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纸质出版日期： 2018-1 ，
录用日期： 2017-8-22
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张纯斌, 杨胜天, 赵长森, 娄和震, 张亦弛, 白娟, 王志伟, 管亚兵, 张远. 2018. 小型消费级无人机地形数据精度验证. 遥感学报, 22(1): 185–195
Zhang C B, Yang S T, Zhao C S, Lou H Z, Zhang Y C, Bai J, Wang Z W, Guan Y B and Zhang Y. 2018. Topographic data accuracy verification of small consumer UAV. Journal of Remote Sensing, 22(1): 185–195
低空遥感是近几年快速发展、应用非常广泛的新兴技术。小型消费级无人机集成可见光传感器
具有快速、灵活、高性价比等优势，受到广泛关注。然而目前有关该类无人机综合测量精度的研究不足，影响其进一步的推广应用。为此，本文开展了针对大疆(Phantom 3 professional)小型消费级无人机地形测量数据精度验证工作，设定6种航高(50 m、60 m、70 m、80 m、90 m和100 m)获取研究区的立体像对，生成影像点云(point cloud)、数字表面模型(DSM)以及数字正射影像图(DOM)等结果。在测量精度验证中，首先，在标准实验场均匀布设地面控制点(GCP)，利用差分GPS测出GCP的高精度3维坐标；然后，通过GCP对立体像对进行绝对定位；最后，利用误差统计方法分析上述结果的测量精度。验证表明，在50—100 m航高时，无人机影像结果的分辨率为2.22—4.23 cm，水平方向平均误差为±0.51 cm，垂直方向平均误差为±4.39 cm，相对均方根误差(RMSE)水平方向为±2.79 cm，垂直方向为±9.98 cm。研究结果表明，小型消费级无人机在飞控系统下的测量精度可达厘米级，这不仅为野外地理和生态调查工作者提供一种低成本、快速、灵活与精确获取地形信息的新型测量手段，同时还对使用此类无人机做航测应用及飞行参数设置提供一定参考。
Low-altitude remote sensing recently became a hot technology with rapid development and com-prehensive application. Small consumer UAV attracted wide attention with rapid
flexible
and cost-effective ad-vantages. Large professional UAV
which is vulnerable to weather conditions
requires professional manipulation and airspace application. These factors restrict its ability to access terrain data agilely and rapidly. A small consumer UAV can compensate for large professional UAV limitations. This study comprehensively verifies the accuracy of the data obtained through this type of UAV to improve application reliability. This study focuses on the precision verification of topographic data obtained by small consumer UAV (Phantom 3 Professional). Six kinds of flight heights (50 m
60 m
70 m
80 m
90 m
and 100 m) are set to acquire a stereoscopic image and generate Point Cloud
Digital Surface Model
and Digital Orthophoto Map. Ground Control Points (GCPs) are laid out uniformly in the standard experimental field to verify measurement accuracy
and their three-dimensional coordinates are derived using differential GPS with high-precision. The absolute position of the stereoscopic images is calibrated by GCPs. Finally
the measurement accuracy of the result is analyzed using the mean error and relative root mean square error (RMSE). Results show that the resolution of the UAV image is 2.22—4.23 cm for flight height 50–100 m and will decrease with increasing flight altitude. The mean error is ± 0.51 cm in the horizontal direction and ± 4.39 cm in the vertical direction. RMSE is ± 2.79 cm in the horizontal direction and ± 9.98 cm in the vertical direction. The errors in horizontal and vertical directions are within normal distribution
but the error range is larger in the vertical direction. Five or more images in the same area are recommended when shooting to avoid errors caused by insufficient image overlap and to generate high-quality data. Simultaneously
GCPs should be evenly laid in the survey area to ensure absolute positioning accuracy and should be found in more than five images. Experimental precision can be influenced by a number of factors
such as light and weather con-ditions and flight stability. The GCP selection
measurement method
and image spike processes include some errors. The research shows that the measurement accuracy of small consumer UAV can reach centimeter level with reliable flight control system condition; this condition provides a new measurement method for low-cost
fast
flexible
and accurate terrain information acquisition to geography and ecology researchers.
小型消费级无人机(UAV)精度验证地形测量差分GPS地面控制点(GCP)
small consumer UAVaccuracy verificationtopographic surveydifferential GPSGCP (Ground Control Points)
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