A prototype system for flood monitoring based on flood forecast combined with COSMO-SkyMed and Sentinel-1 data

The use of synthetic aperture radar (SAR) data is presently well established in operational services for flood management. However, some events might be missed because of the limited area that can be observed through a SAR image and the need of programming SAR acquisitions in advance. To tackle these problems, it is possible to setup a system that is able to trigger the SAR acquisitions based on flood forecasts and to take advantage of the various satellite SAR sensors that are presently operating. On behalf of the Italian Civil Protection Department (DPC), a prototype of this kind of system has been setup and preliminary tested, using COSMO-SkyMed (CSK) and Sentinel-1 (S-1) data, to monitor the Po River (Northern Italy) flood occurred in November 2014. This paper presents the prototype system and describes in detail the near real-time flood mapping algorithm implemented in the system. The algorithm was previously developed to classify CSK images, and is modified here in order to be applied to S-1 data too. The major outcomes of the monitoring of the Po River flood are also analyzed in this paper, highlighting the importance of the in advance programming of the radar acquisitions. Results demonstrate the reliability of the flood predictions provided by the model and the accuracy of the flood mapping algorithm. It is also shown that, when CSK and S-1 data are simultaneously acquired, their joint use allows for an interpretation of some ambiguous radar signatures in agricultural areas.