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Flood mapping and estimation of the maximum water depth are essential elements for the first damage evaluation, civil protection intervention planning and detection of areas where remediation is needed. In this work, we present and discuss a methodology for mapping and quantifying flood severity over floodplains. The proposed methodology considers a multiscale and multisensor approach using free or low-cost data and sensors. We applied this method to the November 2016 Piedmont (northwestern Italy) flood.We first mapped the flooded areas at the basin scale using free satellite data from low- to mediumhigh- resolution from both the SAR (Sentinel-1, COSMOSkymed) and multispectral sensors (MODIS, Sentinel-2). Using very- and ultra-high-resolution images from the lowcost aerial platform and remotely piloted aerial system, we refined the flooded zone and detected the most damaged sector. The presented method considers both urbanised and nonurbanised areas. Nadiral images have several limitations, in particular in urbanised areas, where the use of terrestrial images solved this limitation. Very- and ultra-high-resolution images were processed with structure from motion (SfM) for the realisation of 3-D models. These data, combined with an available digital terrain model, allowed us to obtain maps of the flooded area, maximum high water area and damaged infrastructures. [ABSTRACT FROM AUTHOR]

Flood mapping and estimation of maximum water depth are essential elements for a first damages evaluation, civil protection interventions planning and detection of areas where remedial are more needed. In this work, we present and discuss a methodology for mapping and quantifying flood severity over plain areas. The proposed methodology considers a multiscale and multi-sensor approach using free or low-cost data/sensors. We applied this method to November 2016 Piemonte (NW Italy) flood. We first mapped flooded areas at basin scale using free satellite data from low to medium-high resolution using both SAR (Sentinel-1, Cosmo-Skymed) and multispectral sensors (MODIS, Sentinel-2). Using very- and ultra- high-resolution images from the low-cost aerial platform and Remotely Piloted Aerial System, we refined the flooded zone, and we detected the most damaged sector. The presented method considers both urbanized and not urbanized areas. Nadiral images have several limitations in particular in urbanized areas, where the use of terrestrial images solved this limitation. Very- and ultra-high resolution images have been processed with Structure from Motion (SfM) for the realization of 3-D models. These data, combined with available digital elevation model, allowed us to obtain maps of flooded area, maximum water high and damaged infrastructures. [ABSTRACT FROM AUTHOR]