Combining satellite data for an effective and continuous mapping of floods

Satellite data have been widely used to detect and monitor flooding events, especially in rural areas. The integration of data acquired by different sensors, operating at different wavelengths within the electromagnetic spectrum and using different technologies, can further improve the capabilities of providing more frequent information, which is crucial for the effective management of this dynamic phenomenon. In any case, suitable and robust methodologies must be used to analyze these data to reduce the number of false alarms. In this study, we present an approach based on a combination of microwave data acquired by the C-band SAR aboard Sentinel 1 satellites with optical data collected by the MultiSpectral Instrument onboard Sentinel 2 platforms. The methodology was developed within the Google Earth Engine (GEE) cloud computing system, where all historical data are available and accessible, as well as other datasets/tools useful for its development. The recent flooding event that occurred in central Europe in September 2024 was analyzed, and the results were compared with flood maps made available by the Copernicus Emergency Monitoring Service system to assess their accuracy, and satisfactory results were obtained.