UNDERSTANDING SLOPE MOVEMENTS FROM TEMPORAL TERRESTRIAL LASER SCANS

Abstract

In recent times, surveying techniques, particularly the use of terrestrial laser scanners (TLS), have gained prominence for measuring surface changes through the comparison of 3D point clouds. Slope movements determination using Lidar technology has become an important aspect in disaster miti-gation. Change detection will be the greatest preventive method for landslide occurrence. In this work, the study of behavior of landslides of Byasi and Rampur in Uttarakhand is determined using point cloud data. The instrument used is FARO S350+ TLS, data collected in such a way that Byasi landslide covers two monsoon cycles in which three raw lidar data was acquired, same way Rampur landslide covers one monsoon cycle in which two raw data was acquired. These different time peri-ods data are used to determine the change using change detection algorithms like Cloud to Cloud(C2C), Cloud to Mesh(C2M) and Multi Scale Model to Model Cloud Comparison(M3C2). The above change detection algorithms are compared to one another. This gives an idea to interpret the change caused in the landslide and its magnitude. As a result, all these change detection algo-rithms are applied to 2 landslides (Byasi and Rampur) and determining the impact of terrain rough-ness. Among all the three change detection algorithm M3C2 works on any type of terrain irrespective of its roughness and shows the soil deposition in the form of separate point cloud. Where C2C and C2M don’t work on irregular terrain and gives better results in flat surfaces. Comparing C2C and C2M algorithms, even though the change detection process of both algorithms is same C2C is giving reasonable results due to the irregular mesh formation from point clouds.