Recent advances in analysis and prediction of Rock Falls, Rock Slides, and Rock Avalanches using 3D point clouds

The acquisition of dense terrain information using well-established 3D techniques (e.g. LiDAR, photogrammetry) and the use of new mobile platforms (e.g. Unmanned Aerial Vehicles) together with the increasingly efficient post-processing workflows for image treatment (e.g. Structure From Motion) are opening up new possibilities for analysing, modeling and predicting rock slope failures. Examples of applications at different scales ranging from the monitoring of small changes at unprecedented level of detail (e.g. sub millimeter-scale deformation under lab-scale conditions) to the detection of slope deformation at regional scale. In this communication we will show the main accomplishments of the Swiss National Foundation project “Characterizing and analysing 3D temporal slope evolution“ carried out at Risk Analysis group (Univ. of Lausanne) in close collaboration with the RISKNAT and INTERES groups (Univ. of Barcelona and Univ. of Alicante, respectively).

We have recently developed a series of innovative approaches for rock slope analysis using 3D point clouds, some examples include: the development of semi-automatic methodologies for the identification and extraction of rock-slope features such as discontinuities, type of material, rockfalls occurrence and deformation. Moreover, we have been improving our knowledge in progressive rupture characterization thanks to several algorithms, some examples include the computing of 3D deformation, the use of filtering techniques on permanently based TLS, the use of rock slope failure analogies at different scales (laboratory simulations, monitoring at glacier’s front, etc.), the modelling of the influence of external forces such as precipitation on the acceleration of the deformation rate, etc. We have also been interested on the analysis of rock slope deformation prior to the occurrence of fragmental rockfalls and the interaction of this deformation with the spatial location of future events.

In spite of these recent advances, a great challenge still remains in the development of new algorithms for more accurate techniques for 3D point cloud treatment (e.g. filtering, segmentation, etc.) aiming to improve rock slope characterization and monitoring, a series of exciting research findings are expected in the forthcoming years.