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Not Updated layers
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Above- and belowground terrestrial carbon per country
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Above- and belowground terrestrial carbon per country

Carbon (C) storage in biomass (biological material) is a key link in the global carbon cycle, and consequently for climate change mitigation. Biomass binds carbon from the atmosphere (CO2) as it grows. Forests in particular are an important Carbon sink that help reduce the greenhouse effect. This map represents above- and below-ground terrestrial carbon storage (tonnes (t) of C per hectare (ha)) per country for circa 2010. Above-ground biomass (stem, bark, branches, twigs...) and below-ground biomass (stump, roots...) were extracted from available biomass carbon datasets, summed together and multiplied by 0.5 to convert to carbon.


GOAL 15: Life on land


Other SDGs

GOAL 13: Climate Action


Natural Resources Biodiversity & Wildlife Forests Soil Ecosystem Services


Source: EC-JRC

Not Updated layers
apps
Above Ground Carbon
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Above Ground Carbon

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.


GOAL 15: Life on land


Other SDGs

GOAL 13: Climate Action


Climate Change Natural Resources Biodiversity & Wildlife Forests Soil Ecosystem Services


Source: GlobBiomass

Weekly layers
apps
Active Fire anomaly from MODIS/FIRMS at 10 km resolution
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Active Fire anomaly from MODIS/FIRMS at 10 km resolution

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).


GOAL 13: Climate action


Other SDGs


Climate Change Climate Services Greenhouse Gas Emissions Disaster Risk Natural Disasters Natural Resources Forests


Source: EC-JRC

Annual layers
apps
Annual energy production of hydropower plants
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Annual energy production of hydropower plants

Many African countries, especially in the Sub-Saharan region, highly depend on hydropower, which is one of the energy sources 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 location and annual energy production (GWh/year) of hydropower plants with an installed capacity above 5MW in Africa for year 2016.


GOAL 09: Industry, innovation and infrastructure


Other SDGs


Water & Freshwater Energy Energy Production Clean & Renewable Energy


Source: EC-JRC

Not Updated layers
apps
Annual evaporation from hydropower reservoirs
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Annual evaporation from hydropower reservoirs

Evaporation from hydropower reservoirs represents a key component of the reservoir water budget. Depending on the different climate regimes on the continent, the rate of evaporation from open water changes with region-specific temperature, wind speed, relative humidity and solar radiation. This map shows the annual mean evaporation rate (mm/year) at the centroid of African reservoirs subject to hydropower production, for the year 2016.


GOAL 07: Affordable and clean energy


Other SDGs

GOAL 9: Industry, Innovation and Infrastructure


Natural Resources Water & Freshwater Energy Energy Production Clean & Renewable Energy


Source: EC-JRC

Not Updated layers
apps
Annual gross water loss through evaporation from hydropower reservoirs (mcm/year)
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Annual gross water loss through evaporation from hydropower reservoirs (mcm/year)

Dam-induced impoundment of water in hydropower reservoirs usually causes enlarged water surfaces compared to the waterbody extent prior to dam construction (with the exception of reservoirs constrained by geomorphologic features, i.e. canyons). The annual gross water loss from reservoirs is determined by the reservoir surface area, annual evaporation and a shared use allocation factor in the case of multi-purpose reservoirs. Consequently, an enlarged reservoir surface area leads to increased water losses, depending on location’s climate regime and shared uses of reservoir water. This map shows the yearly gross water loss (mcm/year) from hydropower reservoirs in Africa, as of 2016. Water losses from waterbody surfaces prior to dam construction are not considered in the estimates.


GOAL 07: Affordable and clean energy


Other SDGs

GOAL 9: Industry, Innovation and Infrastructure


Natural Resources Water & Freshwater Energy Energy Production Clean & Renewable Energy


Source: EC-JRC

Not Updated layers
apps
Annual gross water loss vs annual energy production of hydropower plants (mcm/GWh)
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Annual gross water loss vs annual energy production of hydropower plants (mcm/GWh)

In 2016, a total of 42 billion cubic meters of water was lost through evaporation in hydropower reservoirs in Africa. A huge amount compared to the 1.2 billion cubic meters lost from all the other fuel types combined. In the same period, hydropower accounted for 15% of Africa’s total energy production. The ratio of annual water loss (from a hydropower reservoir) versus energy production (of the associated hydropower plant) describes somehow the water efficiency of a hydropower site. The ratio varies from region to region and depend on the reservoir’s surface area and evaporation rate, and on the produced energy of the associated hydropower plant. A better performance (lower ratios, i.e. ratios below 1) in terms of reduced water losses through evaporation per produced energy unit can be achieved at hydropower sites characterized by decreased reservoir surfaces and increased energy production. In contrast, unfavourable, higher ratios occur with water losses higher than the associated hydropower energy production rates. This map shows the location and ratio water loss / energy production (mcm/GWh) of hydropower plants in Africa for year 2016.


GOAL 07: Affordable and clean energy


Other SDGs

GOAL 6: Clean Water and Sanitation, GOAL 9: Industry, Innovation and Infrastructure


Natural Resources Water & Freshwater Energy Energy Production Clean & Renewable Energy


Source: EC-JRC

Not Updated layers
apps
Annual photovoltaic energy yield
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Annual photovoltaic energy yield

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


GOAL 07: Affordable and clean energy


Other SDGs


Energy Energy Production Energy Access Clean & Renewable Energy


Source: EC-JRC

Not Updated layers
apps
Annual precipitation variability (L-CV)
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Annual precipitation variability (L-CV)

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.


GOAL 13: Climate action


Other SDGs

GOAL 6: Clean Water and Sanitation


Climate Change Climate Services Desertification


Source: EC-JRC

Annual layers
apps
Annual surface area of hydropower reservoirs
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Annual surface area of hydropower reservoirs

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.


GOAL 07: Affordable and clean energy


Other SDGs

GOAL 9: Industry, Innovation and Infrastructure


Water & Freshwater Energy Energy Production Clean & Renewable Energy


Source: EC-JRC

Not Updated layers
apps
Annual water loss through evaporation from hydropower reservoirs (mcm/year)
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Annual water loss through evaporation from hydropower reservoirs (mcm/year)

Dam-induced impoundment of water in hydropower reservoirs usually causes enlarged water surfaces compared to the waterbody extent prior to dam construction (with the exception of reservoirs constrained by geomorphologic features, i.e. canyons). The annual gross water loss from reservoirs is determined by the reservoir surface area, annual evaporation and a shared use allocation factor in the case of multi-purpose reservoirs. Consequently, an enlarged reservoir surface area leads to a significant increase of water losses, depending on location’s climate regime and shared uses of reservoir water. This map shows the location and yearly gross water loss (mcm/year) from hydropower reservoirs in Africa, as of 2016. Water losses from waterbody surfaces prior to dam construction are not considered in the estimates.


GOAL 07: Affordable and clean energy


Other SDGs

GOAL 6: Clean Water and Sanitation, GOAL 9: Industry, Innovation and Infrastructure


Water & Freshwater Energy Energy Production Clean & Renewable Energy


Source: EC-JRC

10-Days layers
apps
Anomalies for Fraction of Absorbed Photosynthetically Active Radiation (FAPAR).
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Anomalies for Fraction of Absorbed Photosynthetically Active Radiation (FAPAR).

The Fraction of Photosynthetically Active Radiation Absorbed (FAPAR) is used to track the overall primary productivity associated with atmospheric CO2 fixation. FAPAR anomalies relative to the average between 2003 and 2010 show large surface variations, in terms of values and coverage, of vegetation productivity conditions over Africa. Temperature and precipitation deficits are the main drivers for the negative anomalies. Each location with a negative anomaly (FAPAR value lower than the long-term mean for that location – shades of red) indicates relative vegetation stress during that 10-day interval. Each location with a positive anomaly (FAPAR value higher than long-term mean for that location – shades of green) indicates relative favourable vegetation growth conditions during that 10-day interval. FAPAR values and their anomalies provide useful information for water and agricultural management purposes.


GOAL 15: Life on land


Other SDGs

GOAL 13: Climate Action


Real Time Climate Change Natural Resources Forests Food and Agriculture


Source: EC-JRC

10-Days layers
apps
Anomalies for Leaf Area Index (LAI)
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Anomalies for Leaf Area Index (LAI)

Evapotranspiration and carbon fluxes between the biosphere and the atmosphere are routinely expressed in terms of the Leaf Area Index (LAI) of the canopy. Monitoring the change of LAI is essential for assessing the evolution of the vegetation over Africa. LAI anomalies relative to the average values between 2003 and 2010 show apparent variations of vegetation cover over Africa. Increase of temperature and precipitation deficits are the main drivers for the negative anomalies. Human or animals may also locally impact the state of leaves. This record shows the anomalies of LAI every 10-days reflecting its large variations over Africa.


GOAL 15: Life on land


Other SDGs

GOAL 13: Climate Action


Real Time Climate Change Natural Resources Forests Food and Agriculture


Source: EC-JRC

Not Updated layers
apps
Aridity (areas of concern)
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Aridity (areas of concern)

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.


GOAL 15: Life on land


Other SDGs


Security Disaster Risk Natural Disasters Resource Scarcity Land Degradation Desertification Natural Resources Water & Freshwater Soil Food and Agriculture Food Security


Source: EC-JRC

Annual layers
apps
Armed conflicts (2019-2022)
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Armed conflicts (2019-2022)

Most conflicts initially start out as very local phenomena. Monitoring political violence events at local-level can help anticipate the escalation of conflicts within states, recognise signs of crisis development and determine likely conflict trajectories. The Armed Conflict Location & Event Data Project (ACLED) collects reported information on internal political conflict disaggregated by date, location and actors to facilitate local and scale-dependant research on war patterns and processes. This layer shows all political violence and protest events recorded by ACLED in Africa for the period 2019-2022.


GOAL 16: Peace, justice and strong institutions


Other SDGs


Security Peace Conflicts, Violence, Criminal networks Maritime Security Sustainable Growth & Jobs Gender & Inequality Politics War & Peace People Life Expectancy


Source: Armed Conflict Location & Event Data Project (ACLED)

Not Updated layers
apps
Average annual precipitation (1981-2017)
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Average annual precipitation (1981-2017)

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.


GOAL 06: Clean water and sanitation


Other SDGs


Climate Change Climate Services Desertification


Source: EC-JRC

Not Updated layers
apps
Battery Size vs Photovoltaic Array ratio (kWH/KWP) - High day-time consumption
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Battery Size vs Photovoltaic Array ratio (kWH/KWP) - High day-time consumption

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 layer presents the ratio between the optimized battery size (kWh) and PV array size (kWp) for PV mini-grid using Li-ion batteries to store electricity (instead of the traditional lead-acid batteries) based on a high energy consumption pattern (most energy used during 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 electrification of regions where access to electricity is lacking.


GOAL 07: Affordable and clean energy


Other SDGs


Energy Energy Production Clean & Renewable Energy


Source: EC-JRC

Not Updated layers
apps
Battery Size vs Photovoltaic Array ratio (kWH/KWP) - High night-time consumption
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Battery Size vs Photovoltaic Array ratio (kWH/KWP) - High night-time consumption

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 layer presents the ratio between the optimized battery size (kWh) and PV array size (kWp) for PV mini-grid using Li-ion batteries to store electricity (instead of the traditional lead-acid batteries) based on a low energy consumption pattern (most energy used during night-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 electrification of regions where access to electricity is lacking.


GOAL 07: Affordable and clean energy


Other SDGs


Energy Energy Production Clean & Renewable Energy


Source: EC-JRC

Not Updated layers
apps
Below ground biomass carbon
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Below ground biomass carbon

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).


GOAL 15: Life on land


Other SDGs

GOAL 13: Climate Action


Climate Change Deforestation Natural Resources Biodiversity & Wildlife Forests Soil Ecosystem Services


Source: GlobBiomass

Not Updated layers
apps
Biodiversity Hotspots
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Biodiversity Hotspots

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.


GOAL 15: Life on land


Other SDGs


Natural Resources Biodiversity & Wildlife Protected Areas & Ecological Networks


Source: Critical Ecosystem Partnership Fund (CEPF)

Annual layers
apps
Biodiversity Intactness Index
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Biodiversity Intactness Index

The Biodiversity Intactness Index shows the modelled average abundance of originally-present species in a grid cell, as a percentage, relative to their abundance in an intact ecosystem. Originally available for year 2015, the data is now available in a time series covering the period 2000-2015 - here we provide a bi-decade subset of the index.


GOAL 15: Life on land


Other SDGs


Natural Resources Biodiversity & Wildlife Forests Protected Areas & Ecological Networks


Source: UNEP-WCMC, University College London, Natural History Museum, Imperial College London, CSIRO Canberra, Luc Hoffmann Institute, University of Copenhagen, University of Sussex

Not Updated layers
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Biomes

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.


GOAL 15: Life on land


Other SDGs


Climate Change Natural Resources Biodiversity & Wildlife Forests Food and Agriculture Agroecology


Source: EC-JRC

Annual layers
apps
Biomes protection levels
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Biomes protection levels

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.


GOAL 15: Life on land


Other SDGs


Climate Change Natural Resources Biodiversity & Wildlife Protected Areas & Ecological Networks Food and Agriculture


Source: EC-JRC

Not Updated layers
apps
Built-up area change (areas of concern)
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Built-up area change (areas of concern)

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.


GOAL 15: Life on land


Other SDGs


Climate Change Sustainable Growth & Jobs Territorial Development Urban Development People


Source: EC-JRC

Not Updated layers
apps
Built-up presence (1975)
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Built-up presence (1975)

The Global Human Settlement Layer (GHSL) project produces global spatial information about the human presence on the planet. It benefits many applications ranging from disaster risk reduction and post-disaster humanitarian relief to regular monitoring of changes in human settlement patterns and extent. This layer displays the built-up area in 1975. The value of each cell represent the proportion of building footprint area within the total size of the cell (1km x 1km).


GOAL 11: Sustainable cities and communities


Other SDGs


Sustainable Growth & Jobs Territorial Development Urban Development People Population Growth


Source: EC-JRC

Not Updated layers
apps
Built-up presence (1990)
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Built-up presence (1990)

The Global Human Settlement Layer (GHSL) project produces global spatial information about the human presence on the planet. It benefits many applications ranging from disaster risk reduction and post-disaster humanitarian relief to regular monitoring of changes in human settlement patterns and extent. This layer displays the built-up area in 1990. The value of each cell represent the proportion of building footprint area within the total size of the cell (1km x 1km).


GOAL 11: Sustainable cities and communities


Other SDGs


Sustainable Growth & Jobs Territorial Development Urban Development People Population Growth


Source: EC-JRC

Not Updated layers
apps
Built-up presence (2000)
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Built-up presence (2000)

The Global Human Settlement Layer (GHSL) project produces global spatial information about the human presence on the planet. It benefits many applications ranging from disaster risk reduction and post-disaster humanitarian relief to regular monitoring of changes in human settlement patterns and extent. This layer displays the built-up area in 2000. The value of each cell represent the proportion of building footprint area within the total size of the cell (1km x 1km).


GOAL 11: Sustainable cities and communities


Other SDGs


Sustainable Growth & Jobs Territorial Development Urban Development People Population Growth


Source: EC-JRC

Not Updated layers
apps
Built-up presence (2014)
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Built-up presence (2014)

The Global Human Settlement Layer (GHSL) project produces global spatial information about the human presence on the planet. It benefits many applications ranging from disaster risk reduction and post-disaster humanitarian relief to regular monitoring of changes in human settlement patterns and extent. This layer displays the built-up area in 1975. The value of each cell represent the proportion of building footprint area within the total size of the cell (1km x 1km).


GOAL 11: Sustainable cities and communities


Other SDGs

GOAL 15: Life on Land


Sustainable Growth & Jobs Territorial Development Urban Development People Population Growth


Source: EC-JRC

apps
Change In Aboveground Woody Carbon Density 2003-2014
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Change In Aboveground Woody Carbon Density 2003-2014

The data provided here are the result of a time-series analysis of carbon density change (in Mg/ha) between 2003-2014 spanning tropical America, Africa, and Asia (23.45 N lat.-23.45 S lat.). The original data is provided as two separate rasters representing (1) carbon density net gain and (2) carbon density net loss within each ~463 x 463 metre pixel, with only pixels exhibiting statistical significance at the 95% level being reported. The data here was re-projected from the its original MODIS sinusoidal projection to WGS84.


GOAL 15: Life on land


Other SDGs

GOAL 13: Climate Action


Natural Resources Biodiversity & Wildlife Forests


Source: Woodwell Climate Research Center

Not Updated layers
apps
Change in Malaria Prevalence among Children (%) 2000- 2015
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Change in Malaria Prevalence among Children (%) 2000- 2015

Malaria, a life-threatening disease transmitted by mosquitoes, affects millions of people worldwide. Treatment and prevention efforts such as insecticide-treated mosquito nets and rapid diagnostic tests significantly decreased the number of malaria cases in Africa. This layer displays the change in malaria rates (%) from 2000 to 2015 among children in Sub-Saharan Africa.


GOAL 03: Good health and well-being


Other SDGs


Health Public Health Diseases & Pandemic One Health Sustainable Growth & Jobs People Demography


Source: University of Oxford

Not Updated layers
apps
Chinese Government-funded projects
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Chinese Government-funded projects

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.


GOAL 09: Industry, innovation and infrastructure


Other SDGs


Economy Sustainable Growth & Jobs Gender & Inequality Politics Rural Development Territorial Development Urban Development


Source: AidData

Not Updated layers
apps
Climate-Vegetation trends (areas of concern)
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Climate-Vegetation trends (areas of concern)

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).


GOAL 15: Life on land


Other SDGs


Climate Change Climate Services Desertification Deforestation Natural Resources Biodiversity & Wildlife Forests


Source: EC-JRC

Not Updated layers
apps
Cocoa map for Cote d'Ivoire and Ghana
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Cocoa map for Cote d'Ivoire and Ghana

Côte d'Ivoire and Ghana are the main largest producers of cocoa in the world. However, the cultivation of this crop has led to the loss of vast tracts of forest areas in both countries. Efficient and accurate methods for remotely identifying cocoa farms are essential for the implementation of sustainable cocoa practices and the periodic and effective monitoring of forests. This map, generated using Random Forest image classification, shows the 2019 distribution of cocoa farms in both countries. The estimated area for cocoa is 4.8Mha for Cote d'Ivoire and 2.3Mha for Ghana.


GOAL 15: Life on land


Other SDGs

GOAL 12: Responsible Consumption and Production, GOAL 2: Zero Hunger


Food and Agriculture Land Use in Agriculture Food Production


Source: EC-JRC

Not Updated layers
apps
Convergence of global change issues
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Convergence of global change issues

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.


GOAL 15: Life on land


Other SDGs


Climate Change Land Degradation Desertification Deforestation Natural Resources Ecosystem Services


Source: EC-JRC

Annual layers
apps
Copernicus Global Land Cover 2019
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Copernicus Global Land Cover 2019

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.


GOAL 15: Life on land


Other SDGs


Sustainable Growth & Jobs Rural Development Territorial Development Urban Development Natural Resources Biodiversity & Wildlife Forests Land Use in Agriculture


Source: EC-JRC

apps
Copernicus Hot Spot Land Cover
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Copernicus Hot Spot Land Cover

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.


GOAL 15: Life on land


Other SDGs


Climate Change Natural Resources Biodiversity & Wildlife Forests Protected Areas & Ecological Networks


Source: EC-JRC

Annual layers
apps
Copernicus Hot Spot Land Cover Change (2000-2019)
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Copernicus Hot Spot Land Cover Change (2000-2019)

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.


GOAL 15: Life on land


Other SDGs


Climate Change Natural Resources Forests Protected Areas & Ecological Networks


Source: EC-JRC

Near Real Time layers
apps
Coral bleaching Hotspots
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Coral bleaching Hotspots

Healthy coral reefs provide a home for millions of aquatic species. They protect coastal homes from storms and support commercial and subsistence fisheries as well as jobs and businesses through tourism and recreation. Yet they are severely threatened by pollution, disease, habitat destruction and climate change. When corals are stressed, they expel the symbiotic algae living in their tissues and become white (bleached) and vulnerable. Corals are vulnerable to bleaching when the sea surface temperature (SST) exceeds the temperatures normally experienced in the hottest month of the year. The NOAA Coral Reef Watch daily global 5km Coral Bleaching HotSpot product measures the occurrence and magnitude of instantaneous heat stress, potentially resulting in coral bleaching. It highlights regions where the SST is warmer than the highest monthly mean. HotSpot values of 1°C or more indicate heat stress leading to coral bleaching and are highlighted in yellow to dark red colors.


GOAL 13: Climate action


Other SDGs

GOAL 14: Life Below Water


Real Time Climate Change Natural Resources Marine Resources


Source: National Oceanic and Atmospheric Administration (NOAA)

apps
Coral Reef Shoreline Protection Index
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Coral Reef Shoreline Protection Index

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.


GOAL 14: Life below water


Other SDGs


Natural Resources Biodiversity & Wildlife Marine Resources Ecosystem Services


Source: The Nature Conservancy (TNC), World Resources Institute (WRI), the University of Washington (UWash), and the University of Cambridge

Not Updated layers
apps
Cost of electricity produced by a diesel generator
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Cost of electricity produced by a diesel generator

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.


GOAL 07: Affordable and clean energy


Other SDGs


Energy Energy Production


Source: EC-JRC

Not Updated layers
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Cost of Photo Voltaic versus Diesel
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Cost of Photo Voltaic versus Diesel

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.


GOAL 07: Affordable and clean energy


Other SDGs


Climate Change Energy Energy Production Clean & Renewable Energy


Source: EC-JRC

Annual layers
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Countries' species richness
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Countries' species richness

Biodiversity and the ecosystem services it supports are not only the foundation for our life on Earth, but also critical to the livelihoods and well-being of people everywhere. Africa’s extraordinary richness in biodiversity and ecosystem services, and wealth of indigenous and local knowledge, comprises a strategic asset for 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 countries' richness in animal and plant species 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.


GOAL 15: Life on land


Other SDGs


Natural Resources Biodiversity & Wildlife


Source: EC-JRC

Annual layers
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Countries' threatened mammals
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Countries' threatened mammals

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.


GOAL 15: Life on land


Other SDGs


Natural Resources Biodiversity & Wildlife


Source: EC-JRC

Annual layers
apps
Covenant of Mayors signatures
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Covenant of Mayors signatures

Started in 2015, the Covenant of Mayors in Sub-Saharan Africa (CoM SSA) initiative supports Sub-Saharan cities in their fight against climate change and in their efforts in ensuring access to clean energy. CoM SSA is part of the Global Covenant of Mayors for Climate and Energy (GCoM) – the largest coalition of cities committed to local climate and energy action. Under the CoM SSA, local authorities make a voluntary political commitment to implement climate and energy actions in their communities. This layer shows the location and year of signature of signatory cities and municipalities of the CoM SSA.


GOAL 07: Affordable and clean energy


Other SDGs

GOAL 11: Sustainable Cities and Communities, GOAL 13: Climate Action, GOAL 17: Partnerships to achieve the Goal


Sustainable Growth & Jobs Politics Energy


Source: EC-JRC

Annual layers
apps
Cropland extent
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Cropland extent

By detecting areas where agricultural production deficits might occur, it is possible to prevent food security crises and anticipate response planning. To do this, we need accurate and reliable information on agricultural land cover. This layer shows the extent of cropland in Africa. Each pixel represents the fraction of the area covered by cropland (i.e. the percentage of the pixel with crops).


GOAL 02: Zero hunger


Other SDGs

GOAL 12: Responsible Consumption and Production, GOAL 2: Zero Hunger


Natural Resources Food and Agriculture Land Use in Agriculture


Source: EC-JRC

Annual layers
apps
Crop Mapping for GEOGLAM Country Level Support - Kenya
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Crop Mapping for GEOGLAM Country Level Support - Kenya

Crop conditions monitoring is highly relevant for food security early warning and response planning in food insecure areas of the world. GEOGLAM is the Group on Earth Observations' Global Agricultural Monitoring Initiative. Its main objective is 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 by using Earth Observation data. Copernicus4GEOGLAM is one of the Copernicus Land Monitoring Services managed by the EC Joint Research Centre. This project aims at producing baseline information allowing countries in Africa to improve their agricultural monitoring systems. This crop map covers a 98 687 km2 area of Kenya. It shows the situation at the end of the long rain season of 2021. The mapping service is requested by the country and the results are made fully and freely accessible.


GOAL 02: Zero hunger


Other SDGs


Crop Health


Source: EC-JRC

Annual layers
apps
Crop Mapping for GEOGLAM Country Level Support - Tanzania
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Crop Mapping for GEOGLAM Country Level Support - Tanzania

Crop conditions monitoring is highly relevant for food security early warning and response planning in food insecure areas of the world. GEOGLAM is the Group on Earth Observations' Global Agricultural Monitoring Initiative. Its main objective is 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 by using Earth Observation data. Copernicus4GEOGLAM is one of the Copernicus Land Monitoring Services managed by the EC Joint Research Centre. This project aims at producing baseline information allowing countries in Africa to improve their agricultural monitoring systems. This crop map covers a 116 190 km2 of Tanzania. It shows the situation at the end of the long rain season of 2021. The mapping service is requested by the country and the results are made fully and freely accessible.


GOAL 02: Zero hunger


Other SDGs


Crop Health


Source: EC-JRC

Annual layers
apps
Crop Mapping for GEOGLAM Country Level Support - Uganda
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Crop Mapping for GEOGLAM Country Level Support - Uganda

Crop conditions monitoring is highly relevant for food security early warning and response planning in food insecure areas of the world. GEOGLAM is the Group on Earth Observations' Global Agricultural Monitoring Initiative. Its main objective is 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 by using Earth Observation data. Copernicus4GEOGLAM is one of the Copernicus Land Monitoring Services managed by the EC Joint Research Centre. This project aims at producing baseline information allowing countries in Africa to improve their agricultural monitoring systems. This crop map covers a 89296 km2 of Uganda. It shows the situation at the end of the long rain season of 2021. The mapping service is requested by the country and the results are made fully and freely accessible.


GOAL 02: Zero hunger


Other SDGs

GOAL 15: Life on Land


Crop Health


Source: EC-JRC

Near Real Time layers
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Daily Coral Bleaching Heat Stress Alert Area
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Daily Coral Bleaching Heat Stress Alert Area

Healthy coral reefs provide a home for millions of aquatic species and numerous ecosystemic services. Yet they are severely threatened. When stressed, corals expel the symbiotic algae living in their tissues and become white (bleached) and vulnerable. The NOAA Coral Reef Watch daily global 5km satellite coral Bleaching Alert Area (7-day maximum) is a composite product that summarizes the current Degree Heating Week (a cumulative measurement of both intensity and duration of heat stress) and Coral Bleaching HotSpot (occurrence and magnitude of instantaneous heat stress) values. At a glance, this layer outlines the current locations, coverage, and potential risk level of coral bleaching heat stress.


GOAL 13: Climate action


Other SDGs

GOAL 14: Life Below Water


Real Time Climate Change Natural Resources Marine Resources


Source: National Oceanic and Atmospheric Administration (NOAA)

Not Updated layers
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Decreasing land productivity (areas of concern)
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Decreasing land productivity (areas of concern)

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.


GOAL 15: Life on land


Other SDGs


Economy Climate Change Resource Scarcity Land Degradation Natural Resources Soil Food and Agriculture Yields Food per Person


Source: EC-JRC

Annual layers
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Education Contribution to Overall Poverty Index (%)
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Education Contribution to Overall Poverty Index (%)

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.


GOAL 01: No poverty


Other SDGs

GOAL 10: Reduced Inequality, GOAL 4: Quality Education


Economy Training & Capacity Building Sustainable Growth & Jobs Education Gender & Inequality People


Source: University of Oxford

10-Days layers
apps
Effective Leaf Area Index (LAI)
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Effective Leaf Area Index (LAI)

Evapotranspiration and carbon fluxes between the biosphere and the atmosphere are routinely expressed in terms of the Leaf Area Index (LAI) of the canopy. Monitoring the distribution and changes of LAI is therefore important for assessing the state and evolution of the vegetation over Africa. LAI of a plant canopy is a quantitative measure of the amount of live green leaf material present in the canopy per unit ground surface. Specifically, it is defined as the total one-sided area of all leaves in the canopy within a defined region, and is a non-dimensional quantity, although units of m2/m2 are often quoted, as a reminder of its meaning. This concept is largely used in agro-meteorology, but many atmospheric general circulation or biogeochemical models also rely on it to parameterize the vegetation cover, or its interactions with the atmosphere.


GOAL 15: Life on land


Other SDGs

GOAL 13: Climate Action


Real Time Climate Change Natural Resources Forests Food and Agriculture


Source: EC-JRC

Not Updated layers
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Electricity network existing and planned
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Electricity network existing and planned

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.


GOAL 07: Affordable and clean energy


Other SDGs


Sustainable Growth & Jobs Rural Development Territorial Development Urban Development Energy Energy Access Rural Electrification


Source: EC-JRC

Annual layers
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Endemic Bird Areas
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Endemic Bird Areas

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.


GOAL 15: Life on land


Other SDGs

GOAL 14: Life Below Water


Natural Resources Biodiversity & Wildlife Protected Areas & Ecological Networks


Source: Birdlife

Near Real Time layers
apps
Europe Media Monitor News
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Europe Media Monitor News

The Europe Media Monitor (EMM) News Brief is a summary of news stories from around the world, automatically classified according to thousands of criteria. It is generated automatically every 10 minutes, 24 hours a day, 7 days a week. This layer displays the latest geo-localised news articles caught by the EMM with the keyword “Africa”, together with the link to the original source. You can also search for other keywords in the legend (topic, country name, etc).


GOAL 17: Partnerships for the goals


Other SDGs


Real Time Health Economy Digital Transformation eServices Security Climate Change Sustainable Growth & Jobs Natural Resources Food and Agriculture Energy


Source: EC-JRC

Not Updated layers
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Fires (areas of concern)
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Fires (areas of concern)

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.


GOAL 15: Life on land


Other SDGs


Security Climate Change Disaster Risk Natural Disasters Land Degradation Desertification Deforestation Natural Resources


Source: EC-JRC

Near Real Time layers
apps
Fires last 24 Hours
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Fires last 24 Hours

The Fire Information for Resource Management System (FIRMS) of the National Aeronautics and Space Administration (NASA) uses satellite observations to detect active fires and thermal anomalies. They deliver this information to decision makers in near real-time (within 3 hours of satellite observation). This dataset includes active fires of the last 24h. Each point represents the centre of a 375 m resolution pixel where a fire was detected. It is updated twice daily. Compared to other coarser resolution (≥1km) satellite fire detection products, it provides improved response for smaller fires, improved mapping of large fire perimeters, and better detection at night, when fire activities usually occur. Consequently, the data are well suited for use in support of fire tracking and management (e.g., near real-time alert systems), as well as other science applications requiring improved fire mapping fidelity.


GOAL 13: Climate action


Other SDGs

GOAL 15: Life on Land


Real Time Climate Change Greenhouse Gas Emissions Natural Disasters


Source: NASA

Near Real Time layers
apps
Fires last 48 Hours
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Fires last 48 Hours

The Fire Information for Resource Management System (FIRMS) of the National Aeronautics and Space Administration (NASA) uses satellite observations to detect active fires and thermal anomalies. They deliver this information to decision makers in near real-time (within 3 hours of satellite observation). This dataset includes active fires of the last 48h. Each point represents the centre of a 375 m resolution pixel where a fire was detected. It is updated twice daily. Compared to other coarser resolution (≥1km) satellite fire detection products, it provides improved response for smaller fires, improved mapping of large fire perimeters, and better detection at night, when fire activities usually occur. Consequently, the data are well suited for use in support of fire tracking and management (e.g., near real-time alert systems), as well as other science applications requiring improved fire mapping fidelity.


GOAL 13: Climate action


Other SDGs

GOAL 15: Life on Land


Real Time Climate Change Greenhouse Gas Emissions Natural Disasters


Source: NASA

Near Real Time layers
apps
Fires last 72 Hours
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Fires last 72 Hours

The Fire Information for Resource Management System (FIRMS) of the National Aeronautics and Space Administration (NASA) uses satellite observations to detect active fires and thermal anomalies. They deliver this information to decision makers in near real-time (within 3 hours of satellite observation). This dataset includes active fires of the last 72h. Each point represents the centre of a 375 m resolution pixel where a fire was detected. It is updated twice daily. Compared to other coarser resolution (≥1km) satellite fire detection products, it provides improved response for smaller fires, improved mapping of large fire perimeters, and better detection at night, when fire activities usually occur. Consequently, the data are well suited for use in support of fire tracking and management (e.g., near real-time alert systems), as well as other science applications requiring improved fire mapping fidelity.


GOAL 13: Climate action


Other SDGs

GOAL 15: Life on Land


Real Time Climate Change Greenhouse Gas Emissions Natural Disasters


Source: NASA

Near Real Time layers
apps
Flood hazard (100-year return period)
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Flood hazard (100-year return period)

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.


GOAL 13: Climate action


Other SDGs

GOAL 15: Life on Land


Real Time Climate Change Natural Disasters Land Degradation Natural Resources


Source: EC-JRC

apps
Forest canopy height
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Forest canopy height

Forest canopy height measures the average height of the tree canopy in 2012. This dataset is created by integrating broadscale optical remotely sensed data at 30-metre spatial resolution with on-the-ground measurements.


GOAL 15: Life on land


Other SDGs


Natural Resources Forests


Source: NASA

Not Updated layers
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Forest Cover

Forests worldwide are in a state of flux, with accelerating losses in some regions and gains in others. Given the recognized importance of forest ecosystem services, quantification of global forest extent and change is needed. This map displays the tree cover in the year 2000. Tree cover is defined as canopy closure for all vegetation taller than 5m in height and is expressed as a percentage per output grid cell, in the range 0–100.


GOAL 15: Life on land


Other SDGs


Climate Change Natural Resources Biodiversity & Wildlife Forests


Source: Hansen/UMD/Google/USGS/NASA

Annual layers
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Forest Gain

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


GOAL 15: Life on land


Other SDGs


Climate Change Natural Resources Biodiversity & Wildlife Forests


Source: Hansen/UMD/Google/USGS/NASA

Annual layers
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Forest Loss

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


GOAL 15: Life on land


Other SDGs


Climate Change Natural Resources Biodiversity & Wildlife Forests


Source: Hansen/UMD/Google/USGS/NASA

10-Days layers
apps
Fraction of Absorbed Photosynthetic Radiation (FAPAR)
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Fraction of Absorbed Photosynthetic Radiation (FAPAR)

The Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) is an Essential Climate Variable that serves as an integrated indicator of the status and health of plant canopies. FAPAR plays a critical role in the global carbon cycle and in determining primary productivity of the biosphere. Climate change affects the terrestrial ecosystem dynamics, but few of these dynamics are observable from space. FAPAR is monitored using space remote sensing techniques, allowing high resolution and near-real-time measures of the state and evolution of terrestrial vegetation dynamics.


GOAL 15: Life on land


Other SDGs

GOAL 13: Climate Action


Real Time Climate Change Natural Resources Forests Food and Agriculture


Source: EC-JRC

Monthly layers
apps
Frequency of hotspots of agricultural production anomaly
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Frequency of hotspots of agricultural production anomaly

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.


GOAL 01: No poverty


Other SDGs

GOAL 12: Responsible Consumption and Production, GOAL 2: Zero Hunger


Land Use in Agriculture Yields Food per Person Crop Health


Source: EC-JRC

Monthly layers
apps
Frequency of ten-daily warnings about crop anomalies
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Frequency of ten-daily warnings about crop anomalies

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.


GOAL 01: No poverty


Other SDGs

GOAL 12: Responsible Consumption and Production, GOAL 2: Zero Hunger


Food and Agriculture Land Use in Agriculture Yields Crop Health


Source: EC-JRC

Monthly layers
apps
Frequency of ten-daily warnings about rangeland anomalies
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Frequency of ten-daily warnings about rangeland anomalies

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.


GOAL 01: No poverty


Other SDGs

GOAL 12: Responsible Consumption and Production, GOAL 2: Zero Hunger


Natural Disasters Natural Resources Food and Agriculture Crop Health


Source: EC-JRC

Not Updated layers
apps
Freshwater Global 200
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Freshwater Global 200

The Global 200 is the list of ecoregions identified by WWF, the global conservation organization, as priorities for conservation. According to WWF, an ecoregion is defined as a "relatively large unit of land or water containing a characteristic set of natural communities that share a large majority of their species dynamics, and environmental conditions". The WWF assigns a conservation status to each ecoregion in the Global 200: critical or endangered; vulnerable; and relatively stable or intact. Globally, over half of the ecoregions in the Global 200 are rated endangered.


GOAL 06: Clean water and sanitation


Other SDGs

GOAL 15: Life on Land


Natural Resources Biodiversity & Wildlife Protected Areas & Ecological Networks


Source: WWF

Daily layers
apps
Geo-location of sites with biodiversity funding
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Geo-location of sites with biodiversity funding

Mapping ongoing project activities in the field of conservation in protected areas is essential to identify the various actors and to identify the areas where information and actors are scarce. The aim is to better understand who is funding what and where, with a view to improve decision-making on biodiversity conservation. This map provides the geolocation of all sites that have received funding in the frame of a biodiversity conservation project -or an activity within a project- within approx. the last 20 years. It specifies whether the site is protected or not. One project usually includes several sites.


GOAL 15: Life on land


Other SDGs

GOAL 14: Life Below Water


Economy Financing Training & Capacity Building Sustainable Growth & Jobs Natural Resources Biodiversity & Wildlife Protected Areas & Ecological Networks


Source: EC-JRC

apps
Global Distribution of Coral Reefs
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Global Distribution of Coral Reefs

Warm-water coral reefs are the most biodiverse of marine habitats and the most important ecosystem engineers found in the marine environment. Most of this diversity is not due to the corals themselves but rather due to the multitude of organisms that depend on the coral reef ecosystem. 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.


GOAL 14: Life below water


Other SDGs


Natural Resources Biodiversity & Wildlife Marine Resources Water & Freshwater Ecosystem Services


Source: UNEP-WCMC

apps
Global rainfall erosivity change projections (2050 RCP 2.6)
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Global rainfall erosivity change projections (2050 RCP 2.6)

The erosive force of rainfall (rainfall erosivity) is a major driver of soil, nutrient losses worldwide and an important input for soil erosion assessments models. This map shows the geographical distribution of erosivity changes for RCP2.6 for the period 2010–2050.


GOAL 13: Climate action


Other SDGs

GOAL 15: Life on Land, GOAL 2: Zero Hunger


Climate Change Climate Services Disaster Risk Natural Disasters Land Degradation Desertification Soil Food and Agriculture


Source: EC-JRC

apps
Global rainfall erosivity change projections (2050 RCP 4.5)
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Global rainfall erosivity change projections (2050 RCP 4.5)

The erosive force of rainfall (rainfall erosivity) is a major driver of soil, nutrient losses worldwide and an important input for soil erosion assessments models. This map shows the geographical distribution of erosivity changes for RCP4.5 for the period 2010–2050.


GOAL 13: Climate action


Other SDGs

GOAL 15: Life on Land, GOAL 2: Zero Hunger


Climate Change Climate Services Disaster Risk Natural Disasters Land Degradation Desertification Soil Food and Agriculture


Source: EC-JRC

apps
Global rainfall erosivity change projections (2050 RCP 8.5)
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Global rainfall erosivity change projections (2050 RCP 8.5)

The erosive force of rainfall (rainfall erosivity) is a major driver of soil, nutrient losses worldwide and an important input for soil erosion assessments models. This map shows the geographical distribution of erosivity changes for RCP8.5 for the period 2010–2050.


GOAL 13: Climate action


Other SDGs

GOAL 15: Life on Land, GOAL 2: Zero Hunger


Climate Change Climate Services Disaster Risk Natural Disasters Land Degradation Desertification Soil Food and Agriculture


Source: EC-JRC

apps
Global rainfall erosivity change projections (2070 RCP 2.6)
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Global rainfall erosivity change projections (2070 RCP 2.6)

The erosive force of rainfall (rainfall erosivity) is a major driver of soil, nutrient losses worldwide and an important input for soil erosion assessments models. This map shows the geographical distribution of erosivity changes for RCP2.6 for the period 2050–2070.


GOAL 13: Climate action


Other SDGs

GOAL 15: Life on Land, GOAL 2: Zero Hunger


Climate Change Climate Services Disaster Risk Natural Disasters Land Degradation Desertification Soil Food and Agriculture


Source: EC-JRC

apps
Global rainfall erosivity change projections (2070 RCP 4.5)
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Global rainfall erosivity change projections (2070 RCP 4.5)

The erosive force of rainfall (rainfall erosivity) is a major driver of soil, nutrient losses worldwide and an important input for soil erosion assessments models. This map shows the geographical distribution of erosivity changes for RCP 4.5 for the period 2050–2070.


GOAL 13: Climate action


Other SDGs

GOAL 15: Life on Land, GOAL 2: Zero Hunger


Climate Change Climate Services Disaster Risk Natural Disasters Land Degradation Desertification Soil Food and Agriculture


Source: EC-JRC

apps
Global rainfall erosivity change projections (2070 RCP 8.5)
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Global rainfall erosivity change projections (2070 RCP 8.5)

The erosive force of rainfall (rainfall erosivity) is a major driver of soil, nutrient losses worldwide and an important input for soil erosion assessments models. This map shows the geographical distribution of erosivity changes for RCP8.5 for the period 2050–2070.


GOAL 13: Climate action


Other SDGs

GOAL 15: Life on Land, GOAL 2: Zero Hunger


Climate Change Climate Services Disaster Risk Natural Disasters Land Degradation Desertification Soil Food and Agriculture


Source: EC-JRC

apps
Great Green Wall - African Boundaries
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Great Green Wall - African Boundaries

The Great Green Wall (GGW) Initiative comprises 21 African countries and is implemented under the coordination of the African Union.


GOAL 15: Life on land


Other SDGs


Biodiversity & Wildlife Forests Protected Areas & Ecological Networks Ecosystem Services


Source: greatgreenwall

Not Updated layers
apps
Gridded Livestock of the World - Cattle
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Gridded Livestock of the World - Cattle

Global data sets on the geographic distribution of livestock are essential for diverse applications in agricultural socio-economics, food security, environmental impact assessment and epidemiology. This dataset contains the global distribution of cattle in 2010 expressed in total number of cattle per pixel (5 min of arc) according to the Gridded Livestock of the World database (GLW 3). Cattle are the most common and widespread species of large ruminant livestock and are raised primarily to produce milk, meat and hides and to provide draft power. In grass-based systems they play an important role in nutrient recycling and convert human-inedible plant matter into protein. Cattle are raised in diverse production systems ranging from capital-intensive, specialised beef and dairy grass-based and feed-lot systems; through multi-purpose cattle in labour-intensive, mixed crop-livestock systems; to extensive pastoral and agro-pastoral systems.


GOAL 15: Life on land


Other SDGs

GOAL 12: Responsible Consumption and Production


Food and Agriculture Food Production Rural Growth


Source: FAO

Not Updated layers
apps
Gridded Livestock of the World - Goats
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Gridded Livestock of the World - Goats

Global data sets on the geographic distribution of livestock are essential for diverse applications in agricultural socio-economics, food security, environmental impact assessment and epidemiology. This dataset contains the global distribution of goats in 2010 expressed in total number of goats per pixel (5 min of arc) according to the Gridded Livestock of the World database (GLW 3). The domestic goat is kept mainly for meat, milk, hides and hair. Unlike cattle and sheep, goats are primarily browsing animals and have an extremely varied plant diet that has allowed them to adapt to many diverse environments. They are raised in a wide range of production systems around the world. The majority are raised in smallholder, mixed farming systems but goats are an important component of pastoralist herds and high-value animals are raised for specialized dairy production in temperate regions.


GOAL 15: Life on land


Other SDGs

GOAL 12: Responsible Consumption and Production


Food and Agriculture Food Production Rural Growth


Source: FAO

Not Updated layers
apps
Gridded Livestock of the World - Sheep
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Gridded Livestock of the World - Sheep

Global data sets on the geographic distribution of livestock are essential for diverse applications in agricultural socio-economics, food security, environmental impact assessment and epidemiology. This dataset contains the global distribution of sheep in 2010 expressed in total number of sheep per pixel (5 min of arc) according to the Gridded Livestock of the World database (GLW 3). The domestic sheep is raised primarily for its wool, meat, milk and hides. Sheep are primarily grazing animals, cropping pasture close to the ground. They are raised in a wide range of production systems around the world, reflecting the prevailing environmental conditions and socio-economic context.


GOAL 15: Life on land


Other SDGs

GOAL 12: Responsible Consumption and Production


Rural Development Food and Agriculture Food Production


Source: FAO

Annual layers
apps
Health Contribution to Global Poverty Index (%)
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Health Contribution to Global Poverty Index (%)

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 first dimension in the MIP is the Health dimension. This includes child mortality and nutrition. This map represents the percentage contribution of the health dimension to overall poverty. The lower percentages are shown in darker reds while the higher percentages are shown as brighter, lighter reds.


GOAL 01: No poverty


Other SDGs

GOAL 10: Reduced Inequality


Health Public Health One Health Sustainable Growth & Jobs People Demography


Source: University of Oxford

Annual layers
apps
Heatwaves (1981-2018)
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Heatwaves (1981-2018)

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.


GOAL 13: Climate action


Other SDGs

GOAL 13: Climate Action


Climate Change Climate Services


Source: EC-JRC

Not Updated layers
apps
High-input agriculture (areas of concern)
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High-input agriculture (areas of concern)

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.


GOAL 15: Life on land


Other SDGs


Natural Resources Food and Agriculture Agroecology Sustainable Food Systems Food Production Water-Energy-Food Ecosystem


Source: EC-JRC

apps
Hydrological Basins in Africa
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Hydrological Basins in Africa

Africa is home to the longest river in the world -the Nile- and other major rivers like the Congo and the Niger. This layer shows the official boundaries of river (sub-)basins in Africa (approved and used by the FAO). The downloadable dataset contains the boundaries of the major hydrological basins and their sub-basins. It divides the African continent according to its hydrological characteristics.


GOAL 06: Clean water and sanitation


Other SDGs


Natural Resources Water & Freshwater Food and Agriculture Water-Energy-Food Ecosystem


Source: FAO

Not Updated layers
apps
Income level (areas of concern)
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Income level (areas of concern)

Smallholder farmers and pastoralists have restricted access to capital and may not have the capacity to invest in management practices that mitigate land degradation. This layer displays the areas of concern for the issues related to income level derived from the convergence of global evidence of human-environment interactions that can lead to land degradation.


GOAL 15: Life on land


Other SDGs


Economy Security Sustainable Growth & Jobs People Remittances


Source: EC-JRC

Annual layers
apps
INFORM Epidemic Risk Classes 2020
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INFORM Epidemic Risk Classes 2020

The management of risks due to biological hazards is a national and community priority. Epidemics of infectious diseases have shown the capacity to disrupt many dimensions of human existence. Moreover, they can affect anywhere in the world and severely test the global community's resilience. The INFORM Epidemic Risk Index is a prototype version of hazard dependent INFORM Risk Index (global risk assessment for humanitarian crises and disasters). It is a tool for assessing the countries' risk for all the type of epidemics. The risk levels are set as follows: LOW = risk score 3.5 and below; MEDIUM = risk score between 3.5 an 5; HIGH = risk score between 5 and 6.5; VERY HIGH = risk score 6.5 and above.


GOAL 03: Good health and well-being


Other SDGs

GOAL 10: Reduced Inequality


Health Public Health Diseases & Pandemic One Health Economy Sustainable Growth & Jobs


Source: EC-JRC

Annual layers
apps
INFORM Epidemic Risk Index 2020
close
INFORM Epidemic Risk Index 2020

The management of risks due to biological hazards is a national and community priority. Epidemics of infectious diseases have shown the capacity to disrupt many dimensions of human existence. Moreover, they can affect anywhere in the world and severely test the global community's resilience. The INFORM Epidemic Risk Index is a prototype version of hazard dependent INFORM Risk Index (global risk assessment for humanitarian crises and disasters). It is a tool for assessing the countries' risk for all the type of epidemics. The risk score ranges from 0-10, where 10 is the highest risk.


GOAL 03: Good health and well-being


Other SDGs

GOAL 10: Reduced Inequality


Health Public Health Diseases & Pandemic Economy Sustainable Growth & Jobs


Source: EC-JRC

Annual layers
apps
INFORM Epidemic Risk Index: Person-to-Person (P2P) transmission index
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INFORM Epidemic Risk Index: Person-to-Person (P2P) transmission index

For communities, inadequate shelter and overcrowding are major factors in the transmission of diseases with epidemic potential such as acute respiratory infections, meningitis, typhus, cholera, scabies, etc. Outbreaks of disease are more frequent and more severe when the population density is high. Other public structures such as health facilities not only represent a concentrated area of patients but also a concentrated area of germs. In an emergency, the number of hospital-associated infections will typically rise. Decreasing overcrowding by providing extra facilities and a proper organization of the sites or services in health-care facilities is a priority. As a component of the INFORM Epidemic Risk Index, this Person-to-Person (P2P) transmission index captures the countries' exposure to risk of P2P disease transmission. The risk score ranges from 0-10, where 10 is the highest risk.


GOAL 10: Reduced inequalities


Other SDGs

GOAL 10: Reduced Inequality


Health Public Health Hygiene & Sanitation Diseases & Pandemic One Health Sustainable Growth & Jobs Gender & Inequality


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Classes 2021
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INFORM Risk Classes 2021

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The INFORM Risk Index is a global, open-source risk assessment for humanitarian crises and disasters. It can support decisions about prevention, preparedness and response. This layer shows is which class of risk each of the African countries fall, on the basis of the latest INFORM Risk Index. The risk score ranges from 0-10, where 10 is the highest risk. The risk levels are set as follows: LOW = risk score 3.5 and below; MEDIUM = risk score between 3.5 an 5; HIGH = risk score between 5 and 6.5; VERY HIGH = risk score 6.5 and above.



Other SDGs

GOAL 11: Sustainable Cities and Communities, GOAL 17: Partnerships to achieve the Goal, GOAL 1: No Poverty, GOAL 2: Zero Hunger, GOAL 3: Good Health and Well-being, GOAL 6: Clean Water and Sanitation, GOAL 7: Affordable and Clean Energy, GOAL 9: Industry, Innovation and Infrastructure


Health Public Health Security Conflicts, Violence, Criminal networks Climate Change Natural Disasters People Humanitarian Aids


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index 2021
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INFORM Risk Index 2021

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The INFORM Risk Index is a global, open-source risk assessment for humanitarian crises and disasters. It can support decisions about prevention, preparedness and response. This layer presents the latest INFORM Risk Index of the African countries. The risk score ranges from 0-10, where 10 is the highest risk.



Other SDGs

GOAL 11: Sustainable Cities and Communities, GOAL 17: Partnerships to achieve the Goal, GOAL 1: No Poverty, GOAL 2: Zero Hunger, GOAL 3: Good Health and Well-being, GOAL 6: Clean Water and Sanitation, GOAL 7: Affordable and Clean Energy, GOAL 9: Industry, Innovation and Infrastructure


Security Conflicts, Violence, Criminal networks Climate Change Disaster Risk People Humanitarian Aids


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Access to health care
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INFORM Risk Index: Access to health care

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. Preparing the health workforce to work towards the attainment of a country's health objectives represents one of the most important challenges for its health system. As part of the coping capacity dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters) this layer shows an index for healthcare access. It captures the health system performance via indicators such as maternal mortality, the density of physicians and the overall system strength to deliver infant vaccination. The risk score ranges from 0-10, where 10 is the highest risk.


GOAL 03: Good health and well-being


Other SDGs

GOAL 3: Good Health and Well-being


Health Public Health Sustainable Growth & Jobs Gender & Inequality People Humanitarian Aids


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Aid dependency
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INFORM Risk Index: Aid dependency

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The main focus of humanitarian organizations is people. The Vulnerability dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters) addresses the predispositions of a population to be affected by hazard (economic, political and social characteristics of the community). The Aid Dependency component presented in this layer points out the countries that lack sustainability in development growth due to economic instability and humanitarian crisis. It measure the countries' economic dependency to public aid, development assistance, and remittances. The risk score ranges from 0-10, where 10 is the highest risk.


GOAL 17: Partnerships for the goals


Other SDGs


Sustainable Growth & Jobs Gender & Inequality Politics Territorial Development Smart Specialisation Partnership & Cooperation Economic Impact People Humanitarian Aids


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Children Under 5 vulnerability
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INFORM Risk Index: Children Under 5 vulnerability

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The main focus of humanitarian organizations is people. And young children are among the most vulnerable people in a humanitarian crisis. As part of the Vulnerability dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters), the Health Condition of Children Under Five component is referred to with two indicators: malnutrition and mortality of children under 5. The risk score ranges from 0-10, where 10 is the highest risk.


GOAL 03: Good health and well-being


Other SDGs


Health People Humanitarian Aids


Source: EC-JRC

Annual layers
apps
INFORM Risk Index: Communication
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INFORM Risk Index: Communication

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The coping capacity dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters) measures the ability of a country to cope with disasters in terms of organized activities, infrastructure and governmental effort. The communication component presented in this layer aims to measure the efficiency of dissemination of early warnings through a communication network as well as coordination of preparedness and emergency activities. It is dependent on the dispersion of the communication infrastructure as well as the literacy and education level of the recipients. The risk score ranges from 0-10, where 10 is the highest risk (poorest communication infrastructure).


GOAL 09: Industry, innovation and infrastructure


Other SDGs

GOAL 10: Reduced Inequality, GOAL 17: Partnerships to achieve the Goal, GOAL 7: Affordable and Clean Energy


Sustainable Growth & Jobs Education Gender & Inequality Technology Transfer People Humanitarian Aids


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Development deprivation
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INFORM Risk Index: Development deprivation

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The main focus of humanitarian organizations is people. The Vulnerability dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters) addresses the predispositions of a population to be affected by hazard (economic, political and social characteristics of the community). It is assumed that the more developed a country is the better its people will be able to respond to humanitarian needs using their own individual or national resources. The Development Deprivation component is a composite indicator that includes the Human Poverty Index (HDI), which measures development by combining indicators of life expectancy, educational attainment and income, and the Multidimensional Poverty Index (MPI), which identifies overlapping deprivations at the household level across the same three dimensions and shows the average number of poor people and deprivations with which poor households contend. The risk score ranges from 0-10, where 10 is the highest risk.


GOAL 01: No poverty


Other SDGs


Health Public Health Diseases & Pandemic Economy Financing Security Sustainable Growth & Jobs Gender & Inequality Politics Rural Development Territorial Development Urban Development People


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Disaster Risk Reduction implementation
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INFORM Risk Index: Disaster Risk Reduction implementation

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The coping capacity dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters) measures the ability of a country to cope with disasters in terms of organized activities, infrastructure and governmental effort. The indicator presented in this layer quantifies the level of implementation of Disaster Risk Reduction (DRR) activity for each country. The risk score ranges from 0-10, where 10 is the highest risk (poorest DRR implementation).


GOAL 13: Climate action


Other SDGs


Climate Change Disaster Risk Natural Disasters Sustainable Growth & Jobs Politics People Humanitarian Aids


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Food security
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INFORM Risk Index: Food security

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The main focus of humanitarian organizations is people. The Vulnerability dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters) addresses the predispositions of a population to be affected by hazard (economic, political and social characteristics of the community). This layer presents the Food Security component of the INFORM Risk Index. It encompasses the actual quality and type of food supplied to provide the nutritional balance necessary for healthy and active life. It captures trends in chronic hunger. The risk score ranges from 0-10, where 10 is the highest risk.


GOAL 02: Zero hunger


Other SDGs

GOAL 10: Reduced Inequality


Security Climate Change Disaster Risk Sustainable Growth & Jobs Gender & Inequality People Humanitarian Aids Food and Agriculture Yields Food Security Food Production


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Governance
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INFORM Risk Index: Governance

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The coping capacity dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters) measures the ability of a country to cope with disasters in terms of organized activities, infrastructure and governmental effort. The governance indicator presented in this layer captures the effectiveness of the governments’ effort for building resilience across all sectors of society as well as the level of misuse of political power for private benefit. The risk score ranges from 0-10, where 10 is the highest risk.


GOAL 16: Peace, justice and strong institutions


Other SDGs


Security Conflicts, Violence, Criminal networks Governance & Resilience Climate Change Disaster Risk Gender & Inequality Politics People Humanitarian Aids


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Health Conditions
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INFORM Risk Index: Health Conditions

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The main focus of humanitarian organizations is people. And people with limited access to health care systems are among the most vulnerable people in a humanitarian crisis. As part of the Vulnerability dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters), the "Health Conditions" index captures the prevalence of the three pandemics of low- and middle- income countries (HIV-AIDS, tuberculosis and malaria) as well as people requiring interventions against neglected tropical diseases. The risk score ranges from 0-10, where 10 is the highest risk.


GOAL 03: Good health and well-being


Other SDGs

GOAL 10: Reduced Inequality, GOAL 1: No Poverty


Health Public Health Diseases & Pandemic One Health Sustainable Growth & Jobs Gender & Inequality People Life Expectancy Humanitarian Aids


Source: EC-JRC

Annual layers
apps
INFORM Risk Index: Inequality
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INFORM Risk Index: Inequality

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The main focus of humanitarian organizations is people. The Vulnerability dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters) addresses the predispositions of a population to be affected by hazard (economic, political and social characteristics of the community). Countries with unequal distribution of human development also experience high inequality between women and men, and countries with high gender inequality also experience unequal distribution of human development. The Inequality component introduces the dispersion of conditions within population presented in the Development & Deprivation component. It includes a Gender Inequality Index, which reflects gender-based disadvantages in three dimensions—reproductive health, empowerment and the labour market, and the Gini coefficient, a measure of the extent to which the distribution of income or consumption expenditure among individuals or households within an economy deviates from a perfectly equal distribution. The risk score ranges from 0-10, where 10 is the highest risk.


GOAL 10: Reduced inequalities


Other SDGs


Economy Training & Capacity Building Climate Change Disaster Risk Sustainable Growth & Jobs Gender & Inequality People Humanitarian Aids


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Lack of coping capacity
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INFORM Risk Index: Lack of coping capacity

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. This layer presents the coping capacity dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters). It measures the ability of a country to cope with disasters in terms of organized activities, infrastructure and governmental effort. It is aggregated by a geometric mean of two categories: the institutional category covers the existence of DRR programs that address mostly mitigation and preparedness, and the infrastructure category measures the capacity for emergency response and recovery. The risk score ranges from 0-10, where 10 is the highest risk.



Other SDGs

GOAL 16: Peace and Justice Strong Institutions, GOAL 17: Partnerships to achieve the Goal, GOAL 3: Good Health and Well-being, GOAL 6: Clean Water and Sanitation, GOAL 7: Affordable and Clean Energy, GOAL 9: Industry, Innovation and Infrastructure


Economy Financing Digital Transformation Disaster Risk Sustainable Growth & Jobs Education Gender & Inequality Politics Partnership & Cooperation Humanitarian Aids


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Lack of coping capacity (infrastructure component)
close
INFORM Risk Index: Lack of coping capacity (infrastructure component)

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The coping capacity dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters) measures the ability of a country to cope with disasters in terms of organized activities, infrastructure and governmental effort. In particular, the infrastructure category presented in this layer measures the lack of capacity for emergency response and recovery. The risk score ranges from 0-10, where 10 is the highest risk.


GOAL 09: Industry, innovation and infrastructure


Other SDGs

GOAL 10: Reduced Inequality, GOAL 17: Partnerships to achieve the Goal, GOAL 3: Good Health and Well-being, GOAL 6: Clean Water and Sanitation, GOAL 7: Affordable and Clean Energy


Disaster Risk Sustainable Growth & Jobs Education Gender & Inequality Politics Technology Transfer People Humanitarian Aids Energy


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Lack of coping capacity (institutional component)
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INFORM Risk Index: Lack of coping capacity (institutional component)

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The coping capacity dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters) measures the ability of a country to cope with disasters in terms of organized activities, infrastructure and governmental effort. In particular, the institutional category presented in this layer covers the existence of Disaster Risk Reduction (DDR) programmes, which address mostly mitigation and preparedness, and the effectiveness of the governments’ effort for building resilience. The risk score ranges from 0-10, where 10 is the highest risk.


GOAL 16: Peace, justice and strong institutions


Other SDGs


Climate Change Disaster Risk Natural Disasters People Humanitarian Aids


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Lack of physical connectivity
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INFORM Risk Index: Lack of physical connectivity

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The coping capacity dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters) measures the ability of a country to cope with disasters in terms of organized activities, infrastructure and governmental effort. In particular, the physical infrastructure component presented in this layer tries to assess both the accessibility and the redundancy of the systems, which are two crucial characteristics in a crisis situation. It addresses safe management of drinking water and sanitation services, including dimensions of accessibility, availability and quality. The risk score ranges from 0-10, where 10 is the highest risk.


GOAL 09: Industry, innovation and infrastructure


Other SDGs


Sustainable Growth & Jobs Gender & Inequality Rural Development Territorial Development Trade & Connectivity Urban Development


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Recent shocks
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INFORM Risk Index: Recent shocks

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The main focus of humanitarian organizations is people. And people affected by recent natural disasters are considered more vulnerable than the rest of the population. As part of the Vulnerability dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters), the "Recent Shocks" indicator identifies the countries that are recovering from humanitarian crisis situation by taking into account the population affected by natural disasters in the last 3 years.


GOAL 01: No poverty


Other SDGs

GOAL 15: Life on Land


Climate Change Disaster Risk Natural Disasters Sustainable Growth & Jobs People Humanitarian Aids


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Socio-economical vulnerability
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INFORM Risk Index: Socio-economical vulnerability

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The main focus of humanitarian organizations is people. The Vulnerability dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters) addresses the predispositions of a population to be affected by hazard (economic, political and social characteristics of the community). This layer presents a social vulnerability index for each country. It encompasses the socio-economical dimensions of the countries' vulnerability: inequalities, aid dependency, and development & deprivation. The risk score ranges from 0-10, where 10 is the highest risk.


GOAL 10: Reduced inequalities


Other SDGs


Economy Financing Security Governance & Resilience Sustainable Growth & Jobs Gender & Inequality Politics People


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Uprooted people vulnerability
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INFORM Risk Index: Uprooted people vulnerability

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The main focus of humanitarian organizations is people. Refugees, internally displaced persons (IDPs) and returnees are among the most vulnerable people in a humanitarian crisis. As part of the Vulnerability dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters), the Uprooted people component accounts for those persons of concern. The risk score ranges from 0-10, where 10 is the highest risk.



Other SDGs


Security Conflicts, Violence, Criminal networks People Humanitarian Aids


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Vulnerability
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INFORM Risk Index: Vulnerability

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. The main focus of humanitarian organizations is people. The Vulnerability dimension of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters) addresses the predispositions of a population to be affected by hazard. It represents economic, political and social characteristics of the community that can be destabilized in case of a hazard event. This layer presents the vulnerability index for each country. The risk score ranges from 0-10, where 10 is the highest risk.


GOAL 10: Reduced inequalities


Other SDGs

GOAL 17: Partnerships to achieve the Goal, GOAL 1: No Poverty, GOAL 2: Zero Hunger, GOAL 3: Good Health and Well-being


Health Economy Security Disaster Risk Sustainable Growth & Jobs Gender & Inequality People Humanitarian Aids


Source: EC-JRC

Pluriannual layers
apps
INFORM Risk Index: Vulnerable groups
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INFORM Risk Index: Vulnerable groups

Understanding why and where humanitarian disasters are likely to occur is a fundamental step in saving lives and promoting sustainable development. Refugees, internally displaced persons and returnees are among the most vulnerable people in a humanitarian crisis. Considered as pandemics of low- and middle- income countries, HIV-AIDS, tuberculosis and malaria add to the vulnerability of their populations. As part of the INFORM Risk Index (global risk assessment for humanitarian crises and disasters), this layer presents a vulnerable groups categorisation for each country. It captures the risk related to social groups with limited access to social and health care systems. The risk score ranges from 0-10, where 10 is the highest risk.


GOAL 10: Reduced inequalities


Other SDGs


Health Security Disaster Risk Sustainable Growth & Jobs Gender & Inequality


Source: EC-JRC

Not Updated layers
apps
Installed capacities of hydropower plants
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Installed capacities of hydropower plants

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.


GOAL 07: Affordable and clean energy


Other SDGs

GOAL 9: Industry, Innovation and Infrastructure


Water & Freshwater Energy Energy Production Clean & Renewable Energy


Source: EC-JRC

Not Updated layers
apps
Irrigation (areas of concern)
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Irrigation (areas of concern)

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.


GOAL 15: Life on land


Other SDGs


Climate Change Land Degradation Desertification Natural Resources Water & Freshwater Food and Agriculture Water-Energy-Food Ecosystem


Source: EC-JRC

Annual layers
apps
Key Biodiversity Areas (KBAs)
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Key Biodiversity Areas (KBAs)

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.


GOAL 15: Life on land


Other SDGs

GOAL 14: Life Below Water


Natural Resources Biodiversity & Wildlife Protected Areas & Ecological Networks


Source: Birdlife

Not Updated layers
apps
Key Landscapes for Conservation
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Key Landscapes for Conservation

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.


GOAL 15: Life on land


Other SDGs


Natural Resources Biodiversity & Wildlife Protected Areas & Ecological Networks


Source: EC-JRC

Not Updated layers
apps
Land Cover Change (1995-2015)
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Land Cover Change (1995-2015)

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.


GOAL 15: Life on land


Other SDGs


eServices Natural Resources Biodiversity & Wildlife Forests Water & Freshwater Soil


Source: ESA

Not Updated layers
apps
Land Degradation
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Land Degradation

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.


GOAL 15: Life on land


Other SDGs

GOAL 5: Gender Equality, GOAL 7: Affordable and Clean Energy


Climate Change Land Degradation Desertification Deforestation Natural Resources Food and Agriculture Land Use in Agriculture Crop Health


Source: EC-JRC

Not Updated layers
apps
Land Fragmentation
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Land Fragmentation

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.


GOAL 15: Life on land


Other SDGs


Climate Change Land Degradation Desertification Deforestation Natural Resources Biodiversity & Wildlife


Source: EC-JRC

Not Updated layers
apps
Land Productivity Dynamics in Sahel
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Land Productivity Dynamics in Sahel

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.


GOAL 15: Life on land


Other SDGs


Climate Change Land Degradation Desertification Deforestation Natural Resources Food and Agriculture Land Use in Agriculture Crop Health


Source: EC-JRC

Not Updated layers
apps
Livestock density (areas of concern)
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Livestock density (areas of concern)

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.


GOAL 15: Life on land


Other SDGs


Food and Agriculture Land Use in Agriculture Food per Person Food Security Food Production Water-Energy-Food Ecosystem


Source: EC-JRC

Annual layers
apps
Living Standards Contribution to Overall Poverty Index (%)
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Living Standards Contribution to Overall Poverty Index (%)

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.


GOAL 03: Good health and well-being


Other SDGs

GOAL 10: Reduced Inequality


Economy Sustainable Growth & Jobs Politics People Demography


Source: University of Oxford

Not Updated layers
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Low-input agriculture (areas of concern)
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Low-input agriculture (areas of concern)

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.


GOAL 15: Life on land


Other SDGs


Food and Agriculture Land Use in Agriculture Yields Crop Health Food Production


Source: EC-JRC

Not Updated layers
apps
Malaria rates among children age 2 to 10
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Malaria rates among children age 2 to 10

Malaria, a life-threatening disease transmitted by mosquitoes, affects millions of people worldwide. This layer highlights malaria rates among children age 2 to 10 in Sub-Saharan Africa in 2015.


GOAL 03: Good health and well-being


Other SDGs


Health Public Health Diseases & Pandemic One Health Sustainable Growth & Jobs People Demography


Source: University of Oxford

Annual layers
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Mangroves

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.


GOAL 06: Clean water and sanitation


Other SDGs


Natural Resources Water & Freshwater


Source: Global Mangrove Watch

Annual layers
apps
Marine Ecoregion Protection as of January 2021
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Marine Ecoregion Protection as of January 2021

The Marine Ecoregions of the World is a global system to classify the oceans, helping to plan and prioritise marine conservation measures. How much are marine areas are protected at ecoregion level? For each African marine ecoregion, this map shows the percentage covered by protected areas.


GOAL 14: Life below water


Other SDGs


Natural Resources Biodiversity & Wildlife Protected Areas & Ecological Networks


Source: JRC-WWF

Not Updated layers
apps
Marine Global 200
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Marine Global 200

The Global 200 is the list of ecoregions identified by WWF, the global conservation organization, as priorities for conservation. According to WWF, an ecoregion is defined as a "relatively large unit of land or water containing a characteristic set of natural communities that share a large majority of their species dynamics, and environmental conditions". The WWF assigns a conservation status to each ecoregion in the Global 200: critical or endangered; vulnerable; and relatively stable or intact. Globally, over half of the ecoregions in the Global 200 are rated endangered.


GOAL 14: Life below water


Other SDGs


Natural Resources Biodiversity & Wildlife Marine Resources Protected Areas & Ecological Networks


Source: WWF

Monthly layers
apps
MODIS Chlorophylle-A monthly anomaly
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MODIS Chlorophylle-A monthly anomaly

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.


GOAL 13: Climate action


Other SDGs

GOAL 14: Life Below Water


Climate Change Natural Disasters Natural Resources Biodiversity & Wildlife Marine Resources


Source: EC-JRC

Monthly layers
apps
MODIS Sea Surface Temperature (SST) monthly anomaly
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MODIS Sea Surface Temperature (SST) monthly anomaly

Monitoring of sea surface temperature (SST) provides fundamental information on the global climate system and for the study of marine ecosystems. This layer compares the SST value of the last full month with the long-term mean SST. A positive anomaly (warm colours) means the monthly SST is warmer than the long-term average for that month; a negative anomaly (cool colours) means it is cooler than the average.


GOAL 13: Climate action


Other SDGs


Climate Change Climate Services Natural Disasters


Source: EC-JRC

Monthly layers
apps
Monthly Precipitation Anomaly from CHIRPS (mm)
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Monthly Precipitation Anomaly from CHIRPS (mm)

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.


GOAL 13: Climate action


Other SDGs


Climate Change Climate Services Natural Disasters


Source: EC-JRC

Not Updated layers
apps
National retail diesel prices [US $ cents /litre] 2012
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National retail diesel prices [US $ cents /litre] 2012

In the last decade, the global and African economies have been marked by a high volatility in the prices of diesel. Higher diesel prices impact not only the electricity generation costs but also the prices of all other goods that rely on diesel as an intermediate input. Food –on which poor people in low-income developing countries spend a disproportionately high share of their total household expenditures– is the most significantly impacted. This layer shows the national retail diesel prices [US $ cents /litre] in African countries in a context of high fuel prices. The 2012 prices were selected to represent high diesel prices. The 2012 layer (high fuel prices) can be compared with the 2016 layer (low fuel prices - https://africa-knowledge-platform.ec.europa.eu/dataset/dieselpid16), not only in terms of the actual retail prices, but also taking account of per capita incomes and truck revenues, also in terms of affordability.


GOAL 10: Reduced inequalities


Other SDGs

GOAL 7: Affordable and Clean Energy


Economy Energy Fossil Fuels


Source: EC-JRC

Not Updated layers
apps
National retail diesel prices [US $ cents /litre] 2016
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National retail diesel prices [US $ cents /litre] 2016

In the last decade, the global and African economies have been marked by a high volatility in the prices of diesel. Higher diesel prices impact not only the electricity generation costs but also the prices of all other goods that rely on diesel as an intermediate input. Food –on which poor people in low-income developing countries spend a disproportionately high share of their total household expenditures– is the most significantly impacted. This layer shows the national retail diesel prices [US $ cents /litre] in African countries in a context of low fuel prices. The February 2016 prices were selected to represent low diesel prices. During this time, one of the lowest price levels in the decade was registered, when the price of Brent fell to around US$29 per barrel. The 2016 layer (low fuel prices) can be compared with the 2012 layer (high fuel prices - https://africa-knowledge-platform.ec.europa.eu/dataset/dieselpid12), not only in terms of the actual retail prices, but also taking account of per capita incomes and truck revenues, also in terms of affordability.


GOAL 10: Reduced inequalities


Other SDGs

GOAL 7: Affordable and Clean Energy


Economy Energy Fossil Fuels


Source: EC-JRC

Annual layers
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Natural Areas

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. Derived from the Copernicus Global Land Cover, this map represents the distribution of areas where land cover is not heavily disturbed by man’s activities. In other words, it shows areas where natural ecosystems and their associated species are expected to be found.


GOAL 15: Life on land


Other SDGs

GOAL 11: Sustainable Cities and Communities, GOAL 13: Climate Action, GOAL 3: Good Health and Well-being


Natural Resources Biodiversity & Wildlife Forests


Source: EC-JRC

Annual layers
apps
Natural World Heritage sites
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Natural World Heritage sites

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.


GOAL 15: Life on land


Other SDGs

GOAL 14: Life Below Water


Natural Resources Biodiversity & Wildlife Protected Areas & Ecological Networks


Source: UNESCO/WCMC

Pluriannual layers
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Net Migration

Net migration is defined as the difference between the number of immigrants and the number of emigrants. Developing high spatial resolution data on net migration is a first step to analyse the relation between climate change, population distribution and related migration. This map shows the net migration for the 2010-2014 period as estimated by the European Commission's Knowledge Centre on Migration and Demography (KCMD) at a 25km resolution level, i.e. referring to areas of 25x25 km. It makes it possible to identify whether these areas experience migration losses (i.e. have negative net migration) or migration gains (i.e. positive net migration). The full dataset provides data on net migration for five-year time-steps between 1975 and 2015.


GOAL 10: Reduced inequalities


Other SDGs


Sustainable Growth & Jobs People Migration & Mobility Remittances


Source: EC-JRC

Annual layers
apps
Net official development assistance and official aid received
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Net official development assistance and official aid received

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.


GOAL 10: Reduced inequalities


Other SDGs


Economy Financing Sustainable Growth & Jobs Gender & Inequality Politics


Source: World Bank

Annual layers
apps
Oil Palm Plantations
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Oil Palm Plantations

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.


GOAL 15: Life on land


Other SDGs


Natural Resources Biodiversity & Wildlife Forests Food and Agriculture Food Production


Source: EC-JRC

apps
OpenStreetMap African Railways
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OpenStreetMap African Railways

African Railways extracted from OpenStreetMap on the 15th of October 2021.


GOAL 11: Sustainable cities and communities


Other SDGs

GOAL 10: Reduced Inequality


eServices Territorial Development Transport & Other Infrastructure Urban Development


Source: OpenStreetMap

apps
OpenStreetMap African Roads
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OpenStreetMap African Roads

African Roads extracted from OpenStreetMap on the 15th of October 2021.


GOAL 09: Industry, innovation and infrastructure


Other SDGs

GOAL 10: Reduced Inequality


eServices Territorial Development Transport & Other Infrastructure Urban Development


Source: OpenStreetMap

apps
OpenStreetMap African Waterways
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OpenStreetMap African Waterways

African Waterways extracted from OpenStreetMap on the 15th of October 2021.


GOAL 10: Reduced inequalities


Other SDGs

GOAL 10: Reduced Inequality


eServices Territorial Development Transport & Other Infrastructure Urban Development


Source: OpenStreetMap

Not Updated layers
apps
Population change (areas of concern)
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Population change (areas of concern)

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.


GOAL 15: Life on land


Other SDGs


People Population Growth Migration & Mobility Demography


Source: EC-JRC

Not Updated layers
apps
Population Density (areas of concern)
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Population Density (areas of concern)

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.


GOAL 15: Life on land


Other SDGs


Sustainable Growth & Jobs Urban Development People Demography


Source: EC-JRC

Annual layers
apps
Population natural increase
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Population natural increase

Developing high spatial resolution data on net migration is a first step to analyse the relation between climate change, population distribution and related migration. Net migration is defined as the difference between the number of immigrants and the number of emigrants. When data on in-migration and out-migration are not available, net migration is obtained by comparing population increase over a given period of time with natural increase (births minus deaths) over the same period. This map shows the natural increase for the 2010-2014 period as estimated by the European Commission's Knowledge Centre on Migration and Demography (KCMD) at a 25km resolution level, i.e. referring to areas of 25x25 km. The full dataset provides data on population natural increase for five-year time-steps between 1975 and 2015.


GOAL 10: Reduced inequalities


Other SDGs


Sustainable Growth & Jobs People Migration & Mobility


Source: EC-JRC

Annual layers
apps
Postharvest loss estimates for mais
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Postharvest loss estimates for mais

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.


GOAL 12: Responsible consumption and production


Other SDGs

GOAL 13: Climate Action


Food and Agriculture Food Security Food Waste


Source: EC-JRC

Annual layers
apps
Postharvest loss estimates for millet
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Postharvest loss estimates for millet

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.


GOAL 12: Responsible consumption and production


Other SDGs

GOAL 13: Climate Action


Food and Agriculture Food Security Food Waste


Source: EC-JRC

Annual layers
apps
Postharvest loss estimates for rice
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Postharvest loss estimates for rice

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.


GOAL 12: Responsible consumption and production


Other SDGs

GOAL 13: Climate Action


Food and Agriculture Food Security Food Waste


Source: EC-JRC

Annual layers
apps
Postharvest loss estimates for sorghum
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Postharvest loss estimates for sorghum

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.


GOAL 12: Responsible consumption and production


Other SDGs

GOAL 13: Climate Action


Food and Agriculture Food Security Food Waste


Source: EC-JRC

Annual layers
apps
Postharvest loss estimates for wheat
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Postharvest loss estimates for wheat

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.


GOAL 12: Responsible consumption and production


Other SDGs

GOAL 13: Climate Action


Food and Agriculture Food Security Food Waste


Source: EC-JRC

Not Updated layers
apps
Power plants (Generation Type)
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Power plants (Generation Type)

This dataset shows the African power plants by energy generation type. It includes thermal plants (coal, gas, oil, nuclear, biomass, waste, geothermal) and renewables (hydro, wind, solar). Each power plant is geolocated and entries contain information on plant capacity and generation type.


GOAL 07: Affordable and clean energy


Other SDGs

GOAL 9: Industry, Innovation and Infrastructure


Energy Energy Production Clean & Renewable Energy Fossil Fuels


Source: EC-JRC

Not Updated layers
apps
Power plants (Installed capacity)
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Power plants (Installed capacity)

This dataset shows the African power plants and their installed capacity in MegaWatt (MW). It includes thermal plants (coal, gas, oil, nuclear, biomass, waste, geothermal) and renewables (hydro, wind, solar). Each power plant is geolocated and entries contain information on plant capacity and generation.


GOAL 07: Affordable and clean energy


Other SDGs

GOAL 9: Industry, Innovation and Infrastructure


Energy Energy Production Fossil Fuels Clean & Renewable Energy


Source: EC-JRC

Monthly layers
apps
Protected Areas
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Protected Areas

Protected areas have long played a crucial role in protecting natural landscapes and wildlife, and many consider them to be one of the most effective tools in protecting biodiversity. The International Union for Conservation of Nature (IUCN) officially defines a protected area as ' a clearly defined geographical space, recognised, dedicated and managed, through legal or other effective means, to achieve the long term conservation of nature with associated ecosystem services and cultural values'. Protected areas also play a key role in preserving the benefits that nature brings to people, often referred to as 'ecosystem services'. They come in many shapes and sizes, ranging from strict nature reserves where only scientific research is permitted, to areas that allow natural resources to be used. The World Database on Protected Areas (WDPA) is the most comprehensive global database of marine and terrestrial protected areas.


GOAL 15: Life on land


Other SDGs

GOAL 14: Life Below Water


Natural Resources Biodiversity & Wildlife Protected Areas & Ecological Networks


Source: UNEP-WCMC/IUCN

Annual layers
close
Rangeland

By detecting areas where agricultural production deficits might occur, it is possible to prevent food security crises and anticipate response planning. To do this, we need accurate and reliable information on agricultural land cover. This layer shows the extent of rangeland in Africa. Each pixel represents the fraction of the area covered by rangeland (i.e. the percentage of the pixel with rangeland).


GOAL 02: Zero hunger


Other SDGs

GOAL 12: Responsible Consumption and Production, GOAL 2: Zero Hunger


Food and Agriculture Land Use in Agriculture Yields Food per Person Crop Health


Source: EC-JRC

Annual layers
apps
Raw Materials Trade - Export (USD)
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Raw Materials Trade - Export (USD)

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.


GOAL 09: Industry, innovation and infrastructure


Other SDGs

GOAL 12: Responsible Consumption and Production, GOAL 8: Decent Work and Economic Growth


Economy Sustainable Growth & Jobs Gender & Inequality Raw Materials


Source: EC-JRC

Annual layers
apps
Raw Materials Trade - Import (USD)
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Raw Materials Trade - Import (USD)

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 imported by each African country in 2017.


GOAL 09: Industry, innovation and infrastructure


Other SDGs

GOAL 12: Responsible Consumption and Production, GOAL 8: Decent Work and Economic Growth


Economy Sustainable Growth & Jobs Gender & Inequality Raw Materials


Source: EC-JRC

Annual layers
apps
Regional Economic Communities (RECs)
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Regional Economic Communities (RECs)

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).


GOAL 16: Peace, justice and strong institutions


Other SDGs


Economy Financing Sustainable Growth & Jobs Politics People


Source: EC-JRC

Not Updated layers
apps
Relative likelihood of hydro-political interactions
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Relative likelihood of hydro-political interactions

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.


GOAL 06: Clean water and sanitation


Other SDGs

GOAL 10: Reduced Inequality, GOAL 16: Peace and Justice Strong Institutions


Climate Change Sustainable Growth & Jobs Gender & Inequality Politics Natural Resources Water & Freshwater


Source: EC-JRC

Annual layers
apps
Remittance inflows (2020)
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Remittance inflows (2020)

International migration – the movement of people across international boundaries – has enormous implications for growth and poverty alleviation in both origin and destination countries. Remittances - the money sent by migrant workers to their country of origin - has an important role to play in this. This map based on World Bank data shows the annual remittance inflows (i.e. remittances received) per country, in USD. (Next update expected in April 2021)


GOAL 17: Partnerships for the goals


Other SDGs

GOAL 10: Reduced Inequality


Economy Sustainable Growth & Jobs Gender & Inequality Migration & Mobility Remittances


Source: World Bank

Annual layers
apps
Residential population
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Residential population

In an age of Development Agendas that call for universal inclusiveness of people, global population grids are essential to support analyses and inform policy-making in a wide range of fields, from environmental assessment to disaster risk analysis and reduction. This map combines the best-available population estimates (from CIESIN Gridded Population of the World) with the best-available assessment of the spatial extents of human settlements (inferred from Landsat satellite data). It depicts the distribution and density of population, expressed as the number of people per cell, at high spatial resolution (250m) for the year 2015.


GOAL 11: Sustainable cities and communities


Other SDGs


Sustainable Growth & Jobs Urban Development People Population Growth Migration & Mobility Energy


Source: EC-JRC

10-Days layers
apps
Risk of Drought Impact for Agriculture (RDrI-Agri)
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Risk of Drought Impact for Agriculture (RDrI-Agri)

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 Risk of Drought Impact for Agriculture (RDrI-Agri) is a categorized risk index, indicating the probability of having impacts from a drought, with particular focus on vegetation. Higher risk (in red) means that the areas affected will be the most likely to report impacts due to droughts. It is updated every ten days.


GOAL 15: Life on land


Other SDGs

GOAL 15: Life on Land


Real Time Climate Change Natural Disasters Land Degradation Desertification Natural Resources Water & Freshwater


Source: EC-JRC

Annual layers
apps
Sahel Boundaries
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Sahel Boundaries

The Sahel is an area that, over time, has had multiple definitions, climatic-botanical and political: its limits have been traced in very different ways. Even the usage of this name and its delimitation on maps has been openly questioned and contested. Our contribution proposes a cartography capable of mapping the incessant movement of conditions, limits and possibilities that characterize this strip between the Sahara and the humid Sudanese regions, rendering the areal definition of the Sahel visible and fluid at the same time. However, it is a question of rethinking the very foundation of cartography – what has been ‘taken for granted’ in the past – such as the common tools of cartographic representation, for example the concept of ‘isohyet’ to identify climatic areas or ‘boundaries’ to define political jurisdictions. Knowledge from fieldwork and expertise in the processing of satellite and geo-referenced data converge in this path of analysis and representation.


GOAL 13: Climate action


Other SDGs

GOAL 15: Life on Land


Climate Change Desertification Natural Resources


Source: University of Padova

Annual layers
close
Sahel Breath

The Sahel is an area that, over time, has had multiple definitions, climatic-botanical and political: its limits have been traced in very different ways. Even the usage of this name and its delimitation on maps has been openly questioned and contested. Our contribution proposes a cartography capable of mapping the incessant movement of conditions, limits and possibilities that characterize this strip between the Sahara and the humid Sudanese regions, rendering the areal definition of the Sahel visible and fluid at the same time. However, it is a question of rethinking the very foundation of cartography – what has been ‘taken for granted’ in the past – such as the common tools of cartographic representation, for example the concept of ‘isohyet’ to identify climatic areas or ‘boundaries’ to define political jurisdictions. Knowledge from fieldwork and expertise in the processing of satellite and geo-referenced data converge in this path of analysis and representation. The Sahel is a sub-Saharan area defined between the isohyetal lines of 150mm and 850 mm of rain per year. However, depending on the period, the season and the drought / rain conditions this area moves: hence the definition of the breath of the Sahel. This data represents the minimum and maximum extension of the Sahel area over the last 30 years.


GOAL 13: Climate action


Other SDGs

GOAL 15: Life on Land


Climate Change Desertification Natural Resources


Source: University of Padova

Near Real Time layers
apps
Sea Surface Temperature Anomaly (SSTA)
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Sea Surface Temperature Anomaly (SSTA)

Monitoring of sea surface temperature (SST) provides fundamental information on the global climate system and for the study of marine ecosystems. For example, it helps estimating heat stress conducive to coral bleaching, the process by which they expel the symbiotic algae living in their tissues and become white (bleached) and vulnerable. The NOAA Coral Reef Watch's daily global 5km satellite SST Anomaly (SSTA) compares the daily SST value with the long-term mean SST. A positive anomaly (+1.0 °C or more, warm colours) means the daily SST is warmer than the long-term average for that day; a negative anomaly (-1.0 °C or less, cold colours) means it is cooler than the average.


GOAL 13: Climate action


Other SDGs

GOAL 14: Life Below Water


Real Time Climate Change Climate Services


Source: National Oceanic and Atmospheric Administration (NOAA)

Near Real Time layers
apps
Sea Surface Temperature (SST)
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Sea Surface Temperature (SST)

Ocean temperature is related to ocean heat content (the energy absorbed by the ocean), an important topic in the study of global warming. Monitoring of sea surface temperature (SST) from earth-orbiting infrared radiometers has had a wide impact on oceanographic science. It provides fundamental information on the global climate system and for the study of marine ecosystems. For example, it helps estimating heat stress conducive to coral bleaching, the process by which they expel the symbiotic algae living in their tissues and become white (bleached) and vulnerable. The NOAA Coral Reef Watch Daily Global 5km Satellite Sea Surface Temperature product (a.k.a. CoralTemp) measures the night-time ocean temperature at the sea surface, calibrated to 0.2 meters depth.


GOAL 13: Climate action


Other SDGs

GOAL 14: Life Below Water


Real Time Climate Change Climate Services


Source: National Oceanic and Atmospheric Administration (NOAA)

Near Real Time layers
apps
Sea Surface Temperature Trend (SSTT)
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Sea Surface Temperature Trend (SSTT)

Monitoring of sea surface temperature (SST) provides fundamental information on the global climate system and for the study of marine ecosystems. For example, it helps estimating heat stress conducive to coral bleaching, the process by which they expel the symbiotic algae living in their tissues and become white (bleached) and vulnerable. The NOAA Coral Reef Watch's daily global 5km 7-day SST Trend product shows the SST trend for the most recent seven days. Pixels coloured in blue to purple follow a cooling trend while pixels coloured in yellow to red follow a warming trend. Pixels coloured in green have insignificant trends.


GOAL 13: Climate action


Other SDGs

GOAL 14: Life Below Water


Real Time Climate Change Climate Services


Source: National Oceanic and Atmospheric Administration (NOAA)

Not Updated layers
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Soil Map

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.


GOAL 02: Zero hunger


Other SDGs

GOAL 13: Climate Action, GOAL 15: Life on Land


Natural Resources Soil Land Use in Agriculture Crop Health


Source: EC-JRC

10-Days layers
apps
Soil Moisture Anomaly (SMA)
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Soil Moisture Anomaly (SMA)

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.


GOAL 15: Life on land


Other SDGs

GOAL 13: Climate Action


Real Time Climate Change Climate Services Natural Resources Soil Food and Agriculture


Source: EC-JRC

Not Updated layers
apps
Soil Organic Carbon
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Soil Organic Carbon

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.


GOAL 15: Life on land


Other SDGs


Natural Resources Biodiversity & Wildlife Forests Soil Ecosystem Services


Source: FAO

Not Updated layers
apps
Solar global horizontal irradiation
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Solar global horizontal irradiation

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).


GOAL 07: Affordable and clean energy


Other SDGs


Climate Change Climate Services Energy Energy Production Clean & Renewable Energy


Source: EC-JRC

Near Real Time layers
apps
Species occurrences reported to the GBIF
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Species occurrences reported to the GBIF

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


GOAL 15: Life on land


Other SDGs

GOAL 14: Life Below Water


Natural Resources Biodiversity & Wildlife


Source: GBIF

Annual layers
apps
Species Richness - Amphibians
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Species Richness - Amphibians

Africa’s extraordinary richness in biodiversity and ecosystem services comprises a strategic asset for sustainable development. Yet the decline and loss of biodiversity hampers the sustainable social and economic targets set by African countries. The International Union for the Conservation of Nature (IUCN)'s Red List of Threatened Species is the world’s most comprehensive information source on the global conservation status of animal, fungi and plant species. This map shows the richness in amphibian species based on the IUCN ranges (the species geographical distribution). Areas with a high species richness are shown in shades of red: more amphibian species potentially occur in these areas.


GOAL 15: Life on land


Other SDGs


Natural Resources Biodiversity & Wildlife


Source: IUCN

Annual layers
apps
Species Richness - Birds
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Species Richness - Birds

Africa’s extraordinary richness in biodiversity and ecosystem services comprises a strategic asset for sustainable development. Yet the decline and loss of biodiversity hampers the sustainable social and economic targets set by African countries. The International Union for the Conservation of Nature (IUCN)'s Red List of Threatened Species is the world’s most comprehensive information source on the global conservation status of animal, fungi and plant species. This map shows the richness in bird species based on the IUCN ranges (the species geographical distribution). Areas with a high species richness are shown in shades of red: more bird species potentially occur in these areas.


GOAL 15: Life on land


Other SDGs


Natural Resources Biodiversity & Wildlife


Source: IUCN

Annual layers
apps
Species Richness - Corals
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Species Richness - Corals

Africa’s extraordinary richness in biodiversity and ecosystem services comprises a strategic asset for sustainable development. Yet the decline and loss of biodiversity hampers the sustainable social and economic targets set by African countries. The International Union for the Conservation of Nature (IUCN)'s Red List of Threatened Species is the world’s most comprehensive information source on the global conservation status of animal, fungi and plant species. This map shows the richness in corals and ray species based on the IUCN ranges (the species geographical distribution). Areas with a high species richness are shown in shades of red: more corals and ray species potentially occur in these areas.


GOAL 14: Life below water


Other SDGs


Natural Resources Biodiversity & Wildlife


Source: IUCN

Annual layers
apps
Species Richness - Mammals
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Species Richness - Mammals

Africa’s extraordinary richness in biodiversity and ecosystem services comprises a strategic asset for sustainable development. Yet the decline and loss of biodiversity hampers the sustainable social and economic targets set by African countries. The International Union for the Conservation of Nature (IUCN)'s Red List of Threatened Species is the world’s most comprehensive information source on the global conservation status of animal, fungi and plant species. This map shows the richness in mammal species based on the IUCN ranges (the species geographical distribution). Areas with a high species richness are shown in shades of red: more mammal species potentially occur in these areas.


GOAL 15: Life on land


Other SDGs

GOAL 14: Life Below Water


Natural Resources Biodiversity & Wildlife


Source: IUCN

Annual layers
apps
Species Richness - Sharks and Rays
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Species Richness - Sharks and Rays

Africa’s extraordinary richness in biodiversity and ecosystem services comprises a strategic asset for sustainable development. Yet the decline and loss of biodiversity hampers the sustainable social and economic targets set by African countries. The International Union for the Conservation of Nature (IUCN)'s Red List of Threatened Species is the world’s most comprehensive information source on the global conservation status of animal, fungi and plant species. This map shows the richness in shark and ray species based on the IUCN ranges (the species geographical distribution). Areas with a high species richness are shown in shades of red: more shark and ray species potentially occur in these areas.


GOAL 14: Life below water


Other SDGs


Natural Resources Biodiversity & Wildlife


Source: IUCN

Monthly layers
apps
Standardized Precipitation Index (SPI-3)
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Standardized Precipitation Index (SPI-3)

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.


GOAL 13: Climate action


Other SDGs

GOAL 13: Climate Action


Real Time Climate Change Natural Resources Water & Freshwater


Source: EC-JRC

Not Updated layers
apps
Surficial Lithology
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Surficial Lithology

The Africa Surficial Lithology layer maps the geology of Africa into 20 classes based on the bedrock type and the distribution of unconsolidated surface material. It shows the distribution of the key geological features that affect the distribution of plants and ecosystems in Africa.


GOAL 15: Life on land


Other SDGs


Natural Resources Soil


Source: USGS-ESRI

Not Updated layers
apps
Terrestrial Ecoregions
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Terrestrial Ecoregions

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


GOAL 15: Life on land


Other SDGs


Natural Resources Biodiversity & Wildlife Protected Areas & Ecological Networks


Source: RESOLVE

apps
Terrestrial Ecosystems of Africa
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Terrestrial Ecosystems of Africa

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.


GOAL 15: Life on land


Other SDGs


Natural Resources Biodiversity & Wildlife Forests Protected Areas & Ecological Networks Water & Freshwater Ecosystem Services


Source: USGS-ESRI

Not Updated layers
apps
Terrestrial Global 200
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Terrestrial Global 200

The Global 200 is the list of ecoregions identified by WWF, the global conservation organization, as priorities for conservation. According to WWF, an ecoregion is defined as a "relatively large unit of land or water containing a characteristic set of natural communities that share a large majority of their species dynamics, and environmental conditions". The WWF assigns a conservation status to each ecoregion in the Global 200: critical or endangered; vulnerable; and relatively stable or intact. Globally, over half of the ecoregions in the Global 200 are rated endangered.


GOAL 15: Life on land


Other SDGs

GOAL 14: Life Below Water


Natural Resources Biodiversity & Wildlife Protected Areas & Ecological Networks


Source: WWF

Not Updated layers
apps
Terrestrial Priority Ecoregions
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Terrestrial Priority Ecoregions

A global strategy to conserve biodiversity must aim to protect representative examples of all of the world’s ecosystems, as well as those areas that contain exceptional concentrations of species and endemics. The WWF’s Global 200 project analysed global patterns of biodiversity to identify a set of the Earth's terrestrial, freshwater, and marine ecoregions that harbour exceptional biodiversity and are representative of its ecosystems. The process yielded 238 ecoregions (the Global 200) comprised of 142 terrestrial, 53 freshwater, and 43 marine priority ecoregions. The map shows their location on the African continent. Effective conservation in these ecoregions would help conserve the most outstanding and representative habitats for biodiversity on this planet.


GOAL 15: Life on land


Other SDGs


Natural Resources Biodiversity & Wildlife Protected Areas & Ecological Networks


Source: WWF

Not Updated layers
apps
Topographic Moisture Potential
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Topographic Moisture Potential

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.


GOAL 15: Life on land


Other SDGs


Climate Change Climate Services Natural Resources Soil


Source: USGS-ESRI

Not Updated layers
apps
Total annual energy production of hydropower plants
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Total annual energy production of hydropower plants

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.


GOAL 07: Affordable and clean energy


Other SDGs

GOAL 9: Industry, Innovation and Infrastructure


Water & Freshwater Energy Energy Production Clean & Renewable Energy


Source: EC-JRC

Not Updated layers
apps
Total annual gross water loss through evaporation from hydropower reservoirs
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Total annual gross water loss through evaporation from hydropower reservoirs

Dam-induced impoundment of water in hydropower reservoirs usually causes enlarged water surfaces compared to the waterbody extent prior to dam construction (with the exception of reservoirs constrained by geomorphologic features, i.e. canyons). The annual gross water loss from reservoirs is determined by the reservoir surface area, annual evaporation and a shared use allocation factor in the case of multi-purpose reservoirs. Consequently, an enlarged reservoir surface area leads to a significant increase of water losses, depending on location’s climate regime and shared uses of reservoir water. This map shows the country-aggregated yearly gross water loss (mcm/year) from hydropower reservoirs in Africa, as of 2016. Water losses from waterbody surfaces prior to dam construction are not considered in the estimates.


GOAL 07: Affordable and clean energy


Other SDGs

GOAL 9: Industry, Innovation and Infrastructure


Resource Scarcity Natural Resources Water & Freshwater Energy Energy Production Clean & Renewable Energy


Source: EC-JRC

Not Updated layers
apps
Total annual gross water loss vs total annual energy production of hydropower plants
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Total annual gross water loss vs total annual energy production of hydropower plants

In 2016, a total of 42 billion cubic meters of water was lost through evaporation in hydropower reservoirs in Africa. A huge amount compared to the 1.2 billion cubic meters lost from all the other fuel types combined. In the same period, hydropower accounted for 15% of Africa’s total energy production. The ratio of annual water loss (from a hydropower reservoir) versus energy production (of the associated hydropower plant) describes somehow the water efficiency of a hydropower site. The ratio varies from region to region and depend on the reservoir’s surface area and evaporation rate, and on the produced energy of the associated hydropower plant. A better performance (lower ratios, i.e. ratios below 1) in terms of reduced water losses through evaporation per produced energy unit can be achieved at hydropower sites characterized by decreased reservoir surfaces and increased energy production. In contrast, unfavourable, higher ratios occur with water losses higher than the associated hydropower energy production rates. This map shows the water loss / energy production ratio (mcm/GWh) for each hydropower generating country in Africa (country's total water loss versus country's total annual energy production of hydropower plants) for year 2016.


GOAL 07: Affordable and clean energy


Other SDGs

GOAL 9: Industry, Innovation and Infrastructure


Water & Freshwater Energy Energy Production Clean & Renewable Energy


Source: EC-JRC

Annual layers
close
Total Carbon

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).


GOAL 15: Life on land


Other SDGs

GOAL 13: Climate Action


Natural Resources Biodiversity & Wildlife Forests Ecosystem Services


Source: EC-JRC

Annual layers
apps
Total Fish Catch (tonnes)
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Total Fish Catch (tonnes)

The global capture fisheries has increased over the last 50 years as the consumption of seafood has doubled.This has increased pressure on fish stocks across the world. According to the State of World Fishery and Aquaculture 2020(FAO), the global capture fisheries production rose 14% from 1990 to 2018 and in 2018 it reached 96.4million tonnes. Here we show how much wild fish African countries caught in their EEZ in the last ten years (tonnes). In the attribute table you can find how much of the threatened marine fish species had be legally caught


GOAL 14: Life below water


Other SDGs


Natural Resources Biodiversity & Wildlife Marine Resources Protected Areas & Ecological Networks


Source: JRC

Not Updated layers
apps
Total installed capacity of hydropower plants
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Total installed capacity of hydropower plants

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 drought. This map shows the installed capacities (MW) of hydropower plants with an installed capacity above 5MW, aggregated for each hydropower generating country in Africa for year 2016. The selection of hydropower sites represents 95% of the total hydropower installed capacity in Africa.


GOAL 07: Affordable and clean energy


Other SDGs

GOAL 9: Industry, Innovation and Infrastructure


Water & Freshwater Energy Energy Production Clean & Renewable Energy


Source: EC-JRC

Not Updated layers
apps
Total surface area of hydropower reservoirs
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Total surface area of hydropower reservoirs

Higher energy demands in Africa has led to a wide expansion of the number of hydropower sites, mainly between the 1960s and 980s. The construction of dams causes impoundments of rivers and reservoirs in the region of dam influence with higher evaporation and water temperatures due to increased water surfaces. This map shows the aggregated surfaces (sqkm) of reservoirs subject to hydropower production per country, as of 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.


GOAL 07: Affordable and clean energy


Other SDGs

GOAL 9: Industry, Innovation and Infrastructure


Water & Freshwater Energy Energy Production Clean & Renewable Energy


Source: EC-JRC

Not Updated layers
apps
Travel time to major cities
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Travel time to major cities

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.


GOAL 11: Sustainable cities and communities


Other SDGs

GOAL 13: Climate Action, GOAL 7: Affordable and Clean Energy


Economy Tourism Climate Change Pollution Sustainable Growth & Jobs Territorial Development Trade & Connectivity People Energy


Source: EC-JRC

Not Updated layers
apps
Tree loss (areas of concern)
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Tree loss (areas of concern)

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.


GOAL 15: Life on land


Other SDGs


Climate Change Land Degradation Natural Resources Forests


Source: EC-JRC

Annual layers
apps
Tropical Moist Forests - Deforestation year map
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Tropical Moist Forests - Deforestation year map

Tropical moist forests have a huge environmental value. They play an important role in biodiversity conservation, terrestrial carbon cycle, hydrological regimes, indigenous population subsistence and human health (1-5). They are increasingly recognized as an essential element of any strategy to mitigate climate change. Deforestation, and degradation compromise the functioning of tropical forests as an ecosystem, lead to biodiversity loss and reduced carbon storage capacity. Deforestation and fragmentation are increasing the risk of virus disease outbreaks. This map shows where deforestation occurred in the last three decades (between 1982 and 2020) and the year when the forest cover has been deforested for the first time (followed or not by a regrowth).


GOAL 15: Life on land


Other SDGs


Natural Resources Forests


Source: EC-JRC

Annual layers
apps
Tropical Moist Forests - Degradation year map
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Tropical Moist Forests - Degradation year map

Tropical moist forests have a huge environmental value. They play an important role in biodiversity conservation, terrestrial carbon cycle, hydrological regimes, indigenous population subsistence and human health (1-5). They are increasingly recognized as an essential element of any strategy to mitigate climate change. Deforestation, and degradation compromise the functioning of tropical forests as an ecosystem, lead to biodiversity loss and reduced carbon storage capacity. Deforestation and fragmentation are increasing the risk of virus disease outbreaks. This map shows where degradation occurred in the last three decades (between 1982 and 2020) and the year when the forest has been degraded for the first time (and remained degraded up to 2020).


GOAL 15: Life on land


Other SDGs


Climate Change Land Degradation Natural Resources Forests


Source: EC-JRC

Annual layers
apps
Tropical Moist Forests - Transition map
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Tropical Moist Forests - Transition map

Tropical moist forests have a huge environmental value. They play an important role in biodiversity conservation, terrestrial carbon cycle, hydrological regimes, indigenous population subsistence and human health (1-5). They are increasingly recognized as an essential element of any strategy to mitigate climate change. Accurate characterization of the tropical moist forests changes is needed to support conservation policies and to better quantify their contribution to global carbon fluxes. The transition map captures the dynamics of changes in tropical moist forests between the initial observation period (1990) and the end of the year 2020.


GOAL 15: Life on land


Other SDGs


Natural Resources Forests


Source: EC-JRC

Annual layers
apps
Tropical Moist Forests - Undisturbed tropical moist forest
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Tropical Moist Forests - Undisturbed tropical moist forest

Tropical moist forests have a huge environmental value. They play an important role in biodiversity conservation, terrestrial carbon cycle, hydrological regimes, indigenous population subsistence and human health (1-5). They are increasingly recognized as an essential element of any strategy to mitigate climate change. Accurate characterization of the tropical moist forests changes is needed to support conservation policies and to better quantify their contribution to global carbon fluxes. This map shows the coverage of undisturbed tropical moist forests remaining at the end of the year 2019.


GOAL 15: Life on land


Other SDGs


Natural Resources Forests


Source: EC-JRC

Not Updated layers
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Urban Areas

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.


GOAL 11: Sustainable cities and communities


Other SDGs


Climate Change Pollution Sustainable Growth & Jobs Urban Development People Population Growth


Source: Africapolis

Annual layers
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Water Occurrence (1984-2020)
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Water Occurrence (1984-2020)

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.


GOAL 06: Clean water and sanitation


Other SDGs


Natural Resources Water & Freshwater Energy


Source: EC-JRC

Annual layers
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Water Quality – Trophic State
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Water Quality – Trophic State

Freshwater, in sufficient quantity and quality, is essential for all aspects of life and fundamental to sustainable development. Yet water-related ecosystems are threatened by human activities. Eutrophication is a common threat: the excessive growth of algae resulting in oxygen depletion. It can be occasional or frequent. To monitor this process, one can use the trophic state index. It refers to the degree at which organic matter accumulates in the lake and may be used to infer its particular state, or quality. A five year baseline (2006- 2010), per lake, has been produced. The maps depicts mean deviations (low to extreme) of trophic state in recent years (2017-2019) compared to the individual lake baseline measurements.


GOAL 06: Clean water and sanitation


Other SDGs

GOAL 6: Clean Water and Sanitation


Natural Resources Water & Freshwater


Source: EC-JRC

Annual layers
apps
Water Quality – Turbidity
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Water Quality – Turbidity

Freshwater, in sufficient quantity and quality, is essential for all aspects of life and fundamental to sustainable development. Turbidity is an indicator of water clarity, quantifying the haziness of the water and acting as an indicator of underwater light availability. Light penetration may or may not be sufficient to support the growth of aquatic plants and adversely affect fish and shellfish populations. This parameter may be used to infer a particular state, or quality, of a freshwater body (lake, wetland or river). Mangroves, for instance, are known to reduce the turbidity of waters. A five year baseline (2006-2010), per lake, has been produced. The maps depicts mean deviations (classified from low to extreme) of turbidity in recent years (2017-2019) compared to the individual lake baseline measurements.


GOAL 06: Clean water and sanitation


Other SDGs


Natural Resources Water & Freshwater


Source: EC-JRC

Not Updated layers
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Water stress (areas of concern)
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Water stress (areas of concern)

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.


GOAL 15: Life on land


Other SDGs


Health Climate Change Climate Services Disaster Risk Resource Scarcity Desertification Natural Resources Water & Freshwater


Source: EC-JRC

Not Updated layers
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Water Transitions (1984-2018)
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Water Transitions (1984-2018)

Freshwater, in sufficient quantity and quality, is essential for all aspects of life and fundamental to sustainable development. Yet water-related ecosystems are threatened by human activities (flow alteration; loss of connectivity; pollution; habitat degradation and loss; overexploitation of species). Tracking changes in water-related ecosystems enables decision makers to determine the extent of change over time, understand the threats and implement appropriate mitigation measures. The water transition map shows the total change in the annual extent of permanent and seasonal surface water area for lakes and rivers between 1984 and 2018. It includes surfaces of: permanent water (i.e. area where water is present 12 months per year), new permanent water (i.e. conversion of land into permanent water), lost permanent water (i.e. conversion of permanent water into land), seasonal water (i.e. area where water is present less than 12 months per year), new seasonal water (i.e. conversion of land to seasonal water), lost seasonal water (i.e. conversion of seasonal water to land), seasonal to permanent (i.e. conversion of seasonal water into permanent water) and permanent to seasonal (i.e. conversion of permanent water into seasonal water).


GOAL 06: Clean water and sanitation


Other SDGs


Natural Resources Water & Freshwater


Source: EC-JRC

Not Updated layers
apps
Water Transitions in Reservoir (1984-2018)
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Water Transitions in Reservoir (1984-2018)

Freshwater, in sufficient quantity and quality, is essential for all aspects of life and fundamental to sustainable development. Yet water-related ecosystems are threatened by human activities (flow alteration; loss of connectivity; pollution; habitat degradation and loss; overexploitation of species). Tracking changes in water-related ecosystems enables decision makers to determine the extent of change over time, understand the threats and implement appropriate mitigation measures. Reservoirs are defined as artificial, human-made water bodies. The water transition in reservoir map shows the total change in annual extent of reservoir surface water area between 1984 and 2018. It includes surfaces of: permanent water (i.e. area where water is present 12 months per year), new permanent water (i.e. conversion of land into permanent water), lost permanent water (i.e. conversion of permanent water into land), seasonal water (i.e. area where water is present less than 12 months per year), new seasonal water (i.e. conversion of land to seasonal water), lost seasonal water (i.e. conversion of seasonal water to land), seasonal to permanent (i.e. conversion of seasonal water into permanent water) and permanent to seasonal (i.e. conversion of permanent water into seasonal water).


GOAL 06: Clean water and sanitation


Other SDGs


Natural Resources Water & Freshwater


Source: EC-JRC

Not Updated layers
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Wetlands

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.


GOAL 06: Clean water and sanitation


Other SDGs


Natural Resources Water & Freshwater


Source: DHI-GRAS

Not Updated layers
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Wildlife watching species richness index
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Wildlife watching species richness index

Where are the best places to spot the most requested wildlife-watching species? This grid layer presents a richness index of top wildlife watching species/groups, including rhinos, elephants, lions, leopards, buffalos, giraffes, lowland and mountain gorillas, chimpanzees, bonobos, sifakas, ringtails, aye-aye, mouse lemurs and colobus.


GOAL 15: Life on land


Other SDGs


Economy Tourism Sustainable Growth & Jobs Natural Resources Biodiversity & Wildlife


Source: EC-JRC

apps
Wind power (W/m2)
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Wind power (W/m2)

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.


GOAL 07: Affordable and clean energy


Other SDGs


Climate Change Natural Resources Energy Clean & Renewable Energy


Source: Technical University of Denmark (DTU) and World Bank

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Working poor

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.


GOAL 01: No poverty


Other SDGs


Sustainable Growth & Jobs Gender & Inequality Politics People


Source: ILOSTAT

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