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

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...

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Bibliographic Details
Published in:Journal of mountain science 2020-08, Vol.17 (8), p.1826-1839
Main Authors: Xu, Qiang, Li, Wei-le, Ju, Yuan-zhen, Dong, Xiu-jun, Peng, Da-lei
Format: Article
Language:English
Subjects:
Aerial photography
Detection
Digital imaging
Dimensional measurement
Earth and Environmental Science
Earth Sciences
Ecology
Environment
Finite element method
Flight
Geography
Landslides
Landslides & mudslides
Loess
Monitoring
Orthography
Photogrammetry
Spatial discrimination
Spatial resolution
Three dimensional models
Unmanned aerial vehicles
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Summary: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 highresolution images spanning over 30 months for landslide detection and monitoring of the terrace with an area of 32 km 2 . 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.
ISSN:1672-6316
1993-0321
1008-2786
DOI:10.1007/s11629-020-6064-9