地理科学进展 ›› 2021, Vol. 40 ›› Issue (9): 1570-1580.doi: 10.18306/dlkxjz.2021.09.011

• 无人机行业应用 • 上一篇    下一篇

基于无人机摄影测量的地形变化检测方法与小流域输沙模型研究

代文1,2,3(), 汤国安1,3,4, 胡光辉1,3,4, 杨昕1,3,4, 熊礼阳1,3,4,*(), 王雷5   

  1. 1.南京师范大学地理科学学院,南京 210023
    2.南京信息工程大学地理科学学院,南京 210044
    3.虚拟地理环境教育部重点实验室(南京师范大学),南京210023
    4.江苏省地理信息资源开发与利用协同创新中心,南京210023
    5.西北大学城市与环境学院,西安710069
  • 收稿日期:2020-09-04 修回日期:2020-12-08 出版日期:2021-09-28 发布日期:2021-11-28
  • 通讯作者: * 熊礼阳(1989— ),男,博士,副教授,研究方向为数字地形分析。E-mail: xiongliyang@njnu.edu.cn
    * 熊礼阳(1989— ),男,博士,副教授,研究方向为数字地形分析。E-mail: xiongliyang@njnu.edu.cn
    * 熊礼阳(1989— ),男,博士,副教授,研究方向为数字地形分析。E-mail: xiongliyang@njnu.edu.cn
    * 熊礼阳(1989— ),男,博士,副教授,研究方向为数字地形分析。E-mail: xiongliyang@njnu.edu.cn
    * 熊礼阳(1989— ),男,博士,副教授,研究方向为数字地形分析。E-mail: xiongliyang@njnu.edu.cn
  • 作者简介:代文(1995— ),男,博士生,研究方向为无人机摄影测量与地形分析。E-mail: dwdaerte@163.com
  • 基金资助:
    国家自然科学基金项目(41930102);国家自然科学基金项目(41971333);国家自然科学基金项目(41771415);江苏高校优势学科建设工程资助项目(164320H116)

Modelling sediment transport in space in a watershed based on topographic change detection by UAV survey

DAI Wen1,2,3(), TANG Guo'an1,3,4, HU Guanghui1,3,4, YANG Xin1,3,4, XIONG Liyang1,3,4,*(), WANG Lei5   

  1. 1. School of Geography, Nanjing Normal University, Nanjing ?210023, China
    2. School of Geographical Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China
    3. Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China
    4. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China
    5. College of Urban and Environmental Sciences, Northwest University, Xi'an 710069, China
  • Received:2020-09-04 Revised:2020-12-08 Online:2021-09-28 Published:2021-11-28
  • Supported by:
    National Natural Science Foundation of China(41930102);National Natural Science Foundation of China(41971333);National Natural Science Foundation of China(41771415);Priority Academic Program Development of Jiangsu Higher Education Institutions(164320H116)

摘要:

流域输沙过程是地貌学和地表动力学的重要研究内容,但传统的输沙过程监测方法仅能得到某个区域的总输沙率,无法推算其空间分布。论文以黄土高原绥德县窑家湾小流域为例,利用无人机摄影测量技术得到其2006年和2019年2期数字高程模型(DEM)并计算地形变化量;然后,根据质量守恒原理和多流向算法建立泥沙在空间上的输送模型,进而计算小流域输沙率的空间分布。实验结果表明,该模型能有效模拟泥沙在空间上的输送情况,输沙率出现质量不守恒的区域面积占比小于4%,且不守恒区域多为人类活动影响区。同时,论文讨论了DEM的选择和不同地形变化检测水平对模型结果的影响。当使用第一期DEM进行泥沙搬运路径推算时,质量不守恒区域的面积显著降低。使用误差空间分布图进行地形变化检测得到的输沙率结果鲁棒性更强。使用中误差进行地形检测得到的结果在不同置信度下变化较大。基于无人机地形变化检测的空间输沙模型能方便、快捷地提供详尽的输沙率空间分布,为地表过程研究带来了新的机遇。

关键词: 无人机摄影测量, 小流域侵蚀监测, 地表变形监测, 输沙率空间分布, 误差空间分布, 地表物质交换

Abstract:

Sediment transport rate, as an important indicator for studying Earth surface processes and for planning soil and water conservation, is a spatial variable. However, traditional monitoring methods can only obtain the global sediment transport rate in a certain area and are unable to map the spatial distribution of sediment transport rate. In this study, unmanned aerial vehicle (UAV) photogrammetry was used to obtain a two-phase digital elevation model (DEM) and calculate the amount of topographic change. In accordance with the principle of mass conservation and using a multi-flow direction algorithm, a spatial sediment transport model was established, by which the spatial sediment transport rate from a loess watershed was obtained. The results show that this method can effectively simulate the transportation of sediment in space. The area where the mass is not conserved is less than 4%, and the non-conserved areas are mostly those that are affected by human activities. The effects of DEM choice and the level of topographic change detection on the proposed model are also discussed. When DEM in the first phase is used to calculate the sediment transportation path, the area where the mass is not conserved is significantly reduced. The results of the spatial sediment transport model are more robust when a precision map is used to detect topographic changes, whereas the results from topographic changes detected by root mean square error (RMSE) greatly varied under different confidence levels. The proposed model can conveniently and quickly provide a detailed spatial distribution of sediment transport rate through UAV-based topographic change detection, which provides new perspectives for research of Earth surface processes.

Key words: UAV photogrammetry, soil erosion monitoring in a watershed, topographic change detection, spatial distribution of sediment transport rate, precision map, sediment transport