Using UAV LiDAR to Extract Vegetation Parameters of Inner Mongolian Grassland
文献类型: 外文期刊
第一作者: Zhang, Xiang
作者: Zhang, Xiang;Bao, Yuhai;Wang, Dongliang;Wang, Dongliang;Xin, Xiaoping;Ding, Lei;Xu, Dawei;Hou, Lulu;Shen, Jie;Wang, Dongliang;Wang, Dongliang;Wang, Dongliang
作者机构:
关键词: UAV LiDAR; AGB; Hulun Buir grassland; canopy height; fractional vegetation cover
期刊名称:REMOTE SENSING ( 影响因子:4.848; 五年影响因子:5.353 )
ISSN:
年卷期: 2021 年 13 卷 4 期
页码:
收录情况: SCI
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.
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