Reconstruction of landslide motion by a synergy between the SNAPPING and the GDM-OPT-SLIDE processing services of the GEP

Remote sensing techniques represent a valuable tool for monitoring areas affected by landslides. In comparison with ground-based monitoring techniques, they are characterised by relatively lower costs, especially in remote areas, and guarantee a temporal availability of data even before the start of monitoring. Both optical and Synthetic Aperture Radar (SAR) data are exploited for this cause and their results are widely validated in the literature. This study aims to develop a service prototype that exploits the outputs of different remote sensing techniques to reconstruct the 3D motion of an area affected by landslides. The methodologies used are based on two on-demand services available in the Geohazard TEP platform, the Surface motioN maPPING (SNAPPING) and the Ground Deformation Monitoring with OPtical image Time series (GDM-OPT-SLIDE) services. SNAPPING is a multi-temporal interferometric processor based on the Persistent Scatterers Interferometry (PSI) technique that uses Sentinel-1 IW TOPS SLC data to compute surface displacement time series in the Line-of-Sight of the satellite. Considering its extension, the SNAPPING 3D decomposition time series service, it is possible to compute the vertical and horizontal E-W motion components. GDM-OPT-SLIDE, instead, is a technique that processes Sentinel-2 MSI L1C image time series to obtain the surface displacement values in the horizontal plane. In such a way, taking into account the different spatial and temporal resolutions of the outputs of the two services, it is possible to derive the vertical and east-west components of displacement from SNAPPING service and the motion in north-south direction from GDM-OPT-SLIDE technique. This data is available for the points identified as Persistent Scatterers (PS) targets from the SNAPPING processing within the study area. This service prototype, as a consequence of the characteristics of the two techniques on which it is based, is suitable for monitoring slow-moving landslides affecting areas where buildings, infrastructure or rocks are present.