• 中国科技核心期刊
  • 荷兰《文摘与引文数据库》(Scopus)收录期刊

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

张勤军, 陈巧, 黄之巍, 等. 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. DOI: 10.19388/j.zgdzdc.2024.257
引用本文: 张勤军, 陈巧, 黄之巍, 等. 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. DOI: 10.19388/j.zgdzdc.2024.257
ZHANG Qinjun, CHEN Qiao, HUANG Zhiwei, et al. 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[J]. Geological Survey of China, 2025, 12(2): 120-128. DOI: 10.19388/j.zgdzdc.2024.257
Citation: ZHANG Qinjun, CHEN Qiao, HUANG Zhiwei, et al. 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[J]. Geological Survey of China, 2025, 12(2): 120-128. 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

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” 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” 桂地矿综研【2024】6号

“广西靖西市坡豆河流域岩溶碳汇调查评价” GXDK202405

详细信息
    作者简介:

    张勤军(1984—),男,正高级工程师,主要从事水文地质研究。Email:412941045@qq.com

    通信作者:

    康志强(1982—),男,正高级工程师,主要从事水文地质研究。Email:zqkang000@126.com

  • 中图分类号: P237

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

  • 摘要:

    为实现精细化识别岩溶山区高陡边坡危岩体,以广西罗城典型岩溶地貌区为例,综合运用机载激光雷达(light detection and ranging, LiDAR)、倾斜摄影测量、贴近摄影测量3种低空无人机遥感技术手段开展危岩体精细化调查工作。总结了基于点云数据的林下孤石和裂隙信息提取的方法,系统归纳了运用三维实景模型开展结构面产状信息提取、结构面特征参数信息提取的手段,探讨了岩溶地区高陡边坡危岩体识别和精细化调查方法,开展了研究区危岩体的精细化识别,共识别出34处危岩体。研究成果可为其他类似地区的危岩体识别工作提供技术参考。

    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-altitude 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 information 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.

  • 图  1   研究区和典型危岩体发育区位置

    Figure  1.   Location of the study area and typical development areas of dangerous rock masses

    图  2   不规则三角网滤波法原理

    Figure  2.   Principle of irregular triangulation filtering method

    图  3   危岩体裂隙提取与孤石识别示意图

    Figure  3.   Schematic diagram of crack extraction and solitary rock identification for dangerous rock masses

    图  4   “三点法”结构面测量

    Figure  4.   Three point method for structural plane measurement

    图  5   结构面其他信息获取

    Figure  5.   Obtaining of other information of the structural planes

    图  6   结构面分组示意图

    Figure  6.   Schematic diagram of structural plane grouping

    图  7   研究区结构面辨识

    Figure  7.   Identification of structural planes in the study area

    图  8   1#边坡J1结构面特征参数提取

    Figure  8.   Feature parameter extraction of J1 structural plane on slope 1#

    图  9   研究区危岩体解译分布

    Figure  9.   Distribution of interpreted dangarous rock masses in the study area

    图  10   危岩体识别及三维实景模型影像

    Figure  10.   Identification of dangerous rock masses and images of the three-dimensional real-scene model

    表  1   低空遥感数据获取情况

    Table  1   Data acquisition situation of low-altitude remote sensing

    数据类型 工作设备 数据采集主要参数 成果类型
    机载LiDAR D20+DVLiDAR20 点云密度60 pt/m2 DEM、数字表面模型(digital surface model, DSM)
    倾斜摄影测量 D200+ OP310 分辨率5 cm 倾斜三维实景模型、数字正射影像(digital orthophoto map, DOM)
    贴近摄影测量 DJI Phantom4RTK 分辨率5 mm 贴近三维实景模型
    下载: 导出CSV
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出版历程
  • 收稿日期:  2024-07-11
  • 修回日期:  2025-03-10
  • 网络出版日期:  2025-05-15
  • 刊出日期:  2025-03-31

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