• ISSN 1673-5722
  • CN 11-5429/P

高起伏区无人机摄影测量精度评估−以西秦岭光盖山-迭山断裂为例

张波 高泽民 王爱国 刘小丰 郑龙 袁道阳

张波,高泽民,王爱国,刘小丰,郑龙,袁道阳,2022. 高起伏区无人机摄影测量精度评估−以西秦岭光盖山-迭山断裂为例. 震灾防御技术,17(2):326−339. doi:10.11899/zzfy20220213. doi: 10.11899/zzfy20220213
引用本文: 张波,高泽民,王爱国,刘小丰,郑龙,袁道阳,2022. 高起伏区无人机摄影测量精度评估−以西秦岭光盖山-迭山断裂为例. 震灾防御技术,17(2):326−339. doi:10.11899/zzfy20220213. doi: 10.11899/zzfy20220213
Zhang Bo, Gao Zemin, Wang Aiguo, Liu Xiaofeng, Zheng Long, Yuan Daoyang. Accuracy Assessment of UAV Photogrammetry in High-Relief Area−A Case Study from Guanggaishan-Dieshan Fault in West Qinling Mountain[J]. Technology for Earthquake Disaster Prevention, 2022, 17(2): 326-339. doi: 10.11899/zzfy20220213
Citation: Zhang Bo, Gao Zemin, Wang Aiguo, Liu Xiaofeng, Zheng Long, Yuan Daoyang. Accuracy Assessment of UAV Photogrammetry in High-Relief Area−A Case Study from Guanggaishan-Dieshan Fault in West Qinling Mountain[J]. Technology for Earthquake Disaster Prevention, 2022, 17(2): 326-339. doi: 10.11899/zzfy20220213

高起伏区无人机摄影测量精度评估−以西秦岭光盖山-迭山断裂为例

doi: 10.11899/zzfy20220213
基金项目: 国家自然基金青年基金(41602225);第二次青藏高原综合科学考察研究项目(2019QZKK0901);中国地震局地震预测研究所基本科研项目(2021IESLZ06、2020IESLZ02、2019IESLZ03、2018IESLZ02)
详细信息
    作者简介:

    张波,男,生于1986年。博士,副研究员。主要从事新生代构造与活动构造研究。E-mail:kjwxn999@163.com

    通讯作者:

    王爱国,男,生于1972年。研究员。主要从事地震地质、工程地震及数值模拟方面的研究。E-mail:waguo2008@163.com

Accuracy Assessment of UAV Photogrammetry in High-Relief Area−A Case Study from Guanggaishan-Dieshan Fault in West Qinling Mountain

  • 摘要: 经过近10年的迅速发展,无人机摄影测量已成为活动构造研究的常用方法之一。但对于无人机摄影测量的精度评估,尤其是高起伏地区的精度评估存在不足。为此,选择白龙江北岸光盖山-迭山断裂沿线的黑峪寺、化马村,开展无人机摄影测量,并构建正射影像(DOM)和数字地表模型(DSM),配合差分GPS测绘进行校正和精度验证。通过对比实测控制点和图像提取点分析点精度,通过对比实测剖面与提取剖面分析剖面精度。研究结果表明,未经控制点校正的图像提取点与实测点存在较大误差,水平误差为5~8 m,垂直误差为几十米至上百米,但通过少数控制点校正后,点精度可达20 cm以内;6条实测剖面与提取剖面(提取自控制点校正后的图像)平均垂直精度总体为分米级,即0.16~0.65 m,标准差为0.13~0.69 m,略低于低起伏区的精度,对于测量条件恶劣的高起伏区,该精度是可接受的;异常高的垂直误差常出现在地形突变、低矮植被密集、行走困难等测量条件不理想位置。图像控制点中心点的准确识别、提取剖面线的修正准确性等因素也会影响精度评估的可靠性。
  • 图  1  西秦岭白龙江流域地形地貌及测点分布

    Figure  1.  Topography and measure sites distribution in Bailongjiang watershed, West Qinling

    图  2  无人机摄影测量原理

    Figure  2.  Schematic diagram of UAV photogrammetry

    图  3  黑峪寺无人机摄影测量构建的DOM和DSM

    Figure  3.  DOM and DSM of Heiyusi site constructed by UAV Photogrammetry

    图  4  黑峪寺地形剖面分布

    Figure  4.  Distribution of topographical profiles at Heiyusi site

    图  5  黑峪寺P1实测剖面与提取剖面对比

    Figure  5.  Comparison of P1 in Heiyusi between measured profiles and extraction profiles

    图  6  黑峪寺P2实测剖面与提取剖面对比

    Figure  6.  Comparison of P2 in Heiyusi between measured profiles and extraction profiles

    图  7  黑峪寺P3实测剖面与提取剖面对比

    Figure  7.  Comparison of P3 in Heiyusi between measured profiles and extraction profiles

    图  8  化马村无人机摄影测量

    Figure  8.  UAV Photogrammetry of Huama site

    图  9  化马村地形剖面分布

    Figure  9.  Distribution of Topographical profiles in Huama site

    图  10  化马村P1实测剖面与提取剖面对比

    Figure  10.  Comparison of P1 in Huama between measured profiles and extraction profiles

    图  11  化马村P2实测剖面与提取剖面对比

    Figure  11.  Comparison of P2 in Huama between measured profiles and extraction profiles

    图  12  化马村P3实测剖面与提取剖面对比

    Figure  12.  Comparison of P3 in Huama between measured profiles and extraction profiles

    表  1  黑峪寺和化马村测量情况

    Table  1.   Measurements of Heiyusi and Huama site

    工作点飞行高度/
    m
    测量面积/
    km2
    图像重叠度/
    %
    照片数量/张控制点数目/个点云密度/
    点·m−2
    正射影像(DOM)
    分辨率/cm
    数字地表模型
    (DSM)分辨率/cm
    黑峪寺124.00.725约701 1601231.44.4617.8
    化马村98.60.385约70427747.03.6514.6
    下载: 导出CSV

    表  2  黑峪寺未校正图像提取控制点与差分GPS实测控制点水平误差和垂直误差

    Table  2.   Horizontal and vertical errors between uncorrected image extraction points and DGPS measured points

    控制点未校正图像提取控制点差分GPS实测控制点水平误差/m垂直误差/m
    经度/°纬度/°高度/m经度/°纬度/°高度/m
    1104.186 256 033.924 494 02 265.156104.186 241 133.924 436 32 152.306.54112.85
    2104.186 157 033.923 752 02 236.890104.186 139 133.923 690 02 125.357.08111.54
    3104.185 135 033.924 406 02 240.789104.185 117 633.924 343 72 128.937.1111.86
    4104.184 937 033.925 042 02 246.660104.184 919 933.924 979 42 133.697.12112.97
    5104.184 051 033.924 445 02 216.075104.184 030 333.924 377 22 104.697.76111.38
    6104.184 389 033.925 279 02 244.573104.184 371 833.925 216 12 131.537.16113.05
    7104.184 360 033.926 269 02 275.363104.184 346 333.926 211 82 160.586.47114.79
    8104.183 976 033.926 130 02 266.602104.183 961 133.926 071 92 152.416.59114.19
    9104.183 428 033.925 507 02 263.471104.183 411 833.925 446 62 150.936.86112.54
    10104.183 103 033.926 348 02 279.589104.183 087 833.926 292 72 165.806.29113.79
    11104.182 400 033.926 389 02 288.628104.182 384 833.926 333 72 175.406.29113.23
    12104.182 916 033.927 011 02 311.029104.182 903 333.926 961 32 196.415.64114.62
    下载: 导出CSV

    表  3  经6个控制点校正后提取的检验点坐标与实测坐标对比

    Table  3.   Comparison between six control points-corrected test points and measured points

    检验点从DOM和DSM提取坐标差分GPS实测控制点水平误差/m垂直误差/m
    经度/°纬度/°高度/m经度/°纬度/°高度/m
    2104.186 140 033.923 689 02 125.46104.186 139 133.923 690 02 125.350.150.11
    4104.184 920 033.924 981 02 133.82104.184 919 933.924 979 42 133.690.20.13
    6104.184 371 033.925 217 02 131.74104.184 371 833.925 216 12 131.530.140.22
    8104.183 960 033.926 072 02 152.54104.183 961 133.926 071 92 152.410.080.13
    11104.182 385 033.926 335 02 175.32104.182 384 833.926 333 72 175.400.170.07
    12104.182 903 033.926 960 02 196.22104.182 903 333.926 961 32 196.410.150.19
    下载: 导出CSV

    表  4  化马村未校正图像提取控制点与差分GPS实测控制点水平误差和垂直误差

    Table  4.   Directional error at Huama site between extraction points from uncorrected images and measured points

    控制点未校正图像提取控制点差分GPS实测控制点水平误差/m垂直误差/m
    经度/°纬度/°高度/m经度/°纬度/°高度/m
    1104.540 325 033.741 176 01 556.67104.540 28833.741 114 41 594.247.6537.57
    2104.541 607 033.741 010 01 532.95104.541 56733.740 947 41 569.417.9036.46
    3104.540 270 033.740 160 01 512.82104.540 22633.740 100 61 550.567.7537.74
    4104.540 635 033.739 285 01 467.24104.540 58533.739 227 61 503.287.8636.04
    5104.540 810 033.738 124 01 469.00104.540 76133.738 065 91 506.097.8937.09
    6104.541 360 033.739 435 01 500.42104.541 31533.739 375 31 537.037.8436.60
    7104.542 265 033.740 881 01 536.25104.542 22433.740 818 01 572.047.9735.79
    下载: 导出CSV
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  • 收稿日期:  2019-07-19
  • 刊出日期:  2022-06-30

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