Abstract
Objectives: Traditional remote sensing methods are often limited by the complex terrain and the hardware equipment, which often leads to in-situ measurements that cannot comprehensively, accurately and quickly obtain the slope rock structure data sets. Unmanned aerial vehicle (UAV) oblique photogrammetry technology can obtain comprehensive information on rock structure. Methods: We describe a method for acquiring, visualizing, and extracting three-dimensional information of high slope rock structure based on the dense surface points. The oblique photogrammetric data acquired with UAV is considered and a multi-rotor drone with single-lens is used for aerial surveys to reconstruct the three-dimensional point cloud model of the high slope. The Hough normal algorithm and the HSV(hue, saturation, value) algorithm are used to build a visual three-dimensional rock mass structure model and the model is spherical k-means clustering to complete the automatic extraction of rock structure. Results: From the three-dimensional rock structure analysis, it is possible to quickly extract rock structure characteristics such as orientation, spacing and trace length by rendering the geometry of the three-dimensional slope face. Conclusions: Further research is being carried out in order to build blocky slope masses and identify the kinematic instability of the high limestone cliffs.
Translated title of the contribution | Application of Unmanned Aerial Vehicle Oblique Photogrammetry to Investigation of High Slope Rock Structure |
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Original language | Chinese |
Pages (from-to) | 1739 - 1746 |
Number of pages | 8 |
Journal | Geomatics and Information Science of Wuhan University |
Volume | 45 |
Issue number | 11 |
DOIs | |
Publication status | Published - 18 Nov 2020 |
Keywords
- 3D visualization model
- High slope
- HSV algorithm
- Rock structure
- Spherical k-means clustering
- Unmanned aerial vehicle oblique photogrammetry
ASJC Scopus subject areas
- Computer Science (miscellaneous)
- Earth-Surface Processes