一种机载LIDAR数据估算森林蓄积参数的方法

doi:10.13466/j.cnki.lyzygl.2020.03.020

林业资源管理 ›› 2020, Vol. 0 ›› Issue (3): 105-110.doi: 10.13466/j.cnki.lyzygl.2020.03.020

一种机载LIDAR数据估算森林蓄积参数的方法

许粲¹(), 江腾达²

1.安徽广播电视大学六安分校,安徽六安 237000
2.北科天绘科技有限公司,安徽合肥 230000

收稿日期:2020-03-02 修回日期:2020-03-20 出版日期:2020-06-28 发布日期:2020-07-30
作者简介:许粲(1992-),男,安徽六安人,助教,学士,主要从事激光雷达点云算法和远程教育研究。Email: 1002485860@qq.com

A Method of Estimating Forest Stock Volume Parameters from Airborne LiDAR Data

XU Can¹(), JIANG Tengda²

1. LU'AN Open University,Anhui LU'AN 23700,China
2. Beike Tianhui Technology Co.,Ltd.Anhui Hefei 230000,China

Received:2020-03-02 Revised:2020-03-20 Online:2020-06-28 Published:2020-07-30

摘要/Abstract

摘要：

针对林业调查中的单株树木提取问题,提出一种基于机载激光雷达点云数据,采用局部最大值和噪点消除获取树冠顶点,利用分水岭分割方法提取单株树,根据样地树高和森林蓄积模型估算胸径和森林蓄积量的方法,与传统的人工现场勘测方法相比,具有更高的时间效率,减少了大量的人力成本。

关键词: 机载LIDAR, 局部最大值, 噪点消除, 分水岭分割, 单株树提取

Abstract:

Aiming at the problem of single tree extraction in forestry inventory,a method based on Airborne LiDAR point cloud data is proposed,which uses local maximum value and noise elimination to obtain crown vertex,and uses watershed segmentation method to extract single tree,estimating DBH and forest volume based on tree height and forest volume model.Compared with the traditional artificial field survey method,it has higher time efficiency and reduces a lot of labor cost.

Key words: airborne LiDAR, local maximum, noise elimination, watershed segmentation, single tree detection

中图分类号:

S758.51

许粲, 江腾达. 一种机载LIDAR数据估算森林蓄积参数的方法[J]. 林业资源管理, 2020, 0(3): 105-110.

XU Can, JIANG Tengda. A Method of Estimating Forest Stock Volume Parameters from Airborne LiDAR Data[J]. FOREST RESOURCES WANAGEMENT, 2020, 0(3): 105-110.

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参考文献 7

[1]	Moradi A, Satari M, Momeni M, et al. Individual tree of urban forest extraction from very high density lidar data[J]. Remote Sensing and Spatial Information Sciences, 2016,XLI(B3):337-343.
[2]	刘清旺, 李增元, 陈尔学, 等. 利用机载激光雷达数据提取单株木树高和树冠[J]. 北京林业大学学报, 2008,30(6):83-89.
[3]	Fieber K D, Davenport I J, Ferryman J M, et al. Analysis of full-waveform LiDAR data for classification of an orange orchard scene[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2013,82:63-82. doi: 10.1016/j.isprsjprs.2013.05.002
[4]	Strimbu V F, Strimbu B M. A graph-based segmentation algorithm for tree crown extraction using airborne LiDAR data[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2015,104:30-43. doi: 10.1016/j.isprsjprs.2015.01.018
[5]	Bulatov D, Wayand I, Schilling H. Automatic tree-crown detection in challenging scenarios[J]. Remote Sensing and Spatial Information Sciences, 2016,XLI(B3):575-582.
[6]	Kankare V, Vauhkonen J, Tanhuanpää T, et al. Accuracy in estimation of timber assortments and stem distribution-A comparison of airborne and terrestrial laser scanning techniques[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2014,97:89-97. doi: 10.1016/j.isprsjprs.2014.08.008
[7]	王玲, 王克瀚. 林分蓄积量估算方法研究[J]. 山东林业科技, 2017,47(01):68-72.

参数	数据1	数据2	数据3	数据4	样地一	样地二	样地三
平均株数/株	91	49	66	74	95	150	72
平均树高/m	15.6	18.0	13.6	13.2	15	18	16.4
平均冠径/m	2.2	3.1	2.7	2.4	—	—	—
平均胸径/cm	14.1	18.3	12.1	11.2	21.1	17	20.1
平均蓄积量/m³	12.9	11.7	5.5	5.1	—	—	—

一种机载LIDAR数据估算森林蓄积参数的方法

A Method of Estimating Forest Stock Volume Parameters from Airborne LiDAR Data

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