of Africa as either upland or lowland (and other depressions) area. It was produced as part of the USGS’s Africa Ecosystems Mapping project to create maps depicting standardized, terrestrial ecosystem models. Substrate moisture regimes strongly influence the differentiation and distribution of terrestrial ecosystems, and therefore topographic moisture potential is one of the key input layers in this biophysical stratification.

Carbon storage in biomass (biological material) is a key link in the global carbon cycle, and consequently for climate change mitigation. Forests in particular are an important carbon sink that help reduce the greenhouse effect. Together, the above-ground carbon (carbon fraction contained in the stems, barks, branches and twigs of living trees), the belowground biomass carbon (carbon fraction contained in roots of living trees) and the soil organic carbon (amount of carbon stored in the soil) provide a complete overview of the total carbon stored in forest areas (trees and soil). This map shows the total carbon stored expressed in units of dry mass (Mg) per ground area unit (km2).

The world is shrinking. Cheap flights, large scale commercial shipping and expanding road networks all mean that we are better connected to everywhere else than ever before. Accessibility - whether it is to markets, schools, hospitals or water - is a precondition for the satisfaction of almost any economic need. The new map of Travel Time to Major Cities -developed by the European Commission and the World Bank- captures this connectivity and the concentration of economic activity. It also highlights that there is little wilderness left. The map shows the travel time (in hours/days) to major cities (i.e. cities of 50,000 or more people in year 2000) using land (road/off road) or water (navigable river, lake and ocean) based travel.

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.

This layer is part of the World Altas of Desertification

Tropical moist forests have a huge environmental value. They play an important role in biodiversity conservation, the terrestrial carbon cycle, hydrological regimes, indigenous population subsistence, and human health (1-5), and are increasingly recognized as an essential element of any strategy to mitigate climate change. Deforestation, degradation, and fragmentation compromise the functioning of tropical forests as an ecosystem, leading to biodiversity loss, reduced carbon storage capacity, and an increased risk of viral disease outbreaks. Accurate characterization of changes in tropical moist forests is therefore needed to support conservation policies and to better quantify their contribution to global carbon fluxes.

This dataset comprises the following map layers:

Undisturbed tropical moist forest: Shows the coverage of undisturbed tropical moist forests remaining at the end of the year 2019.
Deforestation year map: Shows where deforestation occurred over three decades (between 1982 and 2020) and indicates the year when the forest cover was deforested for the first time (followed or not by regrowth).
Degradation year map: Shows where degradation occurred over three decades (between 1982 and 2020) and indicates the year when the forest was degraded for the first time (and remained degraded up to 2020).
Transition map: Captures the dynamics of changes in tropical moist forests between the initial observation period (1990) and the end of the year 2020.

Source: European Commission Joint Research Centre (JRC) - Tropical Moist Forests (TMF)

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.

Prevalence of underweight (weight-for-age <-2 standard deviation from the median of the World Health Organization (WHO) Child Growth Standards) among children under 5 years of age. Survey estimates are based on standardized methodology using the WHO Child Growth Standards. Global and regional estimates are based on methodology outlined in UNICEF-WHO-The World Bank: Joint child malnutrition estimates - Levels and trends (UNICEF/WHO/WB 2012).

Africa is projected to have the fastest urban growth rate in the world — by 2050, Africa’s cities will be home to an additional 950 million people. Urban planning and management are essential development challenges. Understanding urbanisation, its drivers, dynamics and impacts, is key to designing targeted, inclusive and foward-looking policies at the local, national and continental levels. Africapolis data and evidence supports cities and governments to make urban areas more inclusive, productive and sustainable. This map of urban population covers 7 500 agglomerations in 50 countries for the base year 2015.

Shapefile showing the location, status, hight and type of volcanoes in Africa that are thought to have been active in the past 10000 years (Holocene). From the Smithsonian Institution, Global Volcanism Program, American Geological Institute, Geological Survey (U.S.) and Environmental Systems Research Institute (Redlands, Calif.)

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

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.

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.

This layer is part of the World Altas of Desertification

Water is essential for life on Earth and a critical natural resource that underpins all social and economic activity. Ensuring water and sanitation for all is one of the Sustainable Development Goals (SDG 6) of the 2030 Agenda. Target 6.6 specifically aims to protect and restore water-related ecosystems, including wetlands. This map shows the total area covered by inland vegetated wetlands. It includes swamps, marshes, peatlands, bogs and fens, the vegetated parts of floodplains as well as rice paddies and flood recession agriculture.

The Global Wind Atlas is a free, web-based application developed to help policymakers, planners, and investors identify high-wind areas for wind power generation. It also serves as a useful tool for governments to get a better understanding of their wind resource potential at provincial and local levels. Wind power density is a measure of the wind resources. This map shows the mean wind power density (W/m2) at 10 m heigth. Higher mean wind power densities indicate a better wind resource potential.

The working poor are employed people who live in households that fall below an accepted poverty line. While poverty in the developed world is often associated with unemployment, the extreme poverty that exists throughout much of the developing world is largely a problem of employed persons. For these poor workers, the problem is typically one of employment quality. Reducing poverty in line with the SDGs therefore necessitates boosting the employment opportunities and incomes of the working poor – those people who are employed, but who are nevertheless unable to lift themselves and their families above the poverty threshold. This map shows for each country the proportion of employed people who live on less than $3.10 a day (in Purchasing Power Parity (PPP) terms), expressed as a percentage of the total employed population aged 15 and older.

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.

Magnetic anomaly map of Africa, derived from the World Digital Magnetic Anomaly map (WDMAM). Note that the blurry areas are interpolated due to source not containing data points.
Values are expressed in nT.
The WDMAM is an international scientific project under the auspices of IAGA (International Association of Geomagnetism and Aeronomy) and CGMW (Commission for the Geological Map of the World), aiming to compile and make available magnetic anomalies caused by the Earth lithosphere, on continental and oceanic areas, in a comprehensive way, all over the World. This layer is part of the Geothermal Atlas for Africa developed within the LEAP-RE project"

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.

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