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干旱区地理 ›› 2025, Vol. 48 ›› Issue (9): 1600-1611.doi: 10.12118/j.issn.1000-6060.2024.565 cstr: 32274.14.ALG2024565

• 地表过程研究 • 上一篇    下一篇

基于无人机激光雷达的青海共和盆地藏锦鸡儿(Caragana tibetica)灌丛沙堆形态测算

尚毅力(), 李悦, 肖锋军(), 南维鸽, 张智, 王利杰   

  1. 陕西师范大学地理科学与旅游学院,陕西 西安 710119
  • 收稿日期:2024-09-22 修回日期:2025-02-08 出版日期:2025-09-25 发布日期:2025-09-17
  • 通讯作者: 肖锋军(1984-),男,博士,副教授,主要从事风沙地貌学研究. E-mail: xiaofengjun@snnu.edu.cn
  • 作者简介:尚毅力(2001-),男,硕士研究生,主要从事风沙地貌学研究. E-mail: syl@snnu.edu.cn
  • 基金资助:
    国家自然科学基金项目(42071009);国家自然科学基金项目(42171004);国家自然科学基金项目(41930641);第二次青藏高原综合科学考察研究(2019QZKK0403);科技部科技基础资源调查专项(2022FY202304);陕西省2021年自然科学基础研究计划(定向委托)项目(2021JCW-17)

Morphological calculation of Caragana tibetica nebkhas based on UAV laser radar technology in Gonghe Basin, Qinghai Province

SHANG Yili(), LI Yue, XIAO Fengjun(), NAN Weige, ZHANG Zhi, WANG Lijie   

  1. School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, Shaanxi, China
  • Received:2024-09-22 Revised:2025-02-08 Published:2025-09-25 Online:2025-09-17

摘要:

利用无人机激光雷达技术对共和盆地龙羊峡水库西侧的300个藏锦鸡儿(Caragana tibetica)灌丛沙堆的形态参数、沙堆底面积和体积进行测量,目的是评价文献中各种估算灌丛沙堆底面积和体积公式的适用性并分析原因。 结果表明:(1) 无人机激光雷达能够对藏锦鸡儿灌丛沙堆的形态进行精准测量,藏锦鸡儿灌丛沙堆的长轴(L)、短轴(W)和高度(H)的平均相对误差为0.70%、1.13%和-1.67%,其相应的均方根误差为0.02 m、0.03 m和0.03 m;平面精度和三维精度的均方根误差分别为0.03 m和0.04 m,均满足精度要求。(2) 藏锦鸡儿灌丛沙堆的长轴、短轴和高度等形态参数变化幅度不大,变异系数在0.26~0.33之间。各形态参数之间呈显著相关(P<0.01),表明灌丛沙堆的形态是长、宽和高协同增长的结果。此外,灌丛沙堆表面的结皮、枯死灌丛、风蚀凹坑都说明灌丛沙堆由成熟期进入衰退期。(3) 藏锦鸡儿灌丛沙堆底面积公式π[(L+W)/4]2、πLW/4和LW/2的总相对误差分别为-0.79%、-1.26%和-37.14%,其中公式π[(L+W)/4]2和πLW/4适合本研究区。体积公式3πLWH/32、πLWH/12、LWH/6、πH{[3(L+W)/4]2+H2}/6和πLWH/6的总相对误差分别为-6.15%、-16.58%、-46.89%、59.14%和66.83%;修正后的体积公式πLWH/10的总相对误差为0.10%,且离散程度低,更适合本研究区。综上,在估算灌丛沙堆底面积和体积时需要同时注意植被类型、发育阶段、生境或沙源丰富度的影响,从而因地制宜选择适合的估算方法。

关键词: 灌丛沙堆, 无人机激光点云, 几何公式, 总相对误差

Abstract:

To explore the applicabilities of various estimation formulas for the morphological parameters of reported nebkhas and justify their selections, the morphological parameters, such as the bottom area and volume, of 300 Caragana tibetica nebkhas on the west of Longyangxia Reservoir (Gonghe Basin, Qinghai Province, China) were measured using the laser radar technology of an unmanned aerial vehicle (UAV). The results are summarized in four points. (1) UAV laser radars can accurately determine the morphologies of C. tibetica nebkhas, obtaining average relative errors of 0.70%, 1.13%, and -1.67% for the length axis (L), width axis (W), and height (H), respectively, with corresponding root-mean-square errors (RMSEs) of 0.02 m, 0.03 m, and 0.03 m, respectively. Additionally, the RMSEs of the plane and three-dimensional (3D) accuracy of the 3D model were 0.03 m and 0.04 m, respectively, satisfying accuracy requirements. (2) The L, W, and H of the C. tibetica nebkhas remained largely unchanged, and their variation coefficients were between 0.26 and 0.33. Additionally, these parameters exhibited a significant correlation (P<0.01), indicating that the morphologies of the nebkhas were determined by coordinated L, W, and H increases. Additionally, the crust, dead shrubs, and wind erosion pits on the surface of the nebkhas indicate that the nebkhas had evolved from the mature stage to the decline stage. (3) The following formulas were used to determine the bottom area of the C. tibetica nebkhas: π[(L+W)/4]2, πLW/4, and LW/2, obtaining total relative errors of -0.79%, -1.26%, and -37.14%, respectively. Among them, π[(L+W)/4]2 and πLW/4 were considered suitable for the study area. Further, the following formulas were used to determine their volume: 3πLWH/32, πLWH/12, LWH/6, πH{[3(L+W)/4]2+H2}/6, and πLWH/6, with total relative errors of -6.15%, -16.58%, -46.89%, 59.14%, and 66.83%, respectively. The modified formula, πLWH/10, yielded a total relative error of 0.10%, as well as a low dispersion degree, making it the most suitable formula for the study area. In summary, the estimation of the bottom areas and volumes of nebkhas requires the careful consideration of the influence of the vegetation type, development stage, habitat, or sand-source richness, as this would ensure the selection of appropriate estimation methods based on local conditions.

Key words: nebkhas, drone laser point cloud, geometric formula, total relative error