Overall Red Earthquake alert in Afghanistan on 21 Jun 2022 20:54 UTC

GDACS is a cooperation framework between the United Nations, the European Commission and disaster managers worldwide to improve alerts, information exchange and coordination in the first phase after major sudden-onset disasters.

M 5.9 in Afghanistan on 21 Jun 2022 20:54 UTC

Automatic definition of the Areas of Interest (AoIs)

Satellite mapping is widely used by humanitarian organisations and disaster managers to rapidly and remotely assess the impact of disasters. Huge effort has been focused over the years to improve the timely and reliability of the satellite-based impact assessments. This new section of the GDACS disaster reports has the scope to support disaster managers to rapidly assess the impact of global disasters with an automatic procedure to detect the most affected areas to target the prompt acquisition of satellite images (Areas of Interest - AoIs).

For Earthquakes the challenge is to estimate in few minutes the possible areas of major damage based on the estimated seismic intensity (eg. Shakemaps). For Tropical Cyclones, the challenge is the pre-tasking of the images, to shorten the time between acquisition of the images and analysis.

The "hazard data" (eg. Shakemaps for earthquakes or wind, precipitation and storm surge for Tropical Cyclones) are automatically combined with the Global Human Settlement Layer (GHSL) to identify the most exposed areas. The use of this series of AoIs allows to focus the acquisitions on the urbanised areas, allowing a comprehensive impact assessment at settlement level.

For each AoI defined by this new system, the exposed population is provided based on the population dataset of GHSL and the various hazards. The following data sources are adopted for the "hazards":

Earthquakes: shakemap intensity produced by USGS.
Tropical Cyclones: definition of the AOIs for the various hazards (winds, rainfall and storm surge) using as input different atmospheric data (NOAA-HWRF, NOAA-GFS, ECMWF-HRES, NASA-GPM). EC-JRC is also working on two additional layers: maximum (Data type: Maximum All) and the combination of the 3 hazards (Data type: Combined All).

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