Identification of persistent discontinuities on a granitic rock mass through 3D datasets and traditional fieldwork: A comparative analysis

Abstract

Geologists and engineers traditionally characterise rock slopes through laboratory tests and data captured during fieldwork and further cabinet work. They find, however, difficulties in capturing data in terms of safety, objectiveness and reliability. However, the continuous improvement of remote sensing techniques is changing the rock slope stability analysis. Light Detection and Ranging (LiDAR) and Structure from Motion (SfM) derived datasets comprise 3D point clouds that represent the studied ground surface. This data permits the geometric analysis and the extraction of the number of discontinuity sets affecting the rock mass, and their orientation, normal spacing and persistence. Despite the importance of persistence for characterising discontinuities, the user must previously decide on the field whether a discontinuity is persistent or non-persistent. Contrarily, the use of 3D datasets enables the establishment of objective criteria during the characterisation of rock masses. In this work, we present a comparative analysis of the persistence of a rock slope in Braga (Portugal). An experienced engineer analysed the discontinuities. Besides, the rock slope was digitised through the SfM technique, enabling the analysis and extraction of their discontinuity sets. The results showed that despite the aid of the 3D point clouds, the fieldwork still plays a key role in the field recognition and discontinuities characterisation. However, the use of 3D point clouds provides objective information to enhance the analysis of a rock slope.