Surface change identification of exposed slope based on UAV inclined photogrammetry

doi:10.13474/j.cnki.11-2246.2023.0230

Abstract

Abstract: In order to overcome the defects of traditional manual slope investigation methods such as low efficiency, high risk and difficulty, the 3D reconstruction of slopes and disaster identification and classification method of UAV tilt photography is adopted for high and steep exposed slopes in this paper. The UAV multi-view sequence images are used to reconstruct the 3D realistic model of exposed slopes and unify the 3D models of slopes in different periods in the same coordinate system. The accuracy of the reconstructed model is better than 2 cm after experimental verification. The 3D point cloud data change detection algorithm based on point cloud and point cloud comparison algorithm analyzes the subtle differences between the point cloud models of two different periods and marks them in the 3D real-view model, and combines the PointNet++ classification neural network algorithm with the homemade point cloud data set to successfully realize the identification as well as classification of the marked areas, so as to realize the identification of slope landslides, The intelligent recognition of disaster scenes such as landslide, collapse and rockfall is successfully realized.

Key words: UAV tilt photography, slope hazard identification, 3D reconstruction, change monitoring

CLC Number:

P237

WANG Yuhao, LI Denghua, DING Yong. Surface change identification of exposed slope based on UAV inclined photogrammetry[J]. Bulletin of Surveying and Mapping, 2023, 0(8): 45-50.

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