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Climate Change Resilience

Title: Africa Regional Centres of Excellence - ArcX: Climate Change Resilience.

Main Objective: Strengthen the climate change and disaster resilience in Sub-Saharan Africa, by improving scientific and technological capacities of the Regional Centers of Excellence, their co-ordination and capacity to contribute to policy and decision making.

Starting Year: 2026
Implementation Duration: 48 Months

Areas of Impact: Still to be defined

Target Groups: Still to be defined

ArcX Partners: Still to be defined

Component Coordinator: European Centre for Medium-Range Weather Forecasts (ECMWF) - pending contract signature.

Scientific and Technical Support from EC - DG JRC: JRC Unit D6 (Nature Conservation and Observations); JRC Unit E1 (Disaster Risk Management).


Available Resources
Displaying 16 - 30 of 93
The GHS Settlement Model layers (GHS-SMOD) GHS-SMOD_GLOBE_R2023A delineate and classify settlement typologies via a logic of cell clusters population size, population and built-up area densities as de...
The GHS Settlement Model layers (GHS-SMOD) GHS-SMOD_GLOBE_R2023A delineate and classify settlement typologies via a logic of cell clusters population size, population and built-up area densities as de...
The GHS Settlement Model layers (GHS-SMOD) GHS-SMOD_GLOBE_R2023A delineate and classify settlement typologies via a logic of cell clusters population size, population and built-up area densities as de...
The GHS Settlement Model layers (GHS-SMOD) GHS-SMOD_GLOBE_R2023A delineate and classify settlement typologies via a logic of cell clusters population size, population and built-up area densities as de...
The GHS Settlement Model layers (GHS-SMOD) GHS-SMOD_GLOBE_R2023A delineate and classify settlement typologies via a logic of cell clusters population size, population and built-up area densities as de...
The GHS Settlement Model layers (GHS-SMOD) GHS-SMOD_GLOBE_R2023A delineate and classify settlement typologies via a logic of cell clusters population size, population and built-up area densities as de...
The GHS Settlement Model layers (GHS-SMOD) GHS-SMOD_GLOBE_R2023A delineate and classify settlement typologies via a logic of cell clusters population size, population and built-up area densities as de...
The GHS Settlement Model layers (GHS-SMOD) GHS-SMOD_GLOBE_R2023A delineate and classify settlement typologies via a logic of cell clusters population size, population and built-up area densities as de...
The GHS Settlement Model layers (GHS-SMOD) GHS-SMOD_GLOBE_R2023A delineate and classify settlement typologies via a logic of cell clusters population size, population and built-up area densities as de...
The GHS Settlement Model layers (GHS-SMOD) GHS-SMOD_GLOBE_R2023A delineate and classify settlement typologies via a logic of cell clusters population size, population and built-up area densities as de...
The GHS Settlement Model layers (GHS-SMOD) GHS-SMOD_GLOBE_R2023A delineate and classify settlement typologies via a logic of cell clusters population size, population and built-up area densities as de...
The GHS Settlement Model layers (GHS-SMOD) GHS-SMOD_GLOBE_R2023A delineate and classify settlement typologies via a logic of cell clusters population size, population and built-up area densities as de...
This GHS-POP spatial raster product (GHS-POP_GLOBE_R2023) depicts the distribution of human population, expressed as the number of people per cell. Residential population estimates at 5 years interval...
This GHS-POP spatial raster product (GHS-POP_GLOBE_R2023) depicts the distribution of human population, expressed as the number of people per cell. Residential population estimates at 5 years interval...
This GHS-POP spatial raster product (GHS-POP_GLOBE_R2023) depicts the distribution of human population, expressed as the number of people per cell. Residential population estimates at 5 years interval...