Rockfall Analysis from UAV-Based Photogrammetry and 3D Models of a Cliff Area

Abstract

The application of Unmanned Aerial Vehicles (UAVs), commonly known as drones, in geological, geomorphological, and geotechnical studies has gained significant attention due to their versatility and capability to capture high-resolution data from challenging terrains. This research uses drone-based high-resolution photogrammetry to assess the geomechanical properties and rockfall potential of several rock scarps within a wide area of 50 ha. Traditional methods for evaluating geomechanical parameters on rock scarps involve time-consuming field surveys and measurements, which can be hazardous in steep and rugged environments. By contrast, drone photogrammetry offers a safer and more efficient approach, allowing for the creation of detailed 3D models of a cliff area. These models provide valuable insights into the topography, geological structures, and potential failure mechanisms. This research processed the acquired drone imagery using advanced geospatial software to generate accurate orthophotos and digital elevation models. These outputs analysed the key factors contributing to rockfall triggering, including identifying discontinuities, joint orientations, kinematic analysis of failures, and fracturing frequency. More than 8.9 × 107 facets, representing discontinuity planes, were recognised and analysed for the kinematic failure modes, showing that direct toppling is the most abundant rockfall type, followed by planar sliding and flexural toppling. Three different fracturation grades were also identified based on the number of planar facets recognised on rock surfaces. The approach used in this research contributes to the ongoing development of fast, practical, low-cost, and non-invasive techniques for geomechanical assessment on vertical rock scarps. In particular, the results show the effectiveness of drone-based photogrammetry for rapidly collecting comprehensive geomechanical data valid to recognise the prone areas to rockfalls in vast regions.

Hash Encoding and Brightness Correction in 3D Industrial and Environmental Reconstruction of Tidal Flat Neural Radiation

“…Unmanned aerial vehicles (UAVs), renowned for their agility, versatility, speed, and cost-effectiveness, serve as invaluable platforms for aerial photography, enabling the swift capture of high-resolution images with vast potential for generating geographic mapping data [ 1 , 2 ]. Over recent decades, UAV photogrammetry has found applications across various disciplines within the geosciences, including sedimentology [ 3 , 4 ], earthquake geology [ 5 , 6 ], structural geology [ 7 ], geomorphology [ 8 ], engineering geology [ 9 , 10 ], archaeology [ 11 , 12 ], forestry [ 13 , 14 ], and landscape evolution and natural hazards [ 15 , 16 ]. Innovative techniques such as RTK or PPK aero photogrammetric surveying have yielded numerous accurate 3D models [ 7 , 17 ].…”

New Concept of Smart UAS-GCP: A Tool for Precise Positioning in Remote-Sensing Applications

“…Data acquired using UASs offer useful information for archaeological investigations and cataloging [8,9], geological and geomorphological surveys and monitoring [10][11][12][13][14][15], earthquake surface-faulting analyses [16], urban mapping [17], emergency assessments [18][19][20], land cover classifications [21][22][23], multitemporal investigations [24][25][26], and engineering applications [27,28]. Nowadays, most UASs include an onboard, multifrequency GNSS receiver, which is very useful for geomatic applications [29,30].…”

Drones and Real-Time Kinematic Base Station Integration for Documenting Inaccessible Ruins: A Case Study Approach

“…In such a case, it becomes interesting to understand the most appropriate approaches on how to conduct the survey, which drone to prefer, and which methods to implement to integrate the data resulting from the different instruments. Certainly, the possibility of using a base GNSS receiver coupled with a UAV makes it possible to take georeferenced photographs, which then allows direct georeferencing to be performed within the photogrammetric process [9,10]. In addition, the use of drones coupled with a ground base station, exploiting Real-Time Kinematic (RTK) or Post-Processing Kinematic (PPK) technologies, would result in a greater accuracy of such data [11][12][13].…”