The Structure from Motion (SfM) photogrammetric technique has been widely used, due to its ease of use and low cost, as an excellent alternative for remote 3D rock mass characterization. This technique uses only the information obtained from the digital images acquired with a regular camera to generate very high-resolution 3D models. However, this technique is widely influenced by environmental and physical conditions (degree of luminosity, distance to the target, geometry, etc.) of each case. In this work, we present our previous experiences, from a micro-scale application (in the laboratory) for small-scale roughness analysis, to a large-scale application (in the field) for the characterization of long slopes using drones. For each application, different methodologies have been proposed, adapting the SfM technique and developing innovative solutions. The obtained results confirm the applicability of SfM to efficiently solve rock engineering problems at different scales and under different conditions.
The multi-scale characterization of rock masses –from intact rock to rock joints, to rock masses– is important in rock mechanics and rock engineering, and several methods have been proposed for such task, such as the suggested by ISRM Commission on Standardization of Laboratory and Field Tests (1978). More recently, efficiency and safety reasons have promoted more advanced characterization technologies –such as photogrammetry or LiDAR– to obtain 3D models of rock joints or rock masses, which can be employed as a basis for engineering characterization of rock joints and rock masses and, hence, to solve rock engineering problems at different scales. This article explores the use of the Structure from Motion (SfM) technology to that end, and it presents recent examples of SfM application to (i) characterize rock joint roughness at the laboratory scale; to (ii) characterize roughness at field scale to solve rock slope stability problems; and (iii) to characterize rock slopes at a larger scale, and to estimate their associated risks.
