The Potential of UAV-Acquired Photogrammetric and LiDAR-Point Clouds for Obtaining Rock Dimensions as Input Parameters for Modeling Rockfall Runout Zones

Abstract

Rockfalls present a significant hazard to human activities; therefore, their identification and knowledge about potential spatial impacts are important in planning protection measures to reduce rockfall risk. Remote sensing with unmanned aerial vehicles (UAVs) has allowed for the accurate observation of slopes that are susceptible to rockfall activity via various methods and sensors with which it is possible to digitally collect information about the rockfall activity and spatial distributions. In this work, a three-dimensional (3D) reconstruction of rock deposits (width, length, and height) and their volumes are addressed, and the results are used in a rockfall trajectory simulation. Due to the availability of different sensors on the UAV, the aim was also to observe the possible differences in the dimension estimations between photogrammetric and LiDAR (light detection and ranging) point clouds, besides the most traditional method where rock deposit dimensions are measured on the field using a measuring tape. The motivation for reconstructing rock dimensions and volumes was solely for obtaining input parameters into a rockfall model. In order to study the differences between rock-measuring methods, rock dimensions were used as input parameters in a rockfall model, and additionally, modeling results such as propagation probability, maximum kinetic energies, and maximum passing heights were compared. The results show that there are no statistically significant differences between the measurement method with respect to rock dimensions and volumes and when modeling the propagation probability and maximum passing heights. On the other hand, large differences are present with maximum kinetic energies where LiDAR point cloud measurements achieved statistically significantly different results from the other two measurements. With this approach, an automated collection and measurement process of rock deposits is possible without the need for exposure to a risk of rockfall during fieldwork.

Multi-Sensor and Multi-Scale Remote Sensing Approach for Assessing Slope Instability along Transportation Corridors Using Satellites and Uncrewed Aircraft Systems

“…The traditional field-based methods, while reliable, can be time-consuming, labor-intensive, and often limited in scope. In the current trend of implementing identification and rating systems for slopes affected by instability along infrastructures, previous studies [39][40][41][42][43][44][45][46] have predominantly focused on characterizing local-scale discontinuities within rock masses. The recognition and characterization of families of discontinuities, extensively studied in the literature, are necessary to understand the potential kinematics of block or debris detachment.…”

“…The versatility of UAS sensors and platforms renders them an efficient (yet far from being fully exploited) alternative for evaluating the early precursors of rock destabilization through topographic models [39]. Refs [40][41][42][43] analyzed the predominant discontinuities through UAS-based structure-from-motion (SfM) photogrammetry techniques to estimate average block sizes and determine their simulated run-out. A multi-scale approach consisting of the creation of different digital surface models of the slope along a road was adopted by [44].…”

Three-Dimensional Rockslide Analysis Using Unmanned Aerial Vehicle and LiDAR: The Castrocucco Case Study, Southern Italy

“…[39] and references therein). Turning specifically to rock landslides, UAV photogrammetry and LiDAR are particularly useful for detecting source areas, extracting discontinuity and joint families, computing the volumes of involved rock masses, and modeling block trajectories [40][41][42][43][44].…”