Using UAV LiDAR to Extract Vegetation Parameters of Inner Mongolian Grassland

doi:10.3390/rs13040656

	Using UAV LiDAR to Extract Vegetation Parameters of Inner Mongolian Grassland
	Zhang, Xiang 1; Bao, Yuhai 1; Wang, Dongliang 2,3,4,5,6; Xin, Xiaoping 3; Ding, Lei 3; Xu, Dawei 3; Hou, Lulu 3; Shen, Jie 3
刊名	REMOTE SENSING
	2021-02-01
卷号	13 期号:4 页码:18
关键词	UAV LiDAR AGB Hulun Buir grassland canopy height fractional vegetation cover
DOI	10.3390/rs13040656
通讯作者	Wang, Dongliang(wangdongliang@igsnrr.ac.cn)
英文摘要	The accurate estimation of grassland vegetation parameters at a high spatial resolution is important for the sustainable management of grassland areas. Unmanned aerial vehicle (UAV) light detection and ranging (LiDAR) sensors with a single laser beam emission capability can rapidly detect grassland vegetation parameters, such as canopy height, fractional vegetation coverage (FVC) and aboveground biomass (AGB). However, there have been few reports on the ability to detect grassland vegetation parameters based on RIEGL VUX-1 UAV LiDAR (Riegl VUX-1) systems. In this paper, we investigated the ability of Riegl VUX-1 to model the AGB at a 0.1 m pixel resolution in the Hulun Buir grazing platform under different grazing intensities. The LiDAR-derived minimum, mean, and maximum canopy heights and FVC were used to estimate the AGB across the entire grazing platform. The flight height of the LiDAR-derived vegetation parameters was also analyzed. The following results were determined: (1) The Riegl VUX-1-derived AGB was predicted to range from 29 g/m(2) to 563 g/m(2) under different grazing conditions. (2) The LiDAR-derived maximum canopy height and FVC were the best predictors of grassland AGB (R-2 = 0.54, root-mean-square error (RMSE) = 64.76 g/m(2)). (3) For different UAV flight altitudes from 40 m to 110 m, different flight heights showed no major effect on the derived canopy height. The LiDAR-derived canopy height decreased from 9.19 cm to 8.17 cm, and the standard deviation of the LiDAR-derived canopy height decreased from 3.31 cm to 2.35 cm with increasing UAV flight altitudes. These conclusions could be useful for estimating grasslands in smaller areas and serving as references for other remote sensing datasets for estimating grasslands in larger areas.
资助项目	National Key Research and Development Project[2016YFC0500608] ; National Key Research and Development Project[2017YFC0506505] ; National Key Research and Development Project[2019YFE0126500] ; National Key Research and Development Project[2017YFB0503005] ; National Natural Science Foundation of China[41501416] ; Special Fund for the Construction of Modern Agricultural Industrial Technology System[CARS34] ; State Key Laboratory of Resources and Environmental Information System ; Tianjin Intelligent Manufacturing Project: Technology of Intelligent Net-working by Autonomous Control UAVs for Observation and Application[Tianjin-IMP-2] ; Natural Science Foundation of Tianjin[18JCYBJC42300]
WOS研究方向	Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	MDPI
WOS记录号	WOS:000624427900001
资助机构	National Key Research and Development Project ; National Natural Science Foundation of China ; Special Fund for the Construction of Modern Agricultural Industrial Technology System ; State Key Laboratory of Resources and Environmental Information System ; Tianjin Intelligent Manufacturing Project: Technology of Intelligent Net-working by Autonomous Control UAVs for Observation and Application ; Natural Science Foundation of Tianjin
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/160407]
专题	中国科学院地理科学与资源研究所
通讯作者	Wang, Dongliang
作者单位	1.Inner Mongolia Normal Univ, Coll Geog Sci, Hohhot 010022, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China 3.Chinese Acad Agr Sci, Inst Agr Resources & Reg Planning, Beijing 100081, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China 5.Inst UAV Applicat Res, Tianjin, Peoples R China 6.Chinese Acad Sci, Tianjin 301800, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Xiang,Bao, Yuhai,Wang, Dongliang,et al. Using UAV LiDAR to Extract Vegetation Parameters of Inner Mongolian Grassland[J]. REMOTE SENSING,2021,13(4):18.
APA	Zhang, Xiang.,Bao, Yuhai.,Wang, Dongliang.,Xin, Xiaoping.,Ding, Lei.,...&Shen, Jie.(2021).Using UAV LiDAR to Extract Vegetation Parameters of Inner Mongolian Grassland.REMOTE SENSING,13(4),18.
MLA	Zhang, Xiang,et al."Using UAV LiDAR to Extract Vegetation Parameters of Inner Mongolian Grassland".REMOTE SENSING 13.4(2021):18.