基于离散点云数据的森林冠层高度模型插值方法

doi:10.11707/j.1001-7488.20160910

林业科学 ›› 2016, Vol. 52 ›› Issue (9): 86-94.doi: 10.11707/j.1001-7488.20160910

基于离散点云数据的森林冠层高度模型插值方法

段祝庚¹, 肖化顺¹, 袁伟湘²

1. 中南林业科技大学理学院长沙 410004;
2. 湖南省岳阳市平江县林业局岳阳 414500

收稿日期:2015-12-03 修回日期:2016-07-07 出版日期:2016-09-25 发布日期:2016-10-20
通讯作者: 肖化顺
基金资助:
中南林业科技大学人才引进科研启动基金项目（2015YJ036）；林业公益性行业科研专项“闽楠、青冈栎次生林提质增量关键技术研究与示范”（201504301）。

Comparison of Interpolation Methods of Forest Canopy Height Model Using Discrete Point Cloud Data

Duan Zhugeng¹, Xiao Huashun¹, Yuan Weixiang²

1. School of Sciences, Central South University of Forestry and Technology Changsha 410004;
2. Forestry Bureau of Pingjiang County, Yueyang City, Hunan Province Yueyang 414500

Received:2015-12-03 Revised:2016-07-07 Online:2016-09-25 Published:2016-10-20

摘要/Abstract

摘要： [目的] 基于森林区域离散点云特点，利用不同插值方法构建冠层高度模型，并对不同插值方法进行比较、分析和评价，为森林冠层高度模型插值方法选择提供参考。[方法] 以30 m×30 m 样方离散点云数据为试验数据，采用开源软件SAGS-GIS利用B样条插值（B-Spline）、普通克里金插值法（OK）、线性插值三角网法（TLI）、反距离加权插值法（IDW）4种插值方法分别构建森林冠层高度模型，对森林冠层高度模型的平面视图、三维视图、剖面图及其像元统计量进行比较和分析；同时对反距离加权插值法的插值参数搜索半径进行讨论、比较和分析。[结果] 对于森林区域空间分布均匀且存在高度突变的点云数据，B-Spline插值对空值区域都进行了填充，林冠空隙也被过分填充，且CHM像元最大值明显偏离原始插值数据；TLI插值的CHM显得比较破碎；OK插值法对影像过度平滑，生成的CHM影像模糊；而IDW插值法对冠层顶部进行了适当填充和平滑，但冠层边缘不被过度平滑，保留高度突变，同时林冠空隙仍然保留也不被过分填充。IDW插值应选择合适的搜索半径，搜索半径为原始点云间隔的1.5~2.5倍较为合适。[结论] IDW插值法优于B-Spline，OK，TLI插值法，生成的CHM能较准确反映森林冠层的真实自然形态，有利于森林参数的提取。

关键词: 机载激光雷达, 冠层高度模型, 反距离加权插值法, B样条曲线插值法, 普通克里金插值法, 线性插值三角网法, 离散点云

Abstract: [Objective] According to the characteristics of the discrete point cloud in forest area, canopy height model(CHM) was built through different interpolation methods. The results of the different interpolation methods were compared, analyzed and evaluated in order to provide the reference for choice of interpolation methods. [Method] In this study, the discrete point cloud data in plots(30 m×30 m) were used as the experimental data. CHMs were generated by B-Spline, triangulation with linear interpolation(TLI), ordinary Kriging(OK) and inverse distance weighted(IDW) interpolation methods, respectively, through the open source software SAGS-GIS. 2D views, 3D views, profiles and pixel statistics of CHMs with different interpolation methods in plots were compared and analyzed. At the same time, the search radius parameters of IDW interpolation were discussed, compared and analyzed.[Result] The spatial distribution was uniform and there was height mutation for the discrete point cloud in forest area. For B-Spline interpolation, zero value(no data) region was filled, canopy gap was grossly filled and pixel maximum of the CHM deviated significantly from the height value of the original data. For TLI interpolation, the CHM appeared to be more fragmentation. For OK interpolation, the image of CHM was not clear duo to excessive smoothing applied. And for the IDW interpolation, the CHM on the top of canopy was properly filled and smoothed, but canopy edge was not excessive smoothing and retained elevation mutation, meanwhile, canopy gap still retained not be over filled. The results showed that the most suitable search radius of IDW interpolation method was about 1.5±2.5 times of the mean interval of original point cloud in forest canopy. [Conclusion] The IDW interpolation was better than B-spline, TLI, OK interpolation for generating CHM from discrete point cloud data. The formation of CHM with IDW interpolation could accurately reflect the truly natural form of forest canopy. So it was good for the extraction of forest parameters.

Key words: light detection and ranging(LiDAR), canopy height model(CHM), inverse distance weighted(IDW), B-spline, triangulation with linear interpolation(TLI), ordinary Kriging(OK), discrete point cloud

中图分类号:

S762.3

段祝庚, 肖化顺, 袁伟湘. 基于离散点云数据的森林冠层高度模型插值方法[J]. 林业科学, 2016, 52(9): 86-94.

Duan Zhugeng, Xiao Huashun, Yuan Weixiang. Comparison of Interpolation Methods of Forest Canopy Height Model Using Discrete Point Cloud Data[J]. Scientia Silvae Sinicae, 2016, 52(9): 86-94.

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基于离散点云数据的森林冠层高度模型插值方法

Comparison of Interpolation Methods of Forest Canopy Height Model Using Discrete Point Cloud Data

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