气候变化领域集成服务门户(CCPortal): A non-destructive method for rapid acquisition of grassland aboveground biomass for satellite ground verification using UAV RGB images

CCPortal

DOI	10.1016/j.gecco.2022.e01999
	A non-destructive method for rapid acquisition of grassland aboveground biomass for satellite ground verification using UAV RGB images
	Zhang, Huifang; Tang, Zhonggang; Wang, Binyao; Meng, Baoping; Qin, Yu; Sun, Yi; Lv, Yanyan; Zhang, Jianguo; Yi, Shuhua
通讯作者	Yi, SH (通讯作者)，Nantong Univ, Inst Fragile Ecoenvironm, 999 Tongjing Rd, Nantong 226007, Jiangsu, Peoples R China.
发表日期	2022
EISSN	2351-9894
卷号	33
英文摘要	Remote sensing has become an indispensable method for estimating the regional-scale collection of grassland aboveground biomass (AGB). However, the lack of ground verification samples often reduces the inversion accuracy. This paper aimed to find a non-destructive method to quickly obtain grassland AGB at quadrat-scale through unmanned aerial vehicles (UAVs) in a large area. Thus, we proposed and assessed the vertical and horizontal indices from UAV RGB images as predictors of grassland AGB using the random forest (RF) machine learning technique. By comparing the performance of different indices combinations, we found that the model combing the horizontal and vertical indices (RFVH) performed best (R-2 = 0.78; RMSE = 24.80 g/m(2)), followed by the model using only horizontal indices (the RFH model; R-2=0.73; RMSE =26.54 g/ m(2)), and the last was the model using only the vertical index. However, the REVH model was unsuitable for collecting AGB samples in a large area because the UAVs with RGB cameras failed to obtain vegetation height information in areas with high vegetation coverage. In conclusion, the RFH model can be used to replace the traditional destructive method for collecting ground data over large regions for AGB satellite inversion.
关键词	CROP SURFACE MODELS CLIMATE-CHANGE VEGETATION CARBON COVER AREA PRODUCTIVITY INDEXES WETLAND HEIGHT
英文关键词	Grassland; Unmanned aerial vehicle; Aboveground biomass; Random forest; Vegetation; RGB image
语种	英语
WOS研究方向	Biodiversity & Conservation ; Environmental Sciences & Ecology
WOS类目	Biodiversity Conservation ; Ecology
WOS记录号	WOS:000742854600003
来源期刊	GLOBAL ECOLOGY AND CONSERVATION
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/254352
作者单位	[Zhang, Huifang; Meng, Baoping; Sun, Yi; Lv, Yanyan; Zhang, Jianguo; Yi, Shuhua] Nantong Univ, Inst Fragile Ecoenvironm, 999 Tongjing Rd, Nantong 226007, Jiangsu, Peoples R China; [Zhang, Huifang; Tang, Zhonggang; Wang, Binyao; Meng, Baoping; Sun, Yi; Lv, Yanyan; Zhang, Jianguo; Yi, Shuhua] Nantong Univ, Sch Geog Sci, 999 Tongjing Rd, Nantong 226007, Jiangsu, Peoples R China; [Qin, Yu] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, State Key Lab Cryospher Sci, 320 Donggang West Rd, Lanzhou 730000, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Huifang,Tang, Zhonggang,Wang, Binyao,et al. A non-destructive method for rapid acquisition of grassland aboveground biomass for satellite ground verification using UAV RGB images[J]. 中国科学院西北生态环境资源研究院,2022,33.
APA	Zhang, Huifang.,Tang, Zhonggang.,Wang, Binyao.,Meng, Baoping.,Qin, Yu.,...&Yi, Shuhua.(2022).A non-destructive method for rapid acquisition of grassland aboveground biomass for satellite ground verification using UAV RGB images.GLOBAL ECOLOGY AND CONSERVATION,33.
MLA	Zhang, Huifang,et al."A non-destructive method for rapid acquisition of grassland aboveground biomass for satellite ground verification using UAV RGB images".GLOBAL ECOLOGY AND CONSERVATION 33(2022).