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Natural rock slopes require accurate engineering–geological characterization to determine their stability conditions. Given that a natural rock mass is often characterized by a non-uniform fracture distribution, the correct, detailed, and accurate characterization of the discontinuity pattern of the rock mass is essential. This is crucial, for example, for identifying the possibility and the probability of kinematic releases. In addition, complete stability analyses of possible rockfall events should be performed and used to create hazard maps capable of identifying the most dangerous parts of a rock mass. This paper shows a working approach that combines traditional geological surveys and remote sensing techniques for engineering–geological investigations in a natural rock slope in Northern Italy. Discontinuities were identified and mapped in a deterministic way by using semi-automatic procedures that were based on detailed 3D Unmanned Aerial Vehicle photogrammetric-based point cloud data and provided georeferenced representations of thousands of fractures. In this way, detailed documentation of the geo-mechanical and geo-structural characteristics of discontinuities were obtained and subsequently used to create fracture density maps. Then, traditional kinematic analyses and probabilistic stability analyses were performed using limit equilibrium methods. The results were then managed in a GIS environment to create a final hazard map that classifies different portions of the rock slope based on three factors: kinematic predisposition to rockfall (planar sliding, wedge sliding, toppling), fracture density, and probability of failure. The integration of the three hazard factors allowed the identification of the most hazardous areas through a deterministic and accurate procedure, with a high level of reliability. The adopted approach can therefore be very useful to determine the areas in which to prioritize remediation measures with the aim of reducing the level of risk.

Hazard Assessment of Rocky Slopes: An Integrated Photogrammetry–GIS Approach Including Fracture Density and Probability of Failure Data