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干旱区地理 ›› 2021, Vol. 44 ›› Issue (2): 441-449.doi: 10.12118/j.issn.1000–6060.2021.02.15

• 地球信息科学 • 上一篇    下一篇

基于无人机的胡杨(Populus euphratica)结构参数获取技术研究

杨雪峰1,2(),昝梅1,2,木尼热·买买提1,2   

  1. 1.新疆师范大学地理科学与旅游学院,新疆 乌鲁木齐 830054
    2.新疆维吾尔自治区重点实验室“干旱区湖泊环境与资源实验室”,新疆 乌鲁木齐 830054
  • 收稿日期:2020-12-01 修回日期:2021-01-10 出版日期:2021-03-25 发布日期:2021-04-14
  • 作者简介:杨雪峰(1972-),男,副教授,硕士,从事干旱区资源环境遥感应用研究. E-mail:744157426@qq.com
  • 基金资助:
    国家自然科学基金(41761075);新疆师范大学校级科研平台招标课题资助(XJNURWJD062017B05)

Structural parameters acquisition technology of Populus euphratica based on UAV

YANG Xuefeng1,2(),ZAN Mei1,2,Munire MAIMAITI1,2   

  1. 1. College of Geography Science and Tourism, Xinjiang Normal University, Urumqi 830054, Xinjiang, China
    2. Xinjiang Key Laboratory of Lake Environment and Resources in Arid Zone, Urumqi 830054, Xinjiang, China
  • Received:2020-12-01 Revised:2021-01-10 Online:2021-03-25 Published:2021-04-14

摘要:

快速准确获取森林结构参数具有重要的科学意义。通过使用大疆精灵4 Pro无人机通过倾斜摄影测量和正射摄影测量方式获取塔里木河下游胡杨林样地的冠层高度模型,提出一种自适应窗口最大值算法来分析处理,获取了研究区胡杨(Populus euphratica)的树高、冠幅和株数等结构参数。最后,使用地面实测数据对以上结构数据进行精度评价。结果表明:(1) 自适应窗口最大值算法计算效果优于传统的固定窗口最大值算法。(2) 倾斜摄影测量方式获取的树高、冠幅和株数精度均优于正射摄影测量方式。(3) 倾斜摄影测量获取的结构数据与实测值比较,树高、冠幅和株数R2分别为0.9002,0.8403和0.9405,均方根误差分别是0.4457、0.6815和4.2500,证明使用消费级无人机可以有效获取单木尺度森林结构参数。

关键词: 胡杨, 结构参数, 自适应窗口最大值算法, 无人机, 倾斜摄影测量

Abstract:

Obtaining the structural parameters of forests accurately and quickly is of great scientific significance. The technologies of polarimetric and interferometric synthetic-aperture radar, high-resolution optical satellite remote sensing, spaceborne lidar, and multi-angle satellite remote sensing can effectively obtain forest structure regionally. However, it is challenging to obtain structural parameters on a single-tree scale using these technologies. The rapid development of unmanned aerial vehicles (UAVs) recently provides a new means to obtain forest structures. The ground images can be obtained using UAV ordinary cameras, and the ground point cloud can be obtained using structure from motion photogrammetry technology for 3D reconstruction, generating digital surface model, digital elevation model (DEM), and canopy height model (CHM). The local maximum algorithm is used to process CHM data. The key to the local maximum algorithm is to select an appropriate window size and find the largest grid value (seed point) in the window as the highest point of the tree crown to represent the tree. However, it is challenging to calculate the window size. One solution is to use the variable window method. In this study, the height and crown diameter of 49 Populus euphratica trees were measured in the lower reaches of the Tarim River, Xinjiang, China. The Populus euphratica were counted in a 251 hm2 grid, and a DJI Phantom 4 Pro was used to acquire the image data. The DJI Phantom 4 Pro is a consumer-grade UAV using oblique and ortho photogrammetry, respectively. An adaptive window maxima algorithm was proposed to analyze and process CHM data, obtaining the structural parameters of the Populus euphratica forest in the study area, such as tree height, crown diameter, and number of trees. The structural parameters extracted using oblique and ortho photogrammetry were compared and analyzed with field-measured data. The results and conclusions are (1) the adaptive window maxima algorithm and fixed window maximum algorithm (1.5-, 2.0-, 2.5-, and 3.0-m fixed windows, respectively) were used to process CHM data obtained using oblique photogrammetry to generate Populus euphratica seed points. The data are compared with the statistical data of 25 sample plots. The R2 of fixed window values vary widely from 0.7834 to 0.8261, indicating that we should choose an appropriate window size to achieve higher accuracy according to the actual situation of the region. While the R2 of the adaptive window maxima algorithm is the highest (0.8341), it can achieve higher accuracy because the algorithm reduces the window size dependence. (2) The tree height measured using oblique and ortho photogrammetry is overestimated, and the crown diameter is underestimated. The mean, median, and distribution of tree height and crown diameter obtained using ortho photogrammetry are closer to the field-measured values, indicating that oblique photogrammetry could achieve more accurate results than ortho photogrammetry. (3) The oblique photogrammetry and field-measured data were compared to determine the coefficients (R2) of tree height, crown diameter, and tree numbers per hectare (0.9002, 0.8403, and 0.9405, respectively). The root means squared error was 0.4457, 0.6815, and 4.2500, respectively. The results prove that it is effective to use a consumer-grade UAV to obtain forest structure parameters on a single-tree scale using an appropriate measurement method and processing algorithm.

Key words: Populus euphratica, structural parameters, adaptive window maxima algorithm, UAV, oblique photogrammetry