A methodology for ground motion area detection (GMA-D) using A-DInSAR time series in landslide investigations

In recent years, the Advanced Differential Interferometric Synthetic-Aperture Radar (A-DInSAR) technique has advanced rapidly for detecting and monitoring ground surface deformations due to landslides. Identification of the areas affected by ground motion through A-DInSAR data is generally based on visual inspection and hotspot or cluster analysis of average displacement rates. However, interpreting A-DInSAR time series of a particular area can provide a better indication of the real trend of displacement of a landslide, while identifying the possible moment of acceleration of the deformation process as well. In this work, a novel methodology is proposed for identifying different typologies of ground motion areas mainly related to landslide phenomena at a regional scale, by means of A-DinSAR data at high spatial and temporal resolutions. This methodological approach was tested and validated in a wide area of the Piedmont region (northern Italy), by means of RADARSAT and COSMO-SkyMed satellite data, in both ascending and descending modes. These sensors have a high spatial resolution, allowing investigation of a higher number of landslides as compared to that of the older ERS-1/2 and Envisat data. Linear (constant in time displacement) and non-linear (acceleration or deceleration in the displacement rate) trends were recognised, allowing characterisation of the kinematic pattern of a landslide or a portion of it. Local and site-specific scale analyses, performed in an Alpine valley and in two hillslopes representative of the main geological/geomorphological contexts of the study area, validated the results obtained at the regional scale. This supported the interpretation of the driving mechanism for such known landslides, or other geological processes which can cause ground motion along slopes. The developed procedure can allow one to specify priority areas for prevention activities, in order to optimise the costs and benefits of designing a plan to monitor instability phenomena at regional and site-specific scale