Using LiDAR as a monitoring device to calculate volume of rockfall over time

There are many natural hazards which threaten the stability of highway infrastructure and the safety of motoring public. Rockfall and unstable slopes are one of the major concerns. This thesis describes a method which safely and accurately evaluates rockfall on rock outcrops through the use of Light Detection and Ranging (LiDAR) data. LiDAR is an imaging technology which can be used to measure and evaluate possible rock outcrop hazards such as: rockfall, rock-avalanches, debris flows, and landslides. LiDAR produces a three dimensional point cloud of millions of points which gives spatial data on the scanned object, accurate to millimeters, in minutes. The point cloud can be exported to different formats which then can be analyzed using specialized software. The software used for LiDAR data processing was developed here at Missouri University of Science and Technology using C++ with two open source libraries: OpenCV and OpenG [Trademark]. The program aligns two point clouds and calculates the volume found in between. The volume is the rockfall over time between the two scan dates used. The rockfall volume data is then correlated with rockfall triggering events, such as freeze and thaw cycles, precipitation levels, and seismic (blasting) data. Very few rockfall volume correlations could be made with the rockfall triggering events at the outcrops tested, but further research should be done on the process with other types of rock outcrops. Some possible improvement areas are discussed in the last couple sections of this thesis. Also included are step-by-step instructions for reproducibility of the research --Abstract, page iii

Evaluation of Rock Fall Hazards using LiDAR Technology

Lidar (light detection and ranging) is a relatively new technology that is being used in many aspects of geology and engineering, including researching the potential for rock falls on highway rock cuts. At Missouri University of Science and Technology, we are developing methods for measuring joint orientations remotely and quantifying the raveling process. Measuring joint orientations remotely along highways is safer, more accurate and can result in larger and more accurate data sets, including measurements from otherwise inaccessible areas. Measuring the nature of rock raveling will provide the data needed to begin the process of modeling the rock raveling process. In both cases, terrestrial lidar scanning is used to generate large point clouds of coordinate triplets representing the surface of the rock cut. Automated algorithms have been developed to organize the lidar data, register successive images without survey control, and removal of vegetation and non-rock artifacts. In the first case, we look for planar elements, identify the plane and calculate the orientations. In the second case, we take a series of scans over time and use sophisticated change detection algorithms to calculate the numbers and volumes of rock that has fallen off the rock face

A Simple Method for Measuring Discontinuity Orientations from Terrestrial LIDAR Data

The measurement of discontinuity (joint) orientations is critical in assessing the stability of discontinuous rock slopes. The discontinuity orientations are used as input to all discontinuous modeling programs and methods, including kinematic screening methods and limited equilibrium sliding methods