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

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... 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