Derivation of Three-Dimensional Displacement Vectors from Multi-Temporal Long-Range Terrestrial Laser Scanning at the Reissenschuh Landslide (Tyrol, Austria)

Abstract

Deep-seated gravitational slope deformations (DSGSDs) endanger settlements and infrastructure in mountain areas all over the world. To prevent disastrous events, their activity needs to be continuously monitored. In this paper, the movement of the Reissenschuh DSGSD in the Schmirn valley (Tyrol, Austria) is quantified based on point clouds acquired with a Riegl VZ®-6000 long-range laser scanner in 2016 and 2017. Geomorphological features (e.g., block edges, terrain ridges, scarps) travelling on top of the landslide are extracted from the acquired point clouds using morphometric attributes based on locally computed eigenvectors and -values. The corresponding representations of the extracted features in the multi-temporal data are exploited to derive 3D displacement vectors based on a workflow exploiting the iterative closest point (ICP) algorithm. The subsequent analysis reveals spatial patterns of landslide movement with mean displacements in the order of 0.62 ma − 1 , corresponding well with measurements at characteristic points using a differential global navigation satellite system (DGNSS). The results are also compared to those derived from a modified version of the well-known image correlation (IMCORR) method using shaded reliefs of the derived digital terrain models. The applied extended ICP algorithm outperforms the raster-based method particularly in areas with predominantly vertical movement.

Multiplatform-SfM and TLS Data Fusion for Monitoring Agricultural Terraces in Complex Topographic and Landcover Conditions

“…The limited number of TLS targets over the study area caused a minor tilting of the point clouds. Therefore, the ICP algorithm implemented in Cyclone was applied to enhance the registration of the point clouds, as in [117]. The Cyclone output errors for the final georeferencing process were RMS values of 0.053 and 0.079 m for Italian and Belgian sites, respectively.…”

3d Point Errors and Change Detection Accuracy of Unmanned Aerial Vehicle Laser Scanning Data

“…Besides reducing the workload in the field, this has advantages for applications in hazardous or inaccessible terrain (e.g. Pfeiffer et al, 2018).…”

Assessment of Landslide-Induced Displacement and Deformation of Above-Ground Objects Using Uav-Borne and Airborne Laser Scanning Data

“…It was introduced and applied in a previous study to assess displacements of a deep-seated landslide in an unbuilt area (Pfeiffer et al, 2018). The ICP-Matching algorithm iteratively matches the points of one point cloud (slave) to the points of the second point cloud (master) and builds point to plane correspondences (Chen and Medioni, 1992).…”

“…Analyses of gravitational mass movements based on laser scanning data in general rely on either (i) high-resolution digital elevation models (e.g. raster grids and triangulated irregular networks) Eeckhaut et al (2007); Monserrat and Crosetto (2008); Břežný and Pánek (2017) or (ii) approaches working with 3D point clouds (Gauthier et al, 2018;Mayr et al, 2017;Pfeiffer et al, 2018;Riquelme et al, 2015). The high availability of different sensing and mapping approaches make the combination and integration of information from different sensors and platforms necessary (Mandlburger et al, 2017;Zieher et al, 2018).…”