干旱区生态环境知识资源中心(Arid): Effects of RapidEye Imagery's Red-edge Band and Vegetation Indices on Land Cover Classification in an Arid Region

Arid

	Effects of RapidEye Imagery's Red-edge Band and Vegetation Indices on Land Cover Classification in an Arid Region
	Li Xianju; Chen Gang; Liu Jingyi; Chen Weitao; Cheng Xinwen; Liao Yiwei
来源期刊	Chinese Geographical Science
ISSN	1002-0063
出版年	2017
卷号	27 期号:5 页码:827-835
英文摘要	Land cover classification (LCC) in arid regions is of great significance to the assessment, prediction, and management of land desertification. Some studies have shown that the red-edge band of RapidEye images was effective for vegetation identification and could improve LCC accuracy. However, there has been no investigation of the effects of RapidEye images' red-edge band and vegetation indices on LCC in arid regions where there are spectrally similar land covers mixed with very high or low vegetation coverage information and bare land. This study focused on a typical inland arid desert region located in Dunhuang Basin of northwestern China. First, five feature sets including or excluding the red-edge band and vegetation indices were constructed. Then, a land cover classification system involving plant communities was developed. Finally, random forest algorithm-based models with different feature sets were utilized for LCC. The conclusions drawn were as follows: 1) the red-edge band showed slight contribution to LCC accuracy; 2) vegetation indices had a significant positive effect on LCC; 3) simultaneous addition of the red-edge band and vegetation indices achieved a significant overall accuracy improvement (3.46% from 86.67%). In general, vegetation indices had larger effect than the red-edge band, and simultaneous addition of them significantly increased the accuracy of LCC in arid regions.
英文关键词	arid region land cover classification RapidEye red-edge band vegetation indices random forest Dunhuang Basin
类型	Article
语种	英语
开放获取类型	Bronze
收录类别	CSCD
WOS研究方向	Plant Sciences
CSCD记录号	CSCD:6065002
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/335858
作者单位	Li Xianju, College of Computer Science,China University of Geosciences(Wuhan), Hubei Key Laboratory of Intelligent Geo-Information Processing, Wuhan, Hubei 430074, China.; Chen Weitao, College of Computer Science,China University of Geosciences(Wuhan), Hubei Key Laboratory of Intelligent Geo-Information Processing, Wuhan, Hubei 430074, China.; Chen Gang, College of Marine Science and Technology, China University of Geosciences(Wuhan), Wuhan, Hubei 430074, China.; Liu Jingyi, Laboratory of Geographic Information and Spatial Analysis, Department of Geography and Planning, Queen's University, Kingston, K7L3N6, Canada.; Cheng Xinwen, Faculty of Information Engineering, China University of Geosciences(Wuhan), Wuhan, Hubei 430074, China.; Liao Yiwei, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.; 430074.; 430074.; 430074.; 430074.; 430074.; K7L3N6.
推荐引用方式 GB/T 7714	Li Xianju,Chen Gang,Liu Jingyi,et al. Effects of RapidEye Imagery's Red-edge Band and Vegetation Indices on Land Cover Classification in an Arid Region[J],2017,27(5):827-835.
APA	Li Xianju,Chen Gang,Liu Jingyi,Chen Weitao,Cheng Xinwen,&Liao Yiwei.(2017).Effects of RapidEye Imagery's Red-edge Band and Vegetation Indices on Land Cover Classification in an Arid Region.Chinese Geographical Science,27(5),827-835.
MLA	Li Xianju,et al."Effects of RapidEye Imagery's Red-edge Band and Vegetation Indices on Land Cover Classification in an Arid Region".Chinese Geographical Science 27.5(2017):827-835.