Simple method for direct crown base height estimation of individual conifer trees using airborne LiDAR data

doi:10.1364/OE.26.00A562

	Simple method for direct crown base height estimation of individual conifer trees using airborne LiDAR data
	Luo, Laiping 1; Zhai, Qiuping 2,3; Su, Yanjun 1,2; Ma, Qin 1; Kelly, Maggi 4; Guo, Qinghua1,2,3
	2018
发表期刊	OPTICS EXPRESS
ISSN	1094-4087
卷号	26 期号:10 页码:A562-A578
摘要	Crown base height (CBH) is an essential tree biophysical parameter for many applications in forest management, forest fuel treatment, wildfire modeling, ecosystem modeling and global climate change studies. Accurate and automatic estimation of CBH for individual trees is still a challenging task. Airborne light detection and ranging (LiDAR) provides reliable and promising data for estimating CBH. Various methods have been developed to calculate CBH indirectly using regression-based means from airborne LiDAR data and field measurements. However, little attention has been paid to directly calculate CBH at the individual tree scale in mixed-species forests without field measurements. In this study, we propose a new method for directly estimating individual-tree CBH from airborne LiDAR data. Our method involves two main strategies: 1) removing noise and understory vegetation for each tree; and 2) estimating CBH by generating percentile ranking profile for each tree and using a spline curve to identify its inflection points. These two strategies lend our method the advantages of no requirement of field measurements and being efficient and effective in mixed-species forests. The proposed method was applied to a mixed conifer forest in the Sierra Nevada, California and was validated by field measurements. The results showed that our method can directly estimate CBH at individual tree level with a root-mean-squared error of 1.62 m a coefficient of determination of 0.88 and a relative bias of 3.36%. Furthermore, we systematically analyzed the accuracies among different height groups and tree species by comparing with field measurements. Our results implied that taller trees had relatively higher uncertainties than shorter trees. Our findings also show that the accuracy for CBH estimation was the highest for black oak trees, with an RMSE of 0.52 m. The conifer species results were also good with uniformly high R-2 ranging from 0.82 to 0.93. In general, our method has demonstrated high accuracy for individual tree CBH estimation and strong potential for applications in mixed species over large areas. (C) 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
学科领域	Optics
DOI	10.1364/OE.26.00A562
收录类别	SCI
语种	英语
WOS关键词	AERIAL IMAGERY ; FOREST BIOMASS ; CANOPY COVER ; LEAF-AREA ; LASER ; GROWTH ; PINE ; MODELS ; VEGETATION ; INDICATORS
WOS记录号	WOS:000432457600015
出版者	OPTICAL SOC AMER
文献子类	Article
出版地	WASHINGTON
资助机构	National Key R&D Program of China [2017YFC0503905, 2016YFC0500202] ; Frontier Science Key Programs of the Chinese Academy of Sciences [QYZDY-SSW-SMC011] ; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [41471363, 31270563, 31741016] ; Beijing Natural Science FoundationBeijing Natural Science Foundation [4164085] ; Beijing Postdoctoral Research FoundationChina Postdoctoral Science Foundation ; Beijing Municipal Education Commission Research Program [KM201511418002] ; open funding project of State Key Laboratory of Virtual Reality Technology and Systems [011177220010020]
作者邮箱	suyanjun1987@gmail.com ; guo.qinghua@gmail.com
作品OA属性	Green Published, gold
引用统计	被引频次：48[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ibcas.ac.cn/handle/2S10CLM1/20401
专题	植被与环境变化国家重点实验室
作者单位	1.Capital Normal Univ, Coll Resource Environm & Tourism, State Key Lab Urban Environm Proc & Digital Simul, Beijing 100048, Peoples R China 2.Univ Calif Merced, Sierra Nevada Res Inst, Sch Engn, Sierra Nevada Res Inst, Merced, CA 95343 USA 3.Chinese Acad Sci, State Key Lab Vegetat & Environm Change, Inst Bot, Beijing 100093, Peoples R China 4.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 5.Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 USA
推荐引用方式 GB/T 7714	Luo, Laiping,Zhai, Qiuping,Su, Yanjun,et al. Simple method for direct crown base height estimation of individual conifer trees using airborne LiDAR data[J]. OPTICS EXPRESS,2018,26(10):A562-A578.
APA	Luo, Laiping,Zhai, Qiuping,Su, Yanjun,Ma, Qin,Kelly, Maggi,&Guo, Qinghua.(2018).Simple method for direct crown base height estimation of individual conifer trees using airborne LiDAR data.OPTICS EXPRESS,26(10),A562-A578.
MLA	Luo, Laiping,et al."Simple method for direct crown base height estimation of individual conifer trees using airborne LiDAR data".OPTICS EXPRESS 26.10(2018):A562-A578.

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