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低空无人机遥感技术在岩溶山区高陡边坡危岩体精细化识别中的应用

张勤军 陈巧 黄之巍 石树静 康志强 郑鹏 郑焕君 冯民豪

中国地质调查2025,Vol.12Issue(2):120-128,9.
中国地质调查2025,Vol.12Issue(2):120-128,9.DOI:10.19388/j.zgdzdc.2024.257

低空无人机遥感技术在岩溶山区高陡边坡危岩体精细化识别中的应用

Application of low-altitude unmanned aerial vehicle remote sensing technology in refined identification of dangerous rock masses on high and steep slopes in karst mountain areas

张勤军 1陈巧 2黄之巍 1石树静 1康志强 3郑鹏 2郑焕君 1冯民豪1

作者信息

  • 1. 广西壮族自治区地质调查院,广西 南宁 530023
  • 2. 京创智慧科技有限责任公司,四川 成都 610052
  • 3. 广西壮族自治区地质矿产勘查开发局,广西 南宁 530023
  • 折叠

摘要

Abstract

In order to accurately identify high and steep slope dangerous rock masses in karst mountainous areas,the authors took the typical karst landform area of Luocheng in Guangxi as an example,through three low-alti-tude unmanned aerial vehicle remote sensing techniques,that is airborne LiDAR,oblique photogrammetry,and close-range photogrammetry,to conduct detailed investigation of dangerous rock masses.The extracting informa-tion methods for isolated rocks and cracks under forests were summarized based on point cloud data,and the 3D real scene models were systematically summarized for extracting structural plane attitude information and structural plane characteristic parameter information.The identification and refined investigation methods of dangerous rock masses on high and steep slopes were discussed,and the refinement identification of dangerous rock masses was carried out,with a total of 34 dangerous rock bodies being identified.The research results could provide technical guidance for identifying hazardous rock masses in similar regions.

关键词

高陡边坡/危岩体/机载LiDAR/贴近摄影/遥感解译

Key words

high and steep slopes/dangerous rock masses/airborne LiDAR/close to photography/remote sens-ing interpretation

分类

天文与地球科学

引用本文复制引用

张勤军,陈巧,黄之巍,石树静,康志强,郑鹏,郑焕君,冯民豪..低空无人机遥感技术在岩溶山区高陡边坡危岩体精细化识别中的应用[J].中国地质调查,2025,12(2):120-128,9.

基金项目

广西科技重大专项"中国—柬埔寨典型岩溶关键带碳循环过程对比研究与应用示范(编号:桂科AA24206020)"、广西地质矿产勘查开发局"广西矿山水文地质勘查关键技术研究人才小高地(编号:桂地矿综研[2024]6 号)"及"广西靖西市坡豆河流域岩溶碳汇调查评价(编号:GXDK202405)"项目联合资助. (编号:桂科AA24206020)

中国地质调查

2095-8706

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