Information Extraction From Remote Sensing Images for Flood Monitoring and Damage Evaluation

Satellite remote sensing missions devoted to Earth observation (EO) currently offer a unique capability to monitor the evolution of the Earth's surface by providing temporally repetitive views at the desired (global, regional, or local) spatial scale. This wealth of remote sensing data conveys a huge potential for preventing, monitoring, and managing natural or man-made disasters. Specifically focusing on flood risk, a successful exploitation of this potential requires not only accurate and reliable image-analysis methods to extract the desired thematic information, but also the ability to combine this information with physically based models of the observed processes. Therefore, a multidisciplinary approach combining remote sensing with geophysical sciences, such as, in this case, hydrometeorology, is fundamental. This combination of expertise allows, in particular, satellite data to be exploited within the different phases of flood risk reduction: risk assessment, prevention, mitigation, monitoring, and management. In this paper, we investigate the key issues involved in the exploitation of satellite data with special focus on the phases of the emergency and post-disaster damage assessment. To this end, the challenges and the methodological approaches involved in the multidisciplinary combination of image analysis and hydrometeorology are discussed with the purpose of guiding and optimizing the process of information extraction from satellite data according to the requirements of civil protection from floods. Experimental examples of a few relevant case studies are also presented.