 This research develops a landslide susceptibility index, LSI, using a GIS-based interdisciplinary approach to map areas prone to trigger slope instability phenomena in the Sorrentina Peninsula, Italy. The LSI combines five weighted and ranked susceptibility parameters, including remote sensing, geolithology, and morphometry data. In SAR technique was used to obtain ground displacement time series and relative mean ground velocity maps, while airborne photo-interpretation identified geomorphological peculiarities connected to potential slope instability. The resulting LSI map classifies the two municipalities with high spatial resolution, 2M, according to five classes of instability, with 85% prediction accuracy for historical landslides. This article was authored by Claudia Spinetti, Marina Bissen, Cristiano Tolomey, and others.