Through the exploitation of mobile terrestrial lidar, rockfall hazard analysis workflows can be optimized to produce minimally biased, repeatable results. Typical rockfall hazard analysis inputs include two distinct but related sections of variables; they are geologically and geometrically controlled. Geological controlled inputs are kinematic stability (joint identification) and rock block shape and size distributions. Geometrically controlled inputs are outcrop shape and size, road, ditch and outcrop profile. All of this information can be extracted or calculated from lidar data, as are demonstrated in this paper.
Highways and railroads situated within mountainous terrains are often subject to the hazard of rockfalls. The task of assessing roadside rockmasses for potential hazards typically involves a visual investigation of the rockmass by an engineer or geologist. At that time numerous measurements associated with discontinuity orientations and spacing, block size and shape distributions, slope geometry, and ditch profile are taken or estimated. The measurements are typically tallied according to the employed hazard rating system and a hazard level is determined for the site. This methodology involves direct exposure of the engineer to the hazard; as well, it creates a biased record of the assessed slope based on the skill, knowledge and background of the engineer. Light Detection and Ranging based technologies have the capability to produce spatially accurate, high-resolution models of physical objects, known as point-clouds. Mobile terrestrial lidar equipment can collect roadside data along highways and rail lines at flow of traffic speed at the rate of hundreds of kilometers per day. The use of lidar data for geomechanical investigation is strongly contingent on data management protocols, processing workflows, and standardized feature extraction techniques. Unlike measurements made in the field, all measurements taken from the lidar data remain part of the data structure and can be reinvestigated at a later date.