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The Global Flood Monitoring (GFM) system of the Copernicus EmergencyManagement Service (CEMS) addresses the challenges and impacts that are causedby flooding. The GFM system provides global, near-real time flood extent masksfor each newly acquired Sentinel-1 Interferometric Wide Swath SyntheticAperture Radar (SAR) image, as well as flood information from the wholeSentinel-1 archive from 2015 on. The GFM flood extent is an ensemble productbased on a combination of three independently developed flood mappingalgorithms that individually derive the flood information from Sentinel-1 data.Each flood algorithm also provides classification uncertainty information thatis aggregated into the GFM ensemble likelihood product as the mean of theindividual classification likelihoods. As the flood detection algorithms deriveuncertainty information with different methods, the value range of the threeinput likelihoods must be harmonized to a range from low [0] to high [100]flood likelihood. The ensemble likelihood is evaluated on two test sites inMyanmar and Somalia, showcasing the performance during an actual flood eventand an area with challenging conditions for SAR-based flood detection. TheMyanmar use case demonstrates the robustness if flood detections in theensemble step disagree and how that information is communicated to theend-user. The Somalia use case demonstrates a setting where misclassificationsare likely, how the ensemble process mitigates false detections and how theflood likelihoods can be interpreted to use such results with adequate caution.

Estimating ensemble likelihoods for the Sentinel-1 based Global Flood Monitoring product of the Copernicus Emergency Management Service