First insights on the potential of Sentinel-1 for landslides detection. Issue 6 (1st November 2016) - Barra, Anna; Monserrat, Oriol; Mazzanti, Paolo; Esposito, Carlo; Crosetto, Michele; Scarascia Mugnozza, Gabriele
ABSTRACT: This paper illustrates the potential of Sentinel-1 for landslide detection, mapping and characterization with the aim of updating inventory maps and monitoring landslide activity. The study area is located in Molise, one of the smallest regions of Italy, where landslide processes are frequent. The results achieved by integrating Differential Synthetic Aperture Radar Interferometry (DInSAR) deformation maps and time series, and Geographical Information System (GIS) multilayer analysis (optical, geological, geomorphological, etc.) are shown. The adopted methodology is described followed by an analysis of future perspectives. Sixty-two landslides have been detected, thus allowing the updating of pre-existing landslide inventory maps. The results of our ongoing research show that Sentinel-1 might represent a significant improvement in terms of exploitation of SAR data for landslide mapping and monitoring due to both the shorter revisit time (up to 6 days in the close future) and the wavelength used, which determine an higher coherence compared to other SAR sensors.