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控制点布设方案对无人机精度测量的影响及其应用以西北地区某尾矿坝地表沉降监测为例

戴嵩, 魏冠军, 梁斌

戴嵩, 魏冠军, 梁斌. 控制点布设方案对无人机精度测量的影响及其应用——以西北地区某尾矿坝地表沉降监测为例[J]. 中国地质灾害与防治学报, 2021, 32(5): 113-120. DOI: 10.16031/j.cnki.issn.1003-8035.2021.05-14
引用本文: 戴嵩, 魏冠军, 梁斌. 控制点布设方案对无人机精度测量的影响及其应用——以西北地区某尾矿坝地表沉降监测为例[J]. 中国地质灾害与防治学报, 2021, 32(5): 113-120. DOI: 10.16031/j.cnki.issn.1003-8035.2021.05-14
Song DAI, Guanjun WEI, Bin LIANG. Influence of control point number on UAV low-altitude photogrammetry and its application: A case study in subsidence monitoring of a tailing dam area in northwestern China[J]. The Chinese Journal of Geological Hazard and Control, 2021, 32(5): 113-120. DOI: 10.16031/j.cnki.issn.1003-8035.2021.05-14
Citation: Song DAI, Guanjun WEI, Bin LIANG. Influence of control point number on UAV low-altitude photogrammetry and its application: A case study in subsidence monitoring of a tailing dam area in northwestern China[J]. The Chinese Journal of Geological Hazard and Control, 2021, 32(5): 113-120. DOI: 10.16031/j.cnki.issn.1003-8035.2021.05-14

控制点布设方案对无人机精度测量的影响及其应用——以西北地区某尾矿坝地表沉降监测为例

基金项目: 国家自然科学基金项目:基于数据同化的高铁路基冻胀变形分析与时空预报研究(41964008);祁连山北部基岩河道宽度及共对构造抬升的响应研究(41771002);兰州交通大学“百名青年优秀人才培养计划”(152022);兰州交通大学优秀平台(201806)
详细信息
    作者简介:

    戴 嵩(1996-),男,山东德州人,建筑与土木工程专业,硕士研究生,目前从事无人机摄影测量及矿区灾害方面的研究。E-mail:731841719@qq.com

    通讯作者:

    魏冠军(1976-),男,甘肃平凉人,测绘工程专业,博士,教授,博士生导师,目前从事测量数据处理,地质灾害预警方面的研究。E-mail:77217808@qq.com

  • 中图分类号: V279+.2; P642.26

Influence of control point number on UAV low-altitude photogrammetry and its application: A case study in subsidence monitoring of a tailing dam area in northwestern China

  • 摘要: 近年来矿区地质灾害愈发严重。为准确监测尾矿坝地表沉陷变形,以地形地貌复杂的尾矿坝为研究实例,开展无人机低空摄影的形式进行监测数据收集。无人机原始POS数据存在系统误差的问题,文章利用误差改正模型纠正原始POS数据,并设计7种像控点布设方案,并对获取的尾矿坝高分辨率正射影像及DEM进行了精度评价。结果显示,当布设像控点数量为8个时,数据误差可以控制在3 mm以内;用两期DEM数据差值覆于地面模型,生成尾矿坝沉降图, 沿Y=350 m、Y=100 m和X=60 m剖面线做剖面图。基于测量结果发现,尾矿坝已出现整体沉降,其中南部尾矿坝下坡沉降范围最大,沉降范围在0.16 m之内。这次应用验证了在尾矿坝地表监测中无人机低空摄影测量的精度是可靠的。利用无人机的高精度成图方法对尾矿坝变形进行监测,对应急响应溃坝可能导致的绿洲地区及周边河湖生态灾难地形和矿区安全生产起到一定的预警作用。
    Abstract: Geological disasters in mining areas have become more and more serious in recent years. For accurate monitoring of surface subsidence with complex topography of tailings dam, based on the monitoring data of UAV(Unmanned Aerial Vehicle) low-altitude photogrammetry, the UAV original POS(Position and Orientation System) data error were improved, data from the error correction model was used to correct the original POS model and 7 kinds of control point layout were designed, high resolution evaluation was conducted on the orthogonal projection as well as the DEM(Digital Elevation Model) accuracy. The results show that when the number of image control points is 8, the data error can be controlled within 3 mm. The settlement map of the mining dam is generated by overlaying the ground model with the difference values of the two DEM data, and the profiles with Y=350 m, Y=100 m and X=60 m were made respectively. The measurement results indicated that the tailing dam has been subsided as a whole, and the southern mining dam has the largest subsidence area, which is within 0.16 m. This application verifies that the accuracy of UAV low altitude photogrammetry in mining dam surface monitoring is reliable. The high-precision mapping method of UAV is used to monitor the deformation of tailing dam, which plays a certain early warning role in the ecological disaster terrain of the oasis area and the surrounding rivers and lakes which may be caused by the emergency response of dam break and the safe production of mining area.
  • 图  1   无人机监测应用流程

    Figure  1.   UAV monitoring application process

    图  2   实验区研究范围

    Figure  2.   Research scope of the experimental area

    图  3   7种布设方案的控制点误差

    Figure  3.   Control point errors of seven layout schemes

    图  4   第一期POS数据纠正前正射影像与纠正后正射影像对比

    Figure  4.   Contrast of orthophoto before and after correction of POS data in the first phase

    图  5   两期控制点与DEM坐标点位误差

    Figure  5.   Error between control points in two phases and DEM coordinates

    图  6   两期DEM整体差值

    Figure  6.   Overall DEM difference between the two phases

    图  7   三维尾矿坝图

    Figure  7.   3D tailing dam

    图  8   尾矿坝整体沉降图

    Figure  8.   Overall settlement of mine dam

    图  9   X=60 m剖面沉降图

    Figure  9.   Settlement diagram of profile with X=60 m

    图  10   Y=350 m剖面沉降图

    Figure  10.   Settlement diagram of profile with Y=350 m

    图  11   Y=100 m剖面沉降图

    Figure  11.   Settlement diagram of profile with Y=100 m

    表  1   外方位元素的改正值和误差来源

    Table  1   Correction values and error sources of elements with external orientation

    外方位元素 改正值 改正误差
    Xi 奇数行带ΔXP 相反性误差
    偏移误差
    偶数行带ΔXP
    Yi 奇数行带ΔYP 相反性误差
    偏移误差
    偶数行带ΔYP
    Zi ΔZP 偏移误差
    Φi ΔΦP 视准轴误差
    Ωi ΔΩP
    Ki ΔKP
    下载: 导出CSV

    表  2   原始POS数据与纠正后POS数据对比

    Table  2   Comparison of original POS data and corrected POS data

    ID |ΔX|
    /m
    |ΔY|
    /m
    |ΔZ|/m |ΔΦP|
    /(°)
    |ΔΩP|/(°) |ΔKP|/(°)
    D35 0.013 0.046 0.093 0.18 0.13 0.87
    D36 0.056 0.099 0.034 0.20 0.43 0.50
    D42 0.074 0.060 0.089 0.47 0.59 0.61
    D43 0.025 0.054 0.051 0.78 0.78 0.84
    D92 0.076 0.012 0.060 0.14 0.11 0.26
    D93 0.047 0.083 0.081 0.28 0.25 0.55
    下载: 导出CSV
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  • 收稿日期:  2020-12-31
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