Assessing the Potential of Long, Multi-Temporal SAR Interferometry Time Series for Slope Instability Monitoring: Two Case Studies in Southern Italy

Abstract

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. This technique has also been proven to be very useful for detecting and monitoring slope instabilities. For this type of hazard, detection of velocity variations over short time intervals should be useful for early warning of damaging events. In this work, we present the results obtained by using both COSMO-SkyMed (CSK) and Sentinel-1 (S1) data for investigating the ground stability of two hilly villages located in the Southern Italian Apennines (Basilicata region), namely the towns of Montescaglioso and Pomarico. In these two municipalities, landslides occurred in the recent past (in Montescaglioso in 2013) and more recently (in Pomarico in 2019), causing damage to houses, commercial buildings, and infrastructures. SAR datasets acquired by CSK and S1 from both ascending and descending orbits were processed using the SPINUA MTInSAR algorithm. Mean velocity maps and displacement time series were analyzed, also by means of innovative ad hoc procedures, looking, in particular, for non-linear trends. Results evidenced the presence of nonlinear displacements in correspondence of some key infrastructures. In particular, the analysis of accelerations and decelerations of PS objects corresponding to structures affected by recent stabilization measures helps to shed new light in relation to known events that occurred in the area of interest.

Remote Sensing Analysis of Geologic Hazards

“…Six papers examine this phenomenon. However, the studies focus on different themes; some are dedicated to landslide detection [29] and others to triggering factors and susceptibility analysis [30][31][32], monitoring [33] and early warning procedures [34].…”

“…Bovenga et al [33] applied MTInSAR to Sentinel-1 and COSMO-SkyMed to measure the velocity time series of two landslides that occurred in 2013 and 2019 in southern Italy, which caused damages to buildings and roads. Their results evidenced the presence of nonlinear displacements in correspondence of some key infrastructures.…”

PSI Spatially Constrained Clustering: The Sibari and Metaponto Coastal Plains

“…Several different techniques have been proposed [18][19][20][21][22]. In particular, PSI techniques are extremely helpful when dealing with slow-occurring phenomena such as subsidence, tectonic uplifts, and ground deformation processes in civil engineering structures [23].…”

LADSDIn: LiCSAR-Based Anomaly Detector of Seismic Deformation in InSAR

“…SBASInSAR improves coherence and deformation detection accuracy by limiting interference to spatial baselines using multiple master image combinations [12]. The combined approach of SBASInSAR can extract distributed point targets that remain coherent for a certain period, further increasing the point density, which is very suitable for natural ground deformation monitoring and can achieve long time series and millimeter-scale deformation monitoring at the regional scale [13]. However, the high price of commercial SAR data and the severe scarcity of civilian SAR data have limited the application of MTInSAR to seismic deformation studies for a long time [14].…”