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林业科学 ›› 2021, Vol. 57 ›› Issue (3): 181-188.doi: 10.11707/j.1001-7488.20210319

• 研究简报 • 上一篇    下一篇

点云数据双向选择单木提取与地面数据匹配方法

霍朗宁,张晓丽*   

  1. 北京林业大学精准林业北京市重点实验室 北京林业大学省部共建森林培育与保护教育部重点实验室 北京 100083
  • 收稿日期:2019-03-01 出版日期:2021-03-25 发布日期:2021-04-07
  • 通讯作者: 张晓丽
  • 基金资助:
    国家重点研发计划(2017YFD0600900)

The Method of Matching Single Tree Information Extracted by Point Cloud to the Reference Data from Field Work through Bidirectional Selection

Langning Huo,Xiaoli Zhang*   

  1. Precision Forestry Key Laboratory of Beijing Key Laboratory for Silviculture and Conservation of Ministry of Education, Beijing Forestry University Beijing 100083
  • Received:2019-03-01 Online:2021-03-25 Published:2021-04-07
  • Contact: Xiaoli Zhang

摘要:

目的: 基于双向选择判断原理,提出一种将激光雷达(LiDAR)点云数据提取到的单木信息与地面实测单木信息进行匹配的方法,以得到更为合理的信息匹配结果。方法: 采用机载LiDAR点云数据分割单木,提取单木位置、数量、树高和冠幅等信息,从LiDAR提取单木位置出发,依据树高和距离正向确定候选地面实测单木,再根据候选地面实测单木位置和距离信息逆向确认LiDAR提取单木是否为最合适的匹配对象木。结果: 以匹配精度、匹配后的单木树高和冠幅精度为判断指标,与邻域最高匹配法、最邻近匹配法和双因素匹配法相比,在匹配精度一致的情况下,双向选择判断法匹配的单木树高精度可从75.21%提升至91.01%,冠幅精度从60.50%提升至68.64%;在保证匹配信息精度一致的情况下,双向选择判断法可将匹配精度从传统方法的33.52%提升至61.11%。结论: 点云数据双向选择单木提取与地面数据匹配方法可快速、高效地将激光雷达点云数据提取到的单木信息与地面实测单木信息进行匹配,与传统方法相比,能够在高密度、多林层林分中发挥更高优势。

关键词: 机载LiDAR, 地面实测信息, 单木匹配, 信息匹配精度

Abstract:

Objective: Based on the principle of bidirectional selection and judgment, a method was proposed to reasonably match the individual tree information extracted from point cloud data(LiDAR) with the reference information measured by the field work. Method: Using airborne LiDAR point cloud data, individual tree information such as tree position, number, height, and crown diameter was extracted. Firstly, the candidate reference trees were selected according to the information of the LiDAR tree. Then whether such candidate trees were the most reasonable LiDAR trees from the reference tree or not were evaluated again. Result: The matching accuracy, the heights and crown diameters accuracy after matching were used as the accuracy indicators. Compared with the other three commonly used matching methods, the height accuracy of individual tree using the proposed matching method was increased from 75.21% to 91.01%, and the crown diameter accuracy was also increased from 60.50% to 68.64% under the conditions with the same matching accuracy. When the height and crown diameter accuracy were controlled with the same value, the proposed method improved the matching accuracy from 33.52% to 61.11% comparing to the traditional method. Conclusion: The proposed method in this paper could match the single tree information quickly and efficiently between the ones extracted by remote sensing and the reference information measured on the field work. Compared with the traditional method, it could show some superiority when used in high-density and multi-layer stands.

Key words: ALS, reference data from the field work, matching individual trees, accuracy of the information matching

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