We discuss here different challenges and limitations of surveying rock slope failures using 3-D reconstruction from image sets acquired from street view imagery (SVI). We show how rock slope surveying can be performed using two or more image sets using online imagery with photographs from the same site but acquired at different instances. Three sites in the French alps were selected as pilot study areas: (1) a cliff beside a road where a protective wall collapsed, consisting of two image sets (60 and 50 images in each set) captured within a 6-year time frame; (2) a large-scale active landslide located on a slope at 250m from the road, using seven image sets (50 to 80 images per set) from five different time periods with three image sets for one period; (3) a cliff over a tunnel which has collapsed, using two image sets captured in a 4-year time frame. The analysis include the use of different structure from motion (SfM) programs and a comparison between the extracted photogrammetric point clouds and a lidar-derived mesh that was used as a ground truth. Results show that both landslide deformation and estimation of fallen volumes were clearly identified in the different point clouds. Results are site- and software-dependent, as a function of the image set and number of images, with model accuracies ranging between 0.2 and 3.8m in the best and worst scenario, respectively. Although some limitations derived from the generation of 3-D models from SVI were observed, this approach allowed us to obtain preliminary 3-D models of an area without on-field images, allowing extraction of the pre-failure topography that would not be available otherwise.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)