In this research, we present a new approach to define the distribution of block volumes during rockfall simulations. Unmanned aerial vehicles (UAVs) are utilized to generate high-accuracy 3D models of the inaccessible SW flank of the Mount Rava (Italy), to provide improved definition of data gathered from conventional geomechanical surveys and to also denote important changes in the fracture intensity. These changes are likely related to the variation of the bedding thickness and to the presence of fracture corridors in fault damage zones in some areas of the slope. The dataset obtained integrating UAV and conventional surveys is then utilized to create and validate two accurate 3D discrete fracture network models, representative of high and low fracture intensity areas, respectively. From these, the ranges of block volumes characterizing the in situ rock mass are extracted, providing important input for rockfall simulations. Initially, rockfall simulations were performed assuming a uniform block volume variation for each release cell. However, subsequent simulations used a more realistic nonuniform distribution of block volumes, based on the relative block volume frequency extracted from discrete fracture network (DFN) models. The results of the simulations were validated against recent rockfall events and show that it is possible to integrate into rockfall simulations a more realistic relative frequency distribution of block volumes using the results of DFN analyses.

Digital photogrammetry (DP) represents one of the most used survey techniques in engineering geology. The availability of new high-resolution digital cameras and photogrammetry software has led to a step-change increase in the quality of engineering and structural geological data that can be collected. In particular, the introduction of the structure from motion methodology has led to a significant increase in the routine uses of photogrammetry in geological and engineering geological practice, making this method of survey easier and more attractive. Using structure from motion methods, the creation of photogrammetric 3D models is now easier and faster, however the use of ground control points to scale/geo-reference the models are still required. This often leads to the necessity of using total stations or Global Positioning System (GPS) for the acquisition of ground control points. Although the integrated use of digital photogrammetry and total station/GPS is now common practice, it is clear that this may not always be practical or economically convenient due to the increase in cost of the survey. To address these issues, this research proposes a new method of utilizing photogrammetry for the creation of georeferenced and scaled 3D models not requiring the use of total stations and GPS. The method is based on the use of an object of known geometry located on the outcrop during the survey. Targets located on such objects are used as ground control points and their coordinates are calculated using a simple geological compass and trigonometric formula or CAD 3D software. We present three different levels of survey using (i) a calibrated digital camera, (ii) a non-calibrated digital camera and (iii) two commercial smartphones. The data obtained using the proposed approach and the three levels of survey methods have been validated against a laser scanning (LS) point cloud. Through this validation we highlight the advantages and limitations of the proposed method, suggesting potential applications in engineering geology.

This research aims to highlight the importance of adopting a multi-disciplinary approach to understanding the factors controlling large rock avalanches using the Scanno landslide, Italy, as a case study. The study area is the Mount Genzana, Abruzzi Central Apennines, characterized by the regional Difesa-Mount Genzana-Vallone delle Masserie fault zone. The Scanno landslide is famous for its role in the formation of the Scanno Lake. The landslide is characterized by a wide exposed scar, which was interpreted in previous studies as the intersection of high-angle joints and an outcropping bedding plane on which the landslide failed sometime between the Upper Pleistocene and the Holocene. In this study, the Scanno landslide was investigated through the integration of geological, geomechanical and geomorphological surveys. Remote sensing techniques were used to enrich the conventionally gathered datasets, while Geographic Information Systems (GIS) were used to integrate, manage and investigate the data. The results of the authors investigation show that the outcropping landslide scar can be interpreted as a low-angle fault, associated with the Difesa-Mount Genzana-Vallone delle Masserie fault zone, which differs from previous investigations and interpretations of the area. The low-angle fault provides the basal failure surface of the landslide, with two systematic high-angle joint sets acting as lateral release and back scarp surfaces, respectively. In light of these new findings, pre- and post-failure models of the area have been created. The models were generated in GIS by combining LiDAR (Light Detection and Ranging) and geophysics data acquired on the landslide body and through bathymetric survey data of the Scanno Lake. Using the pre- and post-failure models it was possible to estimate the approximate volume of the landslide. Finally, back-analyses using static and dynamic limit equilibrium methods is also used to show the possible influence of medium-to-high magnitude seismic events in triggering the Scanno landslide.