干旱区生态环境知识资源中心(Arid): Accuracy of Vegetation Indices in Assessing Different Grades of Grassland Desertification from UAV

Arid

DOI	10.3390/ijerph192416793
	Accuracy of Vegetation Indices in Assessing Different Grades of Grassland Desertification from UAV
	Xu, Xue; Liu, Luyao; Han, Peng; Gong, Xiaoqian; Zhang, Qing
通讯作者	Zhang, Q
来源期刊	INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
EISSN	1660-4601
出版年	2022
卷号	19 期号:24
英文摘要	Grassland desertification has become one of the most serious environmental problems in the world. Grasslands are the focus of desertification research because of their ecological vulnerability. Their application on different grassland desertification grades remains limited. Therefore, in this study, 19 vegetation indices were calculated for 30 unmanned aerial vehicle (UAV) visible light images at five grades of grassland desertification in the Mu Us Sandy. Fractional Vegetation Coverage (FVC) with high accuracy was obtained through Support Vector Machine (SVM) classification, and the results were used as the reference values. Based on the FVC, the grassland desertification grades were divided into five grades: severe (FVC < 5%), high (FVC: 5-20%), moderate (FVC: 21-50%), slight (FVC: 51-70%), and non-desertification (FVC: 71-100%). The accuracy of the vegetation indices was assessed by the overall accuracy (OA), the kappa coefficient (k), and the relative error (RE). Our result showed that the accuracy of SVM-supervised classification was high in assessing each grassland desertification grade. Excess Green Red Blue Difference Index (EGRBDI), Visible Band Modified Soil Adjusted Vegetation Index (V-MSAVI), Green Leaf Index (GLI), Color Index of Vegetation Vegetative (CIVE), Red Green Blue Vegetation Index (RGBVI), and Excess Green (EXG) accurately assessed grassland desertification at severe, high, moderate, and slight grades. In addition, the Red Green Ratio Index (RGRI) and Combined 2 (COM2) were accurate in assessing severe desertification. The assessment of the 19 indices of the non-desertification grade had low accuracy. Moreover, our result showed that the accuracy of SVM-supervised classification was high in assessing each grassland desertification grade. This study emphasizes that the applicability of the vegetation indices varies with the degree of grassland desertification and hopes to provide scientific guidance for a more accurate grassland desertification assessment.
英文关键词	grassland desertification vegetation index fractional vegetation coverage UAV visible light images the Mu Us Sandy
类型	Article
语种	英语
开放获取类型	Green Published, gold
收录类别	SCI-E ; SSCI
WOS记录号	WOS:000902474600001
WOS关键词	AUTOMATED CROP ; RIVER-BASIN ; REMOTE ; IMAGES ; COVER ; CLASSIFICATION ; IDENTIFICATION ; ENVIRONMENTS ; DEGRADATION ; EXTRACTION
WOS类目	Environmental Sciences ; Public, Environmental & Occupational Health
WOS研究方向	Environmental Sciences & Ecology ; Public, Environmental & Occupational Health
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/393179
推荐引用方式 GB/T 7714	Xu, Xue,Liu, Luyao,Han, Peng,et al. Accuracy of Vegetation Indices in Assessing Different Grades of Grassland Desertification from UAV[J],2022,19(24).
APA	Xu, Xue,Liu, Luyao,Han, Peng,Gong, Xiaoqian,&Zhang, Qing.(2022).Accuracy of Vegetation Indices in Assessing Different Grades of Grassland Desertification from UAV.INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH,19(24).
MLA	Xu, Xue,et al."Accuracy of Vegetation Indices in Assessing Different Grades of Grassland Desertification from UAV".INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 19.24(2022).