A major mining slope failure occurred in July 2012 on the East wall of the LAB Chrysotile mine in Canada. The major consequence of this failure was the loss of the local highway (Road 112), the main commercial link between the region and the Northeast USA. LiDAR scanning and subsequent analyses were performed and enabled quantifying the geometry and kinematics of the failure area. Using this information, this paper presents the back analysis of the July 2012 failure. The analyses are performed using deterministic and probabilistic limit equilibrium analysis and finite-element shear strength reduction analysis modelling. The impact of pit water infilling on the slope stability is investigated. The impact of the mining activity in 2011 in the lower part of the slope is also investigated through a parametric analysis.

A major mining slope failure occurred in July 2012 on the East wall of the LAB Chrysotile mine in Canada. The major consequence of this failure was the loss of the local highway (Road 112), the main economic link between the region and the Northeast USA. This paper is part of a proposed integrated remote sensing-numerical modelling methodology to analyze mining rock slope stability. This paper presents the Light Detection and Ranging (LiDAR) monitoring of this slope failure. The main focus is the investigation of that rock slide using both terrestrial (TLS) and airborne (ALS) LiDAR scanning. Since 2010, four ALS and 14 TLS were performed to characterize and monitor the slide. First, laser scanning was used to investigate the geometry of the slide. The failure zone was 1100 m by 250 m in size with a mobilized volume of 25 hm 3. Laser scanning was then used to investigate the rock slide's 3D displacement, thereby enabling a better understanding of the sliding kinematics. The results clearly demonstrate the ability of the proposed approach to monitor and quantify largescale rock mass failure. The slope was monitored for a period of 5 years, and the total displacement was measured at every survey. The maximum cumulative total displacement reached was 145 m. This paper clearly shows the ability of LiDAR scanning to provide valuable quantitative information on large rock mass failures involving very large displacements.

Abstract. 2D and 3D imageries can allow the optimization of rock mass exploitation (quarries, roads, rail networks, open pit, potentially tunnels and underground mines networks). The increasingly common use of photogrammetry makes it possible to obtain georeferenced 3D point clouds that are useful for understanding the rock mass. Indeed, new structural analysis solutions have been proposed since the advent of the 3D technologies. These methods are essentially focused on the production of digital stereonet. Production of additional information from 3D point clouds are possible to better define the structure of the rock mass, in particular the quantification of the discontinuities density. The aim of this paper is to test and validate a new method that provides statistics on the distances between the discontinuity planes. This solution is based on exploiting the information previously extracted from the segmentation of the discontinuity planes of a point cloud and their classification in family. In this article, the proposed solution is applied on two multiscale examples, firstly to validate it with a virtual synthetic outcrop and secondly to test it on a real outcrop. To facilitate these analyses, a software called DiscontinuityLab has been developed and used for the treatments.