SENSOR- AND SCENE-GUIDED INTEGRATION OF TLS AND PHOTOGRAMMETRIC POINT CLOUDS FOR LANDSLIDE MONITORING
- 1Institute for Interdisciplinary Mountain Research, Austrian Academy of Sciences, Technikerstr. 21a, 6020 Innsbruck, Austria
- 23D Optical Metrology (3DOM) Unit – Bruno Kessler Foundation (FBK), Via Sommarive 18, 38123 Trento, Italy
- 3Institute for Earth Observation, Eurac Research, Viale Druso 1, 39100 Bolzano, Italy
- 4ESA Climate Office, ECSAT, Fermi Avenue, Harwell Campus, Didcot, Oxfordshire, OX11 0FD, UK
Keywords: Data integration, Landslide monitoring, Terrestrial laser scanning, Unmanned Aerial Vehicle, Photogrammetry
Abstract. Terrestrial and airborne 3D imaging sensors are well-suited data acquisition systems for the area-wide monitoring of landslide activity. State-of-the-art surveying techniques, such as terrestrial laser scanning (TLS) and photogrammetry based on unmanned aerial vehicle (UAV) imagery or terrestrial acquisitions have advantages and limitations associated with their individual measurement principles. In this study we present an integration approach for 3D point clouds derived from these techniques, aiming at improving the topographic representation of landslide features while enabling a more accurate assessment of landslide-induced changes. Four expert-based rules involving local morphometric features computed from eigenvectors, elevation and the agreement of the individual point clouds, are used to choose within voxels of selectable size which sensor’s data to keep. Based on the integrated point clouds, digital surface models and shaded reliefs are computed. Using an image correlation technique, displacement vectors are finally derived from the multi-temporal shaded reliefs. All results show comparable patterns of landslide movement rates and directions. However, depending on the applied integration rule, differences in spatial coverage and correlation strength emerge.