Multi-sensor SAR data for landslide inventory updating: the case study of Piemonte Region

In the last decade, satellite radar differential interferometry (DInSAR) has been used in updating the landslides inventories. The technique allows to monitor the deformation patterns over large areas, in order to verify and/or modify the landslide boundaries. Moreover, it contributes to define the state of activity of a phenomenon. The improvements of the SAR data, guaranteed by the COSMO-SkyMed satellites and by the future ESA Sentinel missions, that act at higher spatio-temporal resolution, require appropriate methodologies for analyzing large datasets of points of measures. To address to these problems, we present a guiding procedure to analyze multi-sensors SAR dataset with the aim of updating landslides inventories. We applied the methodology in Piemonte region, a wide area of north-western Italy affected by a big amount of different types of landslides. We use satellites images acquired, in ascending and descending acquisition geometry, by C-band (ERS ½, ENVISAT, RADARSAT) and X-band (COSMO-SkyMed) sensors and processed using SqueeSARTM, PSInSARTM and PSP-IfSAR techniques. The project was carried out in collaboration with ARPA Piemonte and a part of the interferometric data were provided by the Italian Ministry of Environment in the frame of the “Extraordinary Plan of Environmental Remote Sensing” (PST-A). The developed methodology consists of three main steps: 1) post-processing elaborations of the SAR data, for removing possible errors which could affect the dataset; 2) identification of the ground motion areas characterized by different deformation style (i.e. lowering, uplift and non-linear trend) by the use of automatic and semi-automatic statistical analysis, based on Principal Component Analysis, on the displacement time series; 3) analysis between the identified ground motion areas and the landslides distribution (The Piemonte Landslide inventory–SIFRAP) both at regional scale and at local scale, thanks to detailed in situ analysis for the most interesting sites. Integrating multi-sensor SAR data collected for a continuous period of 24 years (from 1992 to 2015) provided important information on the landslides detection at regional and local scales, in the different geological, geomorphological and environmental contexts of the Piemonte region. Three study areas, where SAR images of all the considered sensors were available, were selected for representing the main contexts of Piemonte region: the Susa (528 km2 wide) and the Orco-Lanzo (996 km2 wide) valleys, representative of the Alps domain; the western Turin hill (404 km2 wide), representative of the Turin hill context. The availability of the large archive of SAR data allowed the backmonitoring of the time evolution of different phenomena. In particular, different phases of activation, re-activation, acceleration or stabilization of the phenomena were recognized. In addition we have assessed the performance of the multi-sensors SAR data for monitoring different landslides types