无人机遥感数据处理模型的计算精度分析 ——以引黄入冀补淀工程水土保持监测为例

doi:10.16843/j.sswc.2019.02.015

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摘要无人机遥感技术为生产建设项目水土保持监测提供了新的技术手段，特别是在计算弃土场面积和弃土量等方面极大地提高了监测效率和精度，但不同的无人机遥感数据处理模型的计算精度存在差异。本研究旨在对各数据处理模型的精度进行对比。作者以引黄入冀补淀工程为依托，选取5个典型弃土场，构建6组无人机遥感数据处理模型：Pho-Glo、Pho-Loc、Pho-Con、Pix-Glo、Pix-Loc、Pix-Con，对每个弃土场的面积、弃土量进行计算，对比分析不同模型计算结果的精度。结果表明：计算面积精度最高的模型为Pix-Con，误差为1.23%，精度最低的模型为Pho-Glo，误差为5.57%；计算弃土量精度最高的模型为Pix-Con，误差为2.97%，精度最低的模型为Pho-Loc，误差为10.28%。建议在生产建设项目中推广使用Pix-Con无人机遥感数据处理模型。

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	阎世煜
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关键词 ：引黄入冀补淀工程, 水土保持监测方法, 无人机遥感技术, 无人机遥感数据处理模型

Abstract：[Background] The Unmanned Aerial Vehicle(UAV)remote sensing technology has provided a new technical mean for soil and water conservation monitoring in construction projects, especially in terms of the calculation of the area and volume of disposal ground, also greatly improved the efficiency and accuracy of monitoring. However, the accuracy of different models processing UAV remote sensing data varies a lot. Based on the Yellow River-to-Baiyangdian Water Transfer Project, this study selected 5 disposal grounds in Puyang, a city located in the plain area, as the research object. Since these 5 disposal grounds are similar in location and natural conditions, it is convenient for conducting comparative experiments and comparing the calculation accuracy of different models processing remote sensing data.[Methods] In this study, PhotoScan and Pix4D were used to process the UAV remote sensing data to obtain DOM and DSM images of each disposal ground. Global Mapper, LocaSpace Viewer and Context Capture were used to extract information from DOM and DSM images to calculate the area and volume of disposal grounds. Then 6 sets of models processing UAV remote sensing data were structured:Pho-Glo, Pho-Loc, Pho-Con, Pix-Glo, Pix-Loc and Pix-Con. Based on the actual value of construction organization, we quantified the errors of the area and volume of each disposal ground calculated by different models.[Results] 1) Using these 6 models:Pho-Glo, Pho-Loc, Pho-Con, Pix-Glo, Pix-Loc and Pix-Con, the calculation errors of disposal area were 5.57%, 5.05%, 4.84%, 1.69%, 3.06% and 1.23% respectively, and the errors of disposal volume were, 9.06%, 10.28%, 4.76%, 5.73%, 6.52% and 2.97% respectively. 2) When calculating the disposal area, using Pix4D for preliminary processing significantly reduced the error. There was no significant difference among Global Mapper, LocaSpace Viewer and Context Capture as for the information extraction. 3) When calculating the disposal volume, using Pix4D for preliminary treatment significantly reduced the error. There was no significant difference between Global Mapper and LocaSpace Viewer to calculate the volume of disposal grounds, while the accuracy of Context Capture was significantly higher than that of the others. 4) PhotoScan processed images more accurately when there was water on the surface and the DSM images were more consistent with the actual situation.[Conclusions] The accuracy of the 6 models are quite different, though all of them meet the requirements of relevant regulations. UAV has a bright application prospect in soil and water conservation monitoring for construction projects, which is more efficient and accurate than traditional monitoring methods when calculating the area and volume of disposal grounds. It is suggested that Pix-Con model processing UAV remote sensing data should be popularized in monitoring of construction projects.

Key words： the Yellow River-to-Baiyangdian Water Transfer Project soil and water conservation monitoring method UAV remote sensing technology model processing UAV remote sensing data

收稿日期: 2018-11-05

PACS:

S157

基金资助:水利部公益性行业科研专项"东北灌区节水灌溉生态效益评估"（201401001）

通讯作者: 王秀茹(1957-),女,博士,教授。主要研究方向:水土保持与荒漠化防治,流域管理。E-mail:wang-xr@163.com E-mail: wang-xr@163.com

作者简介: 阎世煜(1993-),男,硕士研究生。主要研究方向:水土保持与荒漠化防治。E-mail:yanshiyu@bjfu.edu.cn

引用本文:

阎世煜¹, 王秀茹¹, 王霄², 韩晓亮¹. 无人机遥感数据处理模型的计算精度分析 ——以引黄入冀补淀工程水土保持监测为例[J]. 中国水土保持科学, 2019, 17(2): 121-131.
YAN Shiyu, WANG Xiuru, WANG Xiao, HAN Xiaoliang. Accuracy analysis of model processing UAV remote sensing data: A case study of soil and water conservation monitoring for the Yellow River-to-Baiyangdian Water Transfer Project. SSWC, 2019, 17(2): 121-131.

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http://journal12.magtechjournal.com/Jweb_stbc/CN/10.16843/j.sswc.2019.02.015 或 http://journal12.magtechjournal.com/Jweb_stbc/CN/Y2019/V17/I2/121

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