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中国沙漠 ›› 2024, Vol. 44 ›› Issue (5): 170-181.DOI: 10.7522/j.issn.1000-694X.2024.00080

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基于无人机激光雷达的额济纳绿洲植被覆盖度监测及变化分析

张浪1(), 党国锋1, 鱼腾飞2,3(), 韩拓2,3, 殷一丹2, 陈勇4   

  1. 1.西北师范大学 地理与环境科学学院,甘肃 兰州 730070
    2.中国科学院西北生态环境资源研究院,干旱区生态安全与可持续发展重点实验室 /,甘肃 兰州 730000
    3.中国科学院西北生态环境资源研究院,阿拉善荒漠生态水文试验研究站,甘肃 兰州 730000
    4.内蒙古额济纳胡杨林国家级自然保护区管理局,内蒙古 额济纳旗 735400
  • 收稿日期:2024-04-01 修回日期:2024-05-29 出版日期:2024-09-20 发布日期:2024-10-15
  • 通讯作者: 鱼腾飞
  • 作者简介:鱼腾飞(E-mail: yutf@lzb.ac.cn
    张浪(1998—),男,贵州大方人,硕士研究生,主要从事无人机生态遥感方面的研究。E-mail: zhanglang9811@163.com
  • 基金资助:
    阿拉善盟科技计划项目(AMYY2021-08);内蒙古自治区关键技术攻关项目(2020GG0306)

Monitoring and change analysis of vegetation coverage in Ejin Oasis based on UAV-LiDAR

Lang Zhang1(), Guofeng Dang1, Tengfei Yu2,3(), Tuo Han2,3, Yidan Yin2, Yong Chen4   

  1. 1.School of Geography and Environmental Science,Northwest Normal University,Lanzhou 730070,China
    2.Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands /, Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou 730000,China
    3.Alxa Desert Eco-Hydrology Experimental Research Station, Northwest Institute of Eco-Environment and Resources,Chinese Academy of Sciences,Lanzhou 730000,China
    4.Administration of Populus euphratica Forest National Nature Reserve in Ejin Banner,Ejin Banner 735400,Inner Mongolia,China
  • Received:2024-04-01 Revised:2024-05-29 Online:2024-09-20 Published:2024-10-15
  • Contact: Tengfei Yu

摘要:

植被覆盖度是表征植被生长状况和生态系统变化的重要参数。为科学评估黑河生态输水工程的恢复成效,以额济纳绿洲胡杨林为研究对象,应用无人机挂载激光雷达系统同时获取超高分辨率(GSD<0.7 cm)可见光照片和超高密度激光雷达点云(3 000点·m-2),计算样地植被覆盖度,并与目视解译结果交互验证,据此建立植被覆盖度与植被指数的关系,以反演1986—2023年额济纳绿洲植被覆盖度变化。结果表明:(1)利用雷达点云数据计算的植被覆盖度与目视解译结果较为一致,R2=0.89,RMSE为0.07。相较于遥感的像元二分法,R2增加了0.36,RMSE降低了0.03,说明利用雷达点云可以准确地计算样地植被覆盖度;(2)研究区样地尺度植被覆盖度为0.11~0.60,平均值为0.34;基于激光雷达点云建立的植被覆盖度(y)与改进型土壤调节植被指数(x)最优模型为:y=2.53x-0.07 (R2=0.68,RMSE=0.12);(3)据此模型反演的1986—2000年额济纳绿洲植被覆盖度呈波动趋势,2001—2012年呈上升趋势,年增长率为0.31%,2013—2023年上升略有减缓,年增长率为0.19%。Theil-Sen Median趋势分析和M-K检验显示,生态输水工程实施后,植被覆盖由退化趋势逆转为改善趋势,表明黑河生态输水工程成效显著。

关键词: 遥感, 无人机激光雷达, 植被覆盖度, 额济纳绿洲, 生态输水

Abstract:

Vegetation coverage is the proportion of the vertical projected area of vegetation on the ground to the total area of a given statistical area, and it is an important parameter for characterizing vegetation growth and ecosystem changes. To scientifically evaluate the restoration effectiveness of the Heihe ecological water transfer project, this paper takes the Ejin Oasis Populus euphratica forest as the research object and uses a UAV-LiDAR system to simultaneously obtain ultra-high resolution (GSD<0.7 cm) visible light photos and ultra-high density LiDAR point clouds (3 000 points·m-2) to calculate and investigate the vegetation coverage of the sample land. The relationship between vegetation coverage and the remote sensing vegetation index was established to infer the change of vegetation coverage in the Ejin Oasis from 1986 to 2023. The results showed the following: (1) The vegetation coverage calculated by LiDAR point cloud data was consistent with the visual interpretation results (R2=0.89, RMSE=0.07). Compared with the pixel dichotomy method of remote sensing, R2 increased by 0.36 and RMSE decreased by 0.03, indicating that the LiDAR point cloud can accurately calculate the vegetation coverage of the plot. (2) The FVC of the study area varied from 0.11 to 0.60, with an average of 0.34. The optimal model of vegetation coverage (y)and improved soil-regulated Vegetation Index (x) based on LiDAR point cloud was: y=2.53x-0.07 (R2=0.68, RMSE=0.12). (3) According to the model inversion, the vegetation coverage of Ejin Oasis fluctuated during 1986-2000 and increased during 2001-2012, with an annual growth rate of 0.31%. The increase slowed down slightly during 2013-2023, with an annual growth rate of 0.19%. Theil-Sen median and M-K test trend analysis showed that after the implementation of the ecological water transport project, vegetation cover reversed from a degradation trend to an improvement trend, indicating that the Heihe ecological water transport project has achieved remarkable results.

Key words: remote sensing, UAV-LiDAR, fractional vegetation cover, Ejin Oasis, ecological water transport

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