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

1. Constraints on Government Powers
2. Absence of Corruption
3. Open Government
4. Fundamental Rights
5. Order and Security
6. Regulatory Enforcement
7. Civil Justice
8. Criminal Justice

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

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

The 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.

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

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.

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

This layer provides the Effective Leaf Area Index (LAIe), a critical parameter for modeling evapotranspiration and carbon fluxes between the biosphere and the atmosphere. Monitoring the distribution and seasonal evolution of LAI is essential for assessing vegetation health and ecosystem dynamics across Africa.

The Effective Leaf Area Index is a quantitative measure of the amount of live green leaf material present per unit ground surface. Unlike "True LAI," which represents the total physical leaf area, the Effective LAI is derived from canopy gap fraction measurements and assumes a random distribution of foliage. It is a non-dimensional quantity, typically expressed in units of m²/m².

This dataset is widely utilized in agro-meteorology, biogeochemical modeling, and General Circulation Models (GCMs) to parameterize vegetation cover and its complex interactions with the atmosphere.

This layer is part of the Earth Land Information System (ELIS).

This layer presents the Effective Leaf Area Index (LAIe) Anomalies, representing the deviation of current vegetation density from the historical average. Monitoring the change of LAI is essential for assessing the evolution of the vegetation over Africa.

LAI anomalies are calculated relative to the average values between 2003 and 2010. The dataset captures LAI anomalies every 10 days, reflecting the high variability and rapid changes in African vegetation cover. Increases in temperature and precipitation deficits are the primary drivers for negative anomalies (reduced foliage density). Beyond climatic factors, human activities or animal grazing may also locally impact the state and density of leaves.

This layer is part of the a href="https://fapar.jrc.ec.europa.eu/_www/index.php">Earth Land Information System (ELIS).

The Global Gridded Relative Deprivation Index (GRDI) characterizes the relative levels of multidimensional deprivation and poverty, where a value of 100 represents the highest level of deprivation and a value of 0 the lowest. GRDI is built from sociodemographic and satellite data inputs that were spatially harmonized, indexed, and weighted into six main components to produce the final GRDI layer.

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

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

1. The Composite Index

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

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

2. Dimension: Vulnerability

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

Sub-Index: Socio-Economic Vulnerability

An aggregate index covering three main components of systemic instability:

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

Sub-Index: Vulnerable Groups

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

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

3. Dimension: Lack of Coping Capacity

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

Sub-Index: Institutional Capacity

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

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

Sub-Index: Infrastructure

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

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

The International Wealth Index is an asset-based wealth index that runs from 0 (no assets) to 100 (all assets) and is comparable across place and time. The lower the level of the Index, the greater the potential of electricity access to reduce poverty and foster development.

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.

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.

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.

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

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

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

Key Indicators & Methodology

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

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

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