Abstract
Remote and close range sensing are well-suited methods for monitoring natural hazards such as landslides. In particular, assessing the behavior and the dynamics of landslides through aerial imagery can considerably reduce the social and economic impacts of such events. UAVs (Unmanned Aerial Vehicle) with digital cameras on board represent an efficient, cost-effective and reliable system for 3D mapping of landslides by photogrammetry. In this study, we present the first results of the UAV-based photogrammetric processing performed in June 2016 and aimed at digitally reconstructing the Corvara landslide (South Tirol, Italy) in 3D. The data acquisition was carried out using a RICOH GR compact camera onboard an octocopter UAV platform. The photogrammetric workflow included, first, a camera calibration and image orientation using well distributed control points. Second, a dense image-matching algorithm was adopted to derive dense point clouds featuring almost 400 million points and a mean spatial resolution in the range of 1.5 cm to 2 cm. This data are now useful to perform comparisons with previous flights in order to quantify the displacements of the landslide.