D. Jean Hutchinson

Evaluating roadside rockmasses for rockfall hazards using LiDAR data: optimizing data collection and processing protocols

Highways and railroads situated within rugged terrain are often subjected to the hazard of rockfalls. The task of assessing roadside rockmasses for potential hazards typically involves an on-site visual investigation of the rockmass by an engineer or geologist. At that time, numerous parameters associated with discontinuity orientations and spacing, block size (volume) and shape distributions, slope geometry, and ditch profile are either measured or estimated. Measurements are typically tallied according to a formal hazard rating system, and a hazard level is determined for the site. This methodology often involves direct exposure of the evaluating engineer to the hazard and can also create a potentially non-unique record of the assessed slope based on the skill, knowledge and background of the evaluating engineer. Light Detection and Ranging (LiDAR)–based technologies have the capability to produce spatially accurate, high-resolution digital models of physical objects, known as point clouds. Mobile terrestrial LiDAR equipment can collect, at traffic speed, roadside data along highways and rail lines, scanning continual distances of hundreds of kilometres per day. Through the use of mobile terrestrial LiDAR, in conjunction with airborne and static systems for problem areas, rockfall hazard analysis workflows can be modified and optimized to produce minimally biased, repeatable results. Traditional rockfall hazard analysis inputs include two distinct, but related sets of variables related to geological or geometric control. Geologically controlled inputs to hazard rating systems include kinematic stability (joint identification/orientation) and rock block shape and size distributions. Geometrically controlled inputs include outcrop shape and size, road, ditch and outcrop profile, road curvature and vehicle line of sight. Inputs from both categories can be extracted or calculated from LiDAR data, although there are some limitations and special sampling and processing considerations related to structural character of the rockmass, as detailed in this paper.

Risk considerations for crown pillar stability assessment for mine closure planning

Evaluation of the long-term surface stability of crown pillars overlying underground mines is an important component of mine closure planning. The definition of a crown pillar, as well as a brief discussion of the assessment of the probability and consequence of crown pillar failure are given in this paper. Techniques for stability assessment using mechanistic, empirical and numerical simulation techniques are discussed. Consequence assessment is discussed, but is still subjective and difficult to quantify. Where crown pillars are suspected to be marginally stable or unstable either at the time of the investigation or over the long term, and where the consequence of failure is medium to high, the closure plan for the site must include proposed rehabilitation alternatives. Selection of the optimum solution depends largely upon financial considerations, but also upon the common public expectation that the result of mine closure planning be a ‘permanent’ solution that does not restrict public access or future land use on the site.

Rock Slopes Asset Management: Selecting the Optimal Three-Dimensional Remote Sensing Technology

Transportation corridors are classified as critical infrastructure in the United States and Canada. Successfully maintaining these corridors in safe, operational condition requires strategies that address individual hazard classes and manage associated risks. Natural and constructed slopes along transportation corridors represent one such category of hazard; typical risk management strategies involve quantitative measurements and qualitative evaluations of their present condition and the hazards that they pose to infrastructure, people, and shipments along the route. At some sites, traditional field-based observations are supplemented by high-resolution remotely acquired three-dimensional (3-D) imaging data of the ground surface, generated from various sensors and platforms, including terrestrial lidar and photogrammetry, airborne lidar, and oblique aerial photogrammetry. The collection, processing, and implementation of 3-D data collection and analysis into a slope management system are complex and frequently result in poorly collected, poorly understood, and underused data. Furthermore, the intricacies of the applications and limitations of different technologies generally are well understood only by specialists. As a result, the industry is reluctant to implement these technologies in active slope management systems. Practical procedures for remote data collection are illustrated, and the applications and limitations of the previously mentioned technologies are explained. The current capabilities of these technologies are presented; because the field is advancing rapidly, innovation and development soon will enhance the applicability of these technologies.

Three-dimensional numerical simulations of the Downie Slide to test the influence of shear surface geometry and heterogeneous shear zone stiffness

Massive slow-moving landslides often exhibit deformation patterns which vary spatially across the landslide mass and temporally with changing boundary conditions. Understanding the parameters controlling this behaviour, such as heterogeneous material properties, complex landslide geometry and the distribution of groundwater, is fundamental when making informed design and hazard management decisions. This paper demonstrates that significant improvements to the geomechanical analysis of massive landslides can be achieved through rigorous, three-dimensional numerical modelling. Simulations of the Downie Slide incorporate complex shear zone geometries, multiple water tables and spatial variation of shear zone stiffness parameters to adequately reproduce real slope behaviour observed through an ongoing site monitoring program. These three-dimensional models are not hindered by shortfalls typically associated with two-dimensional analysis, for example the ability to accommodate lateral migration of material, and they out-perform more simplified three-dimensional models where bowl-shaped shear geometries are incapable of reasonably reproducing observed deformation patterns.

Automated terrestrial laser scanning with near-real-time change detection – monitoring of the Séchilienne landslide

We present an automated terrestrial laser scanning (ATLS) system with automatic near-real-time change detection processing. The ATLS system was tested on the Séchilienne landslide in France for a 6-week period with data collected at 30 min intervals. The purpose of developing the system was to fill the gap of high-temporal-resolution TLS monitoring studies of earth surface processes and to offer a cost-effective, light, portable alternative to ground-based interferometric synthetic aperture radar (GB-InSAR) deformation monitoring. During the study, we detected the flux of talus, displacement of the landslide and pre-failure deformation of discrete rockfall events. Additionally, we found the ATLS system to be an effective tool in monitoring landslide and rockfall processes despite missing points due to poor atmospheric conditions or rainfall. Furthermore, such a system has the potential to help us better understand a wide variety of slope processes at high levels of temporal detail.