Vol17 No.8: 1826-1839
【Title】Multitemporal UAV-based photogrammetry forlandslide detection and monitoringin a large area: a case studyin the Heifangtaiterrace in the Loess Plateau of China
【Author】XU Qiang; LI Wei-le*; JU Yuan-zhen; DONG Xiu-jun; PENG Da-lei
【Addresses】State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu 610059, China
【Corresponding author】LI Wei-le
【Citation】Xu Q, Li WL, Ju YZ, et al. (2020) Multitemporal UAV-based photogrammetry for landslide detection and monitoring in a large area: a case study in the Heifangtai terrace in the Loess Plateau of China. Journal of Mountain Science 17(8). https://doi.org/10.1007/s11629-020-6064-9
【Abstract】With high spatial resolution, on-demand-flying ability, and the capacity for obtaining three-dimensional measurements, unmanned aerial vehicle (UAV) photogrammetry is widely used for detailed investigations of single landslides, but its effectiveness for landslide detection and monitoring in a large area needs to be investigated. The Heifangtai terrace in the Loess Plateau of China is a loess terrace that is extremely susceptible to irrigation-induced loess landslides. This paper used UAV-based photogrammetry for a series of high-resolution images spanning over 30 months for landslide detection and monitoring of the terrace with an area of 32 km2. Dense and evenly distributed ground control points were established and measured to ensure the high accuracy of the photogrammetry results. The structure-from-motion (SfM) technique was used to convert overlapping images into orthographic images, 3D point clouds, digital surface models (DSMs) and mesh models. Using multitemporal differential mesh models, landslide vertical movements and potential landslides were detected and monitored. The results indicate that a combination of UAV-based orthophotos and differential mesh models can be used for flexible and accurate detection and monitoring of potential loess landslides in a large area.
【Keywords】Unmanned Aerial Vehicle; Loess Plateau; Landslide detection; Landslide monitoring; Differential mesh model; Vertical movement