Landslide susceptibility mapping with fuzzy methodology

This work proposes an experimental methodology for the characterization of the susceptibility to landslides in the Reggio Calabria area through the combination of remote sensing, GIS systems and soft computing. In particular, we created, a map of the susceptibility to landslides in GIS environment using a neural network and a fuzzy methodology to produce an infrastructure attention level divided into five categories (levels) of risk. Subsequently, starting from this map, we identified the areas of the road s network most exposed to landslide risk also using remote sensing techniques (classification and segmentation techniques) overlapped on the open street map. This system provides us the level of attention that affects the transport infrastructure investigated (a higher level of attention corresponds to a higher level of landslide risk).