This study presents a rockfall analysis using UAV-based photogrammetry and 3D models of a cliff area. The research aims to assess the geomechanical properties and rockfall potential of several rock scarps within a 50-hectare area. Traditional methods for evaluating geomechanical parameters on rock scarps are time-consuming and hazardous, while UAV photogrammetry offers a safer and more efficient approach, enabling the creation of detailed 3D models of cliff areas. These models provide insights into topography, geological structures, and potential failure mechanisms. The study processed drone imagery using advanced geospatial software to generate orthophotos and digital elevation models, analyzing key factors contributing to rockfall triggering, including discontinuities, joint orientations, and fracturing frequency. Over 8.9 × 10⁷ facets representing discontinuity planes were recognized and analyzed, showing that direct toppling is the most abundant rockfall type, followed by planar sliding and flexural toppling. Three fracturation grades were identified based on the number of planar facets on rock surfaces. The approach used in this research contributes to the development of fast, practical, low-cost, and non-invasive techniques for geomechanical assessment on vertical rock scarps. The results demonstrate the effectiveness of drone-based photogrammetry for rapidly collecting comprehensive geomechanical data to identify rockfall-prone areas. The study area is located on the Tyrrhenian side of northern Calabria, characterized by vertical rock scarps exposed to sea wave energy and complex geological formations. The approach used in this study can be extended to other similar geological contexts worldwide to analyze the geomechanical conditions of vertical rock scarps. The study used UAV photogrammetry to overcome in-situ survey limitations, showing a fast and precise approach to surveying and managing geomechanical data for rockfall assessment. The approach combines information analysis between different software with accurate statistical analysis using GIS software to establish areas that can withstand rockfalls and mitigate their impact. The study identified areas with high susceptibility to rockfalls through statistical analyses considering the frequency of jointing on steep rock walls. The results confirmed the effectiveness of the approach, as a rockfall occurred in an area previously identified as high-risk. The study used UAV photogrammetry to create high-resolution Digital Terrain Models (DTMs) and Digital Outcrop Models (DOMs), enabling the identification of rockfall-prone areas. The study also analyzed the kinematic failure modes of rock scarps, identifying direct toppling as the most common type, followed by planar sliding and flexural toppling. The results show that areas with high fracturation grades are more prone to rockfalls. The study used CloudCompare v. 2.13 software to extract geomechanical data from DOMs and analyze jointing frequency. The results indicate that areas with high fracturation grades are more prone to rockfalls. The study also analyzedThis study presents a rockfall analysis using UAV-based photogrammetry and 3D models of a cliff area. The research aims to assess the geomechanical properties and rockfall potential of several rock scarps within a 50-hectare area. Traditional methods for evaluating geomechanical parameters on rock scarps are time-consuming and hazardous, while UAV photogrammetry offers a safer and more efficient approach, enabling the creation of detailed 3D models of cliff areas. These models provide insights into topography, geological structures, and potential failure mechanisms. The study processed drone imagery using advanced geospatial software to generate orthophotos and digital elevation models, analyzing key factors contributing to rockfall triggering, including discontinuities, joint orientations, and fracturing frequency. Over 8.9 × 10⁷ facets representing discontinuity planes were recognized and analyzed, showing that direct toppling is the most abundant rockfall type, followed by planar sliding and flexural toppling. Three fracturation grades were identified based on the number of planar facets on rock surfaces. The approach used in this research contributes to the development of fast, practical, low-cost, and non-invasive techniques for geomechanical assessment on vertical rock scarps. The results demonstrate the effectiveness of drone-based photogrammetry for rapidly collecting comprehensive geomechanical data to identify rockfall-prone areas. The study area is located on the Tyrrhenian side of northern Calabria, characterized by vertical rock scarps exposed to sea wave energy and complex geological formations. The approach used in this study can be extended to other similar geological contexts worldwide to analyze the geomechanical conditions of vertical rock scarps. The study used UAV photogrammetry to overcome in-situ survey limitations, showing a fast and precise approach to surveying and managing geomechanical data for rockfall assessment. The approach combines information analysis between different software with accurate statistical analysis using GIS software to establish areas that can withstand rockfalls and mitigate their impact. The study identified areas with high susceptibility to rockfalls through statistical analyses considering the frequency of jointing on steep rock walls. The results confirmed the effectiveness of the approach, as a rockfall occurred in an area previously identified as high-risk. The study used UAV photogrammetry to create high-resolution Digital Terrain Models (DTMs) and Digital Outcrop Models (DOMs), enabling the identification of rockfall-prone areas. The study also analyzed the kinematic failure modes of rock scarps, identifying direct toppling as the most common type, followed by planar sliding and flexural toppling. The results show that areas with high fracturation grades are more prone to rockfalls. The study used CloudCompare v. 2.13 software to extract geomechanical data from DOMs and analyze jointing frequency. The results indicate that areas with high fracturation grades are more prone to rockfalls. The study also analyzed