测绘学报 ›› 2023, Vol. 52 ›› Issue (8): 1342-1354.doi: 10.11947/j.AGCS.2023.20210698

• 摄影测量学与遥感 • 上一篇    下一篇

机载LiDAR监测黄土高原土壤侵蚀的能力评估

李朋飞, 李豆, 胡晋飞, 姚顽强, 臧宇哲   

  1. 西安科技大学测绘科学与技术学院, 陕西 西安 710054
  • 收稿日期:2021-12-16 修回日期:2022-07-24 发布日期:2023-09-07
  • 通讯作者: 胡晋飞 E-mail:jinfeih@xust.edu.cn
  • 作者简介:李朋飞(1986-),男,博士,教授,研究方向为地貌遥感与水土保持。E-mail:pengfeili@xust.edu.cn
  • 基金资助:
    国家自然科学基金(41977059;U2243211);陕西省自然科学基础研究计划(2022JQ-259);陕西省教育厅资助项目(22JK0463)

Assessing the ability of airborne LiDAR to monitor soil erosion on the Chinese Loess Plateau

LI Pengfei, LI Dou, HU Jinfei, YAO Wanqiang, ZANG Yuzhe   

  1. College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China
  • Received:2021-12-16 Revised:2022-07-24 Published:2023-09-07
  • Supported by:
    The National Natural Science Foundation of China (Nos. 41977059; U2243211); The Natural Science Basic Research Program of Shaanxi (No. 2022JQ-259); Grant from Shaanxi Provincial Department of Education (No. 22JK0463)

摘要: 黄土高原土壤侵蚀严重、地形破碎复杂。受限于监测技术,以往侵蚀研究多基于径流小区开展,流域尺度的土壤侵蚀定量研究较少。机载激光雷达(LiDAR)技术为黄土高原流域尺度的土壤侵蚀高效监测提供了可能,然而其监测复杂地形变化的不确定性有待考究,导致其监测土壤侵蚀的能力缺乏深入研究。鉴于此,本文以黄土高塬沟壑区董庄沟流域内典型坡沟系统为研究区,连续获取地形无变化时段内4架次无人机LiDAR点云并生成DEM。在此基础上,定量评估了不同架次DEM求差(DoD)不确定性的空间分布特征;对比分析了DoD不确定性量级(即DoD不确定性绝对值,DoDua)与文献中不同类型土壤侵蚀所致地形变化量,初步确定机载LiDAR监测土壤侵蚀的能力。结果表明:①不同架次间DoD不确定性差异不显著,且整体空间分布和量级相近,仅局部存在明显差异;②梁峁坡区域DoDua为0.023~0.034 m,明显小于沟谷坡区域的0.057~0.077 m,切沟DoD不确定性的极值大多位于切沟的陡峭沟壁。DoDua越大,面积占比越小,其中0.05 m以下占比超40%,大于0.3 m占比小于7%;③基于无人机LiDAR点云,采用DoD方法可监测场次暴雨引起的切沟和冲沟侵蚀、浅层滑坡和中/深层滑坡,有可能监测到浅沟侵蚀,但不适合用于监测细沟侵蚀。结果可为复杂地形区域流域尺度土壤侵蚀高效监测和机理研究提供参考。

关键词: 土壤侵蚀监测, 流域尺度, 黄土高原, 机载LiDAR, DoD不确定性

Abstract: The Chinese Loess Plateau has been widely acknowledged as one of the world's mostly eroded areas and thus characterized by a fragmented and complex terrain. During the past decades, various monitoring methods, such as field investigations, erosion pins, manipulation experiments and tracer studies, have been employed to monitor soil erosion on the Loess Plateau. However, due to the limitation in the monitoring range of the above methods, previous soil erosion studies have been primarily undertaken at an erosion plot scale, while the catchment scale erosion monitoring was seriously lacking. In recent years, emerging remote sensing technologies, such as airborne light detection and ranging (LiDAR), have provided a promising means for an effective monitoring of soil erosion process over a large area (i.e. the catchment scale). However, little was known about the uncertainty of topographic changes detected by the airborne LiDAR for topographically complex areas, and thus the ability of airborne LiDAR to monitor soil erosion remained unclear. In the study, four airborne LiDAR flights were undertaken during a period without topographic change using an unmanned aerial vehicle (UAV) platform to acquire point clouds for a typical slope-gully system (consisting of hillslopes and gully slopes) in a small catchment (i.e. Dongzhuanggou) of the gullied Loess Plateau. Digital elevation models (DEMs) were produced based on the acquired point clouds using the triangle irregular network (TIN) algorithm. The uncertainty of topographic change detections were then derived as the DEM of difference (DoD) through subtracting the DEMs derived using the point clouds acquired by different flights from one another. The spatial pattern of the DoD uncertainty for the slope-gully system was investigated, while the ability of airborne LiDAR to detect soil erosion was assessed through comparing the magnitude of DoD (DoDua) with soil erosion rates collected from literature. Results showed that ① The DoDua for different flight combination was generally insignificant, while the spatial pattern of DoD uncertainty derived based on different flight combinations was similar, with apparent difference only emerging in certain places. ② The DoDua on the hillslope ranged between 0.023 m and 0.034 m, which was much lower than that of gully areas (0.057 m~0.077 m). The peak values of DoDua were normally found on steep-sloping gully walls. The area percentage decreased with the increase of DoDua, with a<0.05 m DoDua occupying over 40% while a>0.3 m DoDua accounting for less than 7% of the study area. ③ In terms of a comparison of DoDua and measured soil erosion rates, the UAV LiDAR was found to be able to detect soil erosion of permanent gullies at an event scale and deep-seated/shallow landslides. The results also showed that the UAV LiDAR may be able to monitor erosion of shallow (ephemeral) gullies, and was not able to monitor rill erosion. Our results provided a useful reference for the catchment-scale soil erosion monitoring and erosion process studies over topographically complex areas.

Key words: soil erosion monitoring, catchment scale, Loess Plateau, airborne LiDAR, DoD uncertainty

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