Multi-temporal SAR interferometry technique for studying slope instability phenomena and their evolution

Purpose: Multi-temporal SAR interferometry (MTInSAR), by providing both mean displacement maps and displacement time series over coherent objects on the Earth's surface, allows analyzing wide areas, identifying ground displacements, and studying the phenomenon evolution at a long-time scale. In particular, early warning signals derived from MTInSAR displacement products may be very useful for decision-making processes in the risk assessment phase. This study exploits the potential of COSMO-SkyMed (CSK) and Sentinel 1 (S1) satellite missions to investigate ground and structure displacements related to the slope instabilities. Furthermore, it investigates methods for the automatic identification of nonlinear displacement time series that reliably support the analysis of the huge quantity of coherent targets nowadays available from MTInSAR processing chains. Methods: This work presents the results obtained by analyzing displacement time series from both CSK and S1 for investigating the ground stability of hilly villages located in the Southern Italian Apennines. Both ascending and descending orbits were processed by using the SPINUA MTInSAR algorithm. Mean velocity maps and displacement time series were analyzed, looking, in particular, for nonlinear trends that are possibly related to relevant ground instabilities. This analysis was also supported by automated procedures recently developed, one based on the fuzzy entropy (FE) indicator, the other performing nonlinear trend analysis (NLTA) based on the Fisher statistics. The FE index was able to recognize coherent targets affected by phase unwrapping errors, which should be corrected to provide reliable displacement time series to be further analyzed. The NLTA was used for classifying targets according to the optimal degree of a polynomial function describing the displacement trend. This allowed the focus on a smaller set of coherent targets showing nonlinear displacement trends related to the several ground and structure instabilities. Results: The joint exploitation of MTInSAR datasets acquired at different wavelengths, resolutions, and revisit times provided valuable insights, with CSK more effective over man-made structures, and S1 over outcrops. Both automated procedures were very effective in supporting the analysis of ground displacements provided by MTInSAR, since they helped focusing on a smaller set of coherent targets identifying unstable areas or structures on the ground. In particular, the work presents examples concerning [1]: (i) slope pre-failure monitoring; (ii) slope post-failure monitoring; (iii) displacement evolution monitoring of areas and structures affected by instability related to different causes. Conclusions: These results clearly confirm the valuable use of MTInSAR products as a tool that is additional to the established techniques for studying the dynamics of slope instability phenomena and their evolution. The analysis of MTInSAR-based displacement time series, possibly performed through ad hoc automated procedures, can provide useful information for long-term monitoring, management, and risk assessment at the regional level, when combined with planning tools, and support decision-makers at a local level in risk management.