Analysis of UAV lidar information loss and its influence on the estimation accuracy of structural and functional traits in a meadow steppe

doi:10.1016/j.ecolind.2021.108515

	Analysis of UAV lidar information loss and its influence on the estimation accuracy of structural and functional traits in a meadow steppe
	Zhao, Xiaoxia 1; Su, Yanjun 1; Hu, Tianyu 1; Cao, Mengqi 1; Liu, Xiaoqiang 1; Yang, Qiuli 1; Guan, Hongcan 2; Liu, Lingli1 ; Guo, Qinghua2
	2022
发表期刊	ECOLOGICAL INDICATORS
ISSN	1470-160X
卷号	135
摘要	Accurate quantification of grassland structural and functional traits is the foundation for grassland management and restoration. Light detection and ranging (lidar), especially the unmanned aerial vehicle (UAV) lidar, has been recognized as an accurate and effective technique for local to regional-scale vegetation structural and functional traits estimation. However, in grassland ecosystems, it is more likely to be influenced by UAV lidar information loss caused by dense vegetation canopies. In this study, we investigated how UAV lidar information loss may occur and how it may influence the estimation accuracy of grassland structural and functional traits by comparing it with terrestrial laser scanning (TLS) and field measurements in a meadow steppe of northern China. Five structural traits (i.e., mean vegetation height, maximum vegetation height, standard deviation of vegetation height, canopy cover, and canopy volume) and one functional trait (i.e., aboveground biomass) were estimated from the UAV lidar data and TLS data for evaluation. The results showed that TLS-derived structural and functional traits had a much higher accuracy than UAV lidar-derived traits. By comparing with TLS data, we found that UAV lidar data had a much more prevailing information loss at canopy tops than at canopy bottoms. The average height loss of UAV lidar at canopy tops reached over 0.30 m, and the average relative height loss reached over 49%, comparing to a value of 0.03 m and 6% at canopy bottoms. Maximum vegetation height, standard deviation, and the distance from the UAV lidar system to the ground were the three most influential factors on UAV lidar information loss at canopy tops, indicating the commonly seen sharp canopy tops of grasslands were prone to be missed by the UAV lidar system. UAV lidar information loss at canopy tops had a much stronger influence on the estimation accuracy of grassland structural and functional traits than that at canopy bottoms. With the decrease of information loss at canopy tops, UAV lidar can be used to extract grassland structural and functional traits with a comparable accuracy to TLS. Among the five grassland traits, aboveground biomass was the least influenced by UAV lidar information loss. This study is a very first evaluation on the UAV lidar information loss in grassland ecosystems and its influence on grassland structural and functional trait estimation, which can provide guidance for UAV lidar data collection and processing in future grassland applications.
关键词	UAV lidar Information loss TLS Structural trait Functional trait
学科领域	Biodiversity Conservation ; Environmental Sciences
DOI	10.1016/j.ecolind.2021.108515
收录类别	SCI
语种	英语
WOS关键词	AIRBORNE LIDAR ; TERRESTRIAL LIDAR ; VEGETATION ; BIOMASS ; COVER ; SHRUB ; GRASSLAND ; IMAGERY ; HEIGHT
WOS研究方向	Science Citation Index Expanded (SCI-EXPANDED)
WOS记录号	WOS:000761393800003
出版者	ELSEVIER
文献子类	Article
出版地	AMSTERDAM
EISSN	1872-7034
资助机构	Strategic Priority Research Program of Chinese Academy of Sciences [XDA26010101, XDA23080301]
作者邮箱	ysu@ibcas.ac.cn
作品OA属性	gold
引用统计	被引频次：19[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/2S10CLM1/28979
专题	植被与环境变化国家重点实验室
作者单位	1.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Peking Univ, Coll Urban & Environm Sci, Inst Ecol, Beijing 100871, Peoples R China
推荐引用方式 GB/T 7714	Zhao, Xiaoxia,Su, Yanjun,Hu, Tianyu,et al. Analysis of UAV lidar information loss and its influence on the estimation accuracy of structural and functional traits in a meadow steppe[J]. ECOLOGICAL INDICATORS,2022,135.
APA	Zhao, Xiaoxia.,Su, Yanjun.,Hu, Tianyu.,Cao, Mengqi.,Liu, Xiaoqiang.,...&Guo, Qinghua.(2022).Analysis of UAV lidar information loss and its influence on the estimation accuracy of structural and functional traits in a meadow steppe.ECOLOGICAL INDICATORS,135.
MLA	Zhao, Xiaoxia,et al."Analysis of UAV lidar information loss and its influence on the estimation accuracy of structural and functional traits in a meadow steppe".ECOLOGICAL INDICATORS 135(2022).

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