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The Cosmo-SkyMed mission offers a unique opportunity to obtain radar images useful for flood mapping, being characterized by high revisit time, thanks to the four satellites that form its constellation. In the context of a study aiming at evaluating the usefulness of Earth Observation data for managing flood events, particularly focused on Cosmo-SkyMed, an algorithm to map flooded areas from synthetic aperture radar imagery has been developed. It is based on methods developed in previous studies and aims at combining an image segmentation technique based on mathematical morphology and the fuzzy logic that allows us to label the identified objects as flooded or non-flooded. The default parameters of the fuzzy classifier are derived from the outputs of well-established electromagnetic scattering models.