An example of the combined use of UAV photogrammetry and rockfall numerical simulation is described. A case of fragmental rockfall occurred on 17 November 2018 in Cárcavos, a site located in the Spanish municipality of Ayna (Albacete). The event caused a great social alarm as some infrastructure was affected. By using Unmanned Aerial Vehicle (UAV) photogrammetry, a high-resolution 3D model has been generated from point cloud data, and distribution and size of the fragmented rocks (more than 600 boulders) determined. The analysis has been performed through numerical simulations to: (1) reproduce the paths followed by the real blocks; and (2) estimate the speed and energy of the blocks, together with their heights, impacts and stopping points. Accordingly, source areas have been identified, including the potential source areas and unstable blocks on the slope. In addition, the exposed elements at risk (buildings, facilities, infrastructures, etc.) have been identified, and the effectiveness of mitigation measures against future events evaluated.

Rockslides are one of the most dangerous hazards in mountainous and hilly areas. In this study, a rockslide that occurred on 30 November 2022 in Castrocucco, a district located in the Italian municipality of Maratea (Potenza province) in the Basilicata region, was investigated by using pre- and post-event high-resolution 3D models. The event caused a great social alarm as some infrastructures were affected. The main road to the tourist hub of Maratea was, in fact, destroyed and made inaccessible. Rock debris also affected a beach club and important boat storage for sea excursions to Maratea. This event was investigated by using multiscale and multisensor close-range remote sensing (LiDAR and SfM) to determine rockslide characteristics. The novelty of this work lies in how these data, although not originally acquired for rockslide analysis, have been integrated and utilized in an emergency at an almost inaccessible site. The event was analyzed both through classical geomorphological analysis and through a quantitative comparison of multi-temporal DEMs (DoD) in order to assess (i) all the morphological features involved, (ii) detached volume (approximately 8000 m³), and (iii) the process of redistributing and reworking the landslide deposit in the depositional area.

In the last decade the interest in understanding or assessing the susceptibility of earthquake induced landslides has considerably increased in the scientific literature. In this context rockfalls present a challenge due to the difficulty to collect information on fallen boulders following an earthquake emergency. The data obtained is often biased, as it is usually recorded only when it causes damage to buildings or road networks. Important aspects for future studies, such as the identification of source areas, are generally overlooked.This study aims to develop a coseismic rockfall analysis based on the Turkish scenario, where two massive earthquakes of magnitude 7.8 and 7.5 struck on February 6, 2023, triggering approximately 3,673 landslides, the majority of which were rockfalls. The approach combines data collection and statistical analysis to obtain the key input data needed for forecasting rockfall trajectories caused by future earthquakes.The well-timed collection of post-event high resolution ortho-images allowed to realize a thorough coseismic rockfall inventory of the area affected by the earthquakes. This inventory will serve to train both the source area susceptibility model and the trajectories simulation model.This information allows the application of an occurrence probability model based on ground motion predictive equations and the estimated peak ground acceleration for a potential earthquake along the left-lateral East Anatolian Fault, focusing on the identification of future source areas susceptible to rockfall. From these sources, some rockfall trajectories will be simulated to assess the hazard zonation along the main infrastructures like road, pipelines and villages.