Automatic Mapping of Discontinuity Persistence on Rock Masses Using 3D Point Clouds

Finding new ways to quantify discontinuity persistence values in rock masses in an automatic or semi-automatic manner is a considerable challenge, as an alternative to the use of traditional methods based on measuring patches or traces with tapes. Remote sensing techniques potentially provide new ways of analysing visible data from the rock mass. This work presents a methodology for the automatic mapping of discontinuity persistence on rock masses, using 3D point clouds. The method proposed herein starts by clustering points that belong to patches of a given discontinuity. Coplanar clusters are then merged into a single group of points. Persistence is measured in the directions of the dip and strike for each coplanar set of points, resulting in the extraction of the length of the maximum chord and the area of the convex hull. The proposed approach is implemented in a graphic interface with open source software. Three case studies are utilized to illustrate the methodology: (1) small-scale laboratory setup consisting of a regular distribution of cubes with similar dimensions, (2) more complex geometry consisting of a real rock mass surface in an excavated cavern and (3) slope with persistent sub-vertical discontinuities. Results presented good agreement with field measurements, validating the methodology. Complexities and difficulties related to the method (e.g. natural discontinuity waviness) are reported and discussed. An assessment on the applicability of the method to the 3D point cloud is also presented. Utilization of remote sensing data for a more objective characterization of the persistence of planar discontinuities affecting rock masses is highlighted herein

Recommendations for the quantitative analysis of landslide risk

This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies described focus on the evaluation of the probabilities of occurrence of different landslide types with certain characteristics. Methods used to determine the spatial distribution of landslide intensity, the characterisation of the elements at risk, the assessment of the potential degree of damage and the quantification of the vulnerability of the elements at risk, and those used to perform the quantitative risk analysis are also described. The paper is intended for use by scientists and practising engineers, geologists and other landslide experts

Probabilistic vs. Deterministic Approach in Landslide Triggering Prediction at Large–scale

Reliability in the prediction of rainfall-induced shallow landslides at large scale has constituted a great challenge in the last decades. Different approaches have been adopted to include in the forecasts both the geometric, mechanical and climatic factors that affect the triggering phase of the process. A quite promising one is based on the probabilistic physically–based model implemented in the code PG TRIGRS, which takes into account the uncertainty in soil spatial variability and characterization. The model uses the Kriging technique to assess the spatial distribution of soil properties for the study areas, starting from available georeferenced measurements, alongwith their probability distribution functions. The Point Estimate Method (PEM) is then used to evaluate the Probability of Failure (PoF) within the study area, where PoF is defined as the probability that the Factor of Safety is less or equal than 1. This version is an extension of the original TRIGRS code, which combines a 1D hydrologic model with a stability analysis to assess the safety level of a given slope in a deterministic manner. In this work we compare the results provided by PG TRIGRS versus the original version of the code, by applying both of them to the same study area in Central Italy