Identification of rocky ledge on steep, high slopes based on UAV photogrammetry

Xuan-hao Wang, Wei Cui (), Gui-ke Zhang and Hong Yang
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Xuan-hao Wang: Wuhan University
Wei Cui: Tianjin University
Gui-ke Zhang: Yalong River Hydropower Development Company, LTD
Hong Yang: Yalong River Hydropower Development Company, LTD

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2023, vol. 116, issue 3, No 17, 3224 pages

Abstract: Abstract The rocky ledge on steep, high slopes easily tends to instability under the action of gravity, earthquake, excavation unloading, etc., which threatens the safety of the constructors and water conservancy and hydropower engineering. The early investigation of rocky ledge is of great significance. Due to large areas of slopes and inconvenient traffic, manual investigation is time-consuming and dangerous. A rapid identification method for rock ledge is proposed based on unmanned aerial vehicle (UAV) photogrammetry. This method consists of generating the point cloud model of the slope by UAV photogrammetry, segmenting the point cloud model by kernel density estimation, clustering the point cloud by the density-based spatial clustering of applications with noise, and classifying the point clusters representing rocky ledges by the geometric feature. The slope near the Lianghekou hydropower station is used to study. The results show that the method can rapidly identify the rocky ledge on the whole slope scale, which reduces the risk and improves efficiency.

Keywords: Rocky ledge; UAV photogrammetry; Point cloud; Kernel density estimation; DBSCAN (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s11069-022-05803-z

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