| Citation: | Pang Xin, Yuan Ming, Lu Yuan, Du Wenjie, Wan Daochun, Li De, Ding Haifeng, Fu Xiaodong. Rapid identification method for the dangerous rock mass of a high-steep slope based on UAV LiDAR and ground imitation flight[J]. Bulletin of Geological Science and Technology, 2023, 42(6): 21-30. doi: 10.19509/j.cnki.dzkq.tb20220427
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In Southwest China, rockfall hazards are extremely developed in high mountains and deep valley areas with high and steep slopes. Due to the large elevation difference and steep slope, the dangerous rock mass on a high-steep slope has remarkable characteristics of suddenness. Thus, a rapid, accurate and convenient interpretation and identification for the source of dangerous rock mass becomes the primary problem of risk analysis of high-steep slopes. At present, the progress of detection makes image-based geological hazard interpretation gradually develop from visual identification to human-computer interactive identification. Among them, the UAV LiDAR system is widely used in geological disaster investigation by integrating both advantages of UAV carrier and LiDAR measurement technology, while the introduction of ground imitation flight technology can make the UAV LiDAR system adapt to complex terrain, obtaining high-precision and high-density point cloud data.
On this basis, a UAV survey was carried out on the East side slope of open-pit mine, and a high-precision DOM image and 3D point cloud model were obtained by processing the UAV survey data. As the supplementary materials of the DOM image, the geometric feature parameters of outcrop, including surface roughness and dip, are quantitatively extracted from the point cloud model. On this basis, a set of human-computer interactive identification for dangerous rock masses based on DOM images and geometric features is proposed.
The application to the East side slope of open-pit mine shows that by superimposing outcrop slope geometric features based on DOM images, the proposed human-computer interactive identification method can significantly improve the efficiency and accuracy of identification, and the identification of overhanging dangerous rock mass is much more robust than visual ones.
By combining innovative remote sensing technologies, the proposed method provides a fast and convenient solution for the identification of dangerous rock masses on high and steep rocky slopes.
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