QUANTIFYING THE SLOPE DEFORMATION OF A LASER POINT CLOUD ACQUIRED USING MOBILE MAPPING SYSTEM

In recent years, the increasing frequency of heavy short-duration rainfall has escalated the risk of slope collapse. Inspecting the slope to detect any deformation is crucial for preventing slope collapse. However, conventionally, these inspections are conducted using close visual inspection. As a result, the findings are primarily dependent on the experience and skill level of the inspection engineers. In this study, we used a mobile mapping system (MMS) that could efficiently acquire laser point clouds over a wide area and quantitatively evaluate the shape of the structures. Thereafter, the point cloud was used to quantify the slope deformation by applying the iterative closest point (ICP) algorithm. The effectiveness of this method in aiding slope inspection was evaluated by examining the direction and amount of slope deformation on two separate days. Thereafter, the obtained deformations were clarified by filtering them to remove point clouds, such as vegetation and vehicles. Based on the study findings, we expect the proposed method to play an important role in assisting slope inspection.