A new technique for modeling the geomorphology of a slow moving, soft-slope landslide using terrestrial LiDAR

Soft slope movement is a big problem whether it involves an engineered slope, one that is near infrastructure, or both. Active landslides that fail slowly sometimes allow ample time to affect remedial works. In order to plan effective remedial works, there needs to be a model of the entire geometry of the slide. This thesis describes a new approach to evaluate the morphology of slope geometry using Light Detection and Ranging (LiDAR) data obtained from simple targets strategically positioned on a slide body. The data was gathered in three-month intervals over a period of one year to allow enough time for any movement. Each scan produced tens of millions of points allowing a very detailed image to be used for processing. Proprietary research code was developed at Missouri University of Science and Technology to manipulate LiDAR point-cloud data and further modified to interpret the data gathered for this thesis. The code uses a mesh system that the scan data is transformed to match. The mesh system is nothing more than a grid onto which the data is projected and it allows the follow-up programs to reference specific cells easier. A minor amount of movement was detected over the course of a year and was consistent with what is expected for this type of landslide given the weather conditions for the year it was monitored. Furthermore, the calculated displacement is reasonably comparable to what was observed during ground-truthing. This process can be further enhanced to be useful in real-time monitoring of landslide hazard zones and allow for better mitigation (and less litigation) in the future. A detailed set of instructions are included in case this research should need to be reproduced or investigated further. --Abstract, page iii