Abstract
Multi-temporal high-density terrestrial laser scanning (TLS) datasets are processed to delineating possible movements from terrain surfaces and trees. Terrain surface movements are estimated with the help of segmentation and random sample consensus (RANSAC) algorithm. Tree movements are interpreted by iterative closest point (ICP) solved translations and rotations of tree point clouds. The capabilities of the proposed methodology were tested using a case study of the Slumgullion landslide, where the trees without clear trunks cover the terrain surfaces. The displacements from the terrain surfaces and trees are similar with the results observed using our global positioning system (GPS) and historic results.
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