长江科学院院报 ›› 2023, Vol. 40 ›› Issue (9): 188-194.DOI: 10.11988/ckyyb.20220394

• 水利信息化 • 上一篇    

基于机载LiDAR及无人机影像的高位危岩体调查和成因分析

夏雄彬1, 谯立家2, 许万忠2   

  1. 1.中国电建集团昆明勘测设计研究院有限公司,昆明 650051;
    2.昆明理工大学 国土资源工程学院,昆明 650093
  • 收稿日期:2022-04-18 修回日期:2022-07-18 出版日期:2023-09-01 发布日期:2023-09-01
  • 作者简介:夏雄彬(1981-),湖北通山人,正高级工程师,硕士,主要从事岩土工程专业研究工作。E-mail:58315378@qq.com
  • 基金资助:
    国家自然科学基金项目(41562016)

Investigation and Cause Analysis of Dangerous Rock Masses on High and Steep Slope Based on Airborne LiDAR and UAV Imagery

XIA Xiong-bin1, QIAO Li-jia2, XU Wan-zhong2   

  1. 1. Power China Kunming Engineering Corporation, Kunming 650051,China;
    2. Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming 650093,China
  • Received:2022-04-18 Revised:2022-07-18 Published:2023-09-01 Online:2023-09-01

摘要: 在水利水电工程中,危岩体常发育在高陡边坡的危险隐蔽地带,传统勘察测量方法存在精度低、勘察难度高等缺点,快速、便捷地识别高陡边坡危岩体具有重要的工程意义。以黄登水电站重要建筑物边坡开口线外危岩体隐患排查结果为研究基础,利用无人机倾斜摄影构建1∶500的三维实景模型,结合机载激光雷达(LiDAR)遥感测量技术获取研究区内高精度的LiDAR点云数据及光学影像数据等成果,搭载三维可视化遥感解译平台,建立危岩体解译标志,获取危岩体的结构面产状特征并开展野外详细调查及解译成果复核工作,复核工作证明前期遥感测量技术准确率强,解译成果可信度高。同时根据地理空间数据分析方法研究危岩体的发育分布规律及成因机制,得出研究区内危岩体主要发育在1 609~1 963 m高程,多数危岩体所在的边坡坡度为40°~70°,危岩体发育以正南向为主,并且河流水系与人类工程活动对危岩灾害的发生也具有一定影响。研究结果对水电库区高位危岩体的隐患识别及成因分析有重要参考价值。

关键词: 高位危岩体, 机载LiDAR, 无人机影像, 稳定性, 成因分析

Abstract: In water conservancy and hydropower projects, dangerous rock masses often develop in hidden areas of high and steep slopes, posing challenges for accurate surveying and measurement using conventional methods. Swiftly and conveniently identifying dangerous rock masses on such slopes is of significant engineering importance. To address this issue, we take the investigation findings of dangerous rock masses outside the opening line of slope for critical building at Huangdeng Power Station as the research basis. We constructed a 1∶500 scale 3D model of the actual scene using UAV (unmanned aerial vehicle) oblique photography. By using airborne LiDAR remote sensing measurement technology, we acquired high-precision LiDAR point cloud data and optical image data in the research area. By incorporating a 3D visual remote sensing interpretation platform, we established the interpretation marks for dangerous rock mass, allowing for the extraction of structural plane characteristics of these rock masses. Furthermore, we conducted in-depth field investigations and review of the interpretation results. Our review work confirms the robust accuracy of remote sensing measurement technology in the initial stage, with highly credible interpretation results. Furthermore, by employing a geospatial data analysis method, we explored the development distribution patterns and genesis mechanisms of dangerous rock masses. The findings demonstrate that dangerous rock masses in the study area predominantly develop in the elevation range from 1 609 m to 1 963 m and the slope gradient range from 40° to 70°, primarily facing the south direction. Additionally, dangerous rock disasters is also affected to some extent by river systems and human engineering activities. The research findings hold significant reference value for the identification and causal analysis of high-risk rock masses in hydropower reservoir areas.

Key words: dangerous rock mass, airborne LiDAR, unmanned aerial vehicle, stability, cause analysis

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