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Kinematics is a key component of a landslide hazard because landslides moving at similar rates can affect structures or collapse differently depending on their mechanisms. While a complete definition of landslide kinematics requires integrating surface and subsurface site investigation data, its practical estimate is usually based on 2D profiles of surface slope displacements. These can be now measured accurately using Persistent Scatterer InSAR (PSI), which exploits open access satellite imagery. Although 2D profiles of kinematic quantities are easy to retrieve, the efficacy of possible descriptors and extraction strategies has not been systematically compared, especially for complex landslides. Large, slow rock slope deformations, characterized by low displacement rates (<50 mm/year) and spatial and temporal heterogeneities, are an excellent testing ground to explore the best approaches to exploit PSI data from Sentinel-1 for kinematic characterization. For three case studies, we extract profiles of different kinematic quantities using different strategies and evaluate them against field data and simplified numerical modelling. We suggest that C-band PSI data allow for an effective appraisal of complex landslide kinematics, provided that the interpretation is (a) based on decomposed velocity vector descriptors, (b) extracted along critical profiles using interpolation techniques respectful of landslide heterogeneity, and (c) constrained by suitable model-based templates and field data.

Spaceborne radar interferometry is a powerful tool to characterize landslides at local and regional scales. However, its application to very slow rock slope deformations in alpine environments (displacement rates < 5 cm/year) remains challenging, mainly due to low signal to noise ratio, atmospheric disturbances, snow cover effects, and complexities resulting from heterogeneous displacement in space and time. Here we combine SqueeSARTM data, targeted multi-temporal baseline DInSAR, GPS data, and detailed field morpho-structural mapping, to unravel the kinematics, internal segmentation, and style of activity of the Mt. Mater deep-seated gravitational slope deformation (DSGSD) in Valle Spluga (Italy). We retrieve slope kinematics by performing 2D decomposition (2D InSAR) of SqueeSARTM products derived from Sentinel-1 data acquired in ascending and descending orbits. To achieve a spatially-distributed characterization of DSGSD displacement patterns and activity, we process Sentinel-1 A/B images (2016-2019) with increasing temporal baselines (ranging from 24-days to 1-year) and generate several multi-temporal interferograms. Unwrapped displacement maps are validated using ground-based GPS data. Interferograms derived with different temporal baselines reveal a strong kinematic and morpho-structural heterogeneity and outline nested rockslides and active sectors, that arise from the background displacement signal of the main DSGSD. Seasonal interferograms, supported by GPS displacement measurements, reveal non-linear displacement trends suggesting a complex response of different slope sectors to rainfall and snowmelt. Our analyses clearly outline a composite slope instability with different nested sectors possibly undergoing different evolutionary trends towards failure. The results herein outline the potential of a targeted use of DInSAR for the detailed investigation of very slow rock slope deformations in different geological and geomorphological settings.