Three dimensional laser scanning, also known as Light Detection and Ranging (LiDAR) has quickly been expanding in its applications in the field of geological engineering due to its ability to rapidly acquire highly accurate three dimensional positional data. Recently is has been shown that LiDAR scanning can be easily integrated into an excavation sequence in an underground environment for the purpose of collecting rockmass and discontinuity information. As scans are often taken multiple times of the same environment, the next logical application of LiDAR scanning is for monitoring for change and deformation. Traditionally, deformation and change in an underground environment is measured using a series of five or more permanent control points installed around the profile of an excavation. Using LiDAR for profile analysis provides many benefits as compared to traditional monitoring techniques. Due to the high density of the point cloud data, the change in profile is able to be fully characterized, and areas of anomalous movement can easily be separated from overall closure trends. Furthermore, monitoring with LiDAR does not require the permanent installation of control points, therefore monitoring can be completed more quickly after excavation, and scanning is non-invasive therefore no damage is done during the installation of temporary control points. The main drawback of using LiDAR scanning for deformation monitoring is that the raw point accuracy is generally the same magnitude as the smallest level of deformations that need to be measured. To overcome this, statistical techniques for profile analysis must be developed. This thesis outlines the development one such method, called the Elliptical Fit Analysis (EFA) and LiDAR Profile Analysis (EFA) for tunnel and shaft convergence analysis. Testing of the EFA and LPA has proved the robustness of this technique in its ability to deal with accuracy and precision issues associated with LiDAR scanning. / Thesis (Master, Geological Sciences & Geological Engineering) -- Queen's University, 2012-05-15 13:24:28.398