State of activity classification of deep-seated gravitational slope deformation at regional scale based on Sentinel-1 data

Deep-seated gravitational slope deformations (DsGSDs) are very slow slope instabilities that can have a long-term impact on anthropic structures and infrastructures. The characterization of their state of activity is, therefore, essential to evaluate it. By employing Differential Interferometry Synthetic Aperture Radar (DInSAR) techniques, a dedicated procedure, to explore the behavior and define the state of activity of 279 DsGSDs, inventoried in the regional landslide inventory of the Aosta Valley Region (Western Italian Alps), has been implemented. The proposed methodology consists of several steps. Firstly, Sentinel-1 data have been processed through a two-step, advanced, DInSAR processing scheme to detect and identify Persistent Scatterers (PSs). The velocity values measured along the radar Line of Sight (LOS) have been projected along the steepest slope. Subsequently, an analysis of PSs within DsGSD polygons, devoted to the assessment of Sentinel-1 data coverage, has been carried out; in particular, considering the PS abundance, computing voids in point distributions and assessing PS clustering to identify cases with adequate point number and distribution for a suitable definition of the state of activity. Finally, a spatial analysis based on cluster and outlier identification has been carried out to characterize the moving phenomena and their degree of variability in deformation rates. Overall, the implemented methodology provides a valid instrument to remotely define the state of activity of these huge phenomena, often wrongly underestimated or neglected in risk management, useful for a better definition of DsGSD impacts on anthropic elements for a proper land use planning.