Airborne remote sensing systems are increasingly used in engineering geology and geomorphology for studying and monitoring natural hazardous scenarios and events. In this study, we used two remote sensing monitoring techniques, i.e., light detection and ranging (LiDAR) and unmanned aerial vehicles (UAV) to analyze the kinematic evolution of the Montescaglioso landslide (Basilicata, Southern Italy), a large rain-triggered landslide that occurred in December 2013. By comparing pre- and post-event LiDAR and UAV DEMs and UAV orthomosaics, we delineated landslide morphological features and measured horizontal displacements and elevation change differences within landslide body. Analysis of two subsequent post-events digital terrain models (DTMs) also allowed the evaluation of the evolutionary behavior of the slope instability, highlighting no signs of reactivation. The UAV-derived digital surface models (DSMs) were found consistent with the LiDAR-DTMs, but their use was in addition highlighted as highly effective to support geomorphic interpretations and complement LiDAR and field-based data acquisitions. This study shows the effectiveness of combining the two UAV-LiDAR methodologies to evaluate geomorphological features indicative of the failure mechanism and to interpret the evolutionary behavior of the instability process

In this paper, a study aimed to assess the landslide susceptibility at a regional scale for the wide provincial territory of Matera (Basilicata region, southern Italy) and the relative risk along the main road corridors distributed in this area is presented. A heuristic-bivariate statistical predictive model was performed to assess and map the landslide susceptibility in the study area by using a polynomial function of eight predisposing factors, weighted according to their influence on the instability process. The resulting susceptibility map was successively used for assessing the landslide risk along the provincial road network. The importance of these roads, representing the main network connecting the urban centres, derives from the absence of an efficient integrated transportation system through the entire regional territory. The landslide risk was evaluated through a matricial approach, which has allowed to define the risk levels (low, medium and high) along road stretches by overlapping the consequences and hazard maps, by combining their corresponding classes in a matrix and by associating to each combination a risk level. The resulting landslide risk map provides support information for decision-making and for identifying the priorities for the design of appropriate mitigation plans.

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.