Water extraction of hyperspectral imagery based on a fast and effective decision tree water index

doi:10.1117/1.JRS.15.042605

	Water extraction of hyperspectral imagery based on a fast and effective decision tree water index
	Yang, Jiawei 1; Wang, Xin 1; Wang, Jiyan 1; Ye, Chongchong 1; Xiong, Junnan 1,2
刊名	JOURNAL OF APPLIED REMOTE SENSING
	2021-08-27
卷号	15 期号:4 页码:19
关键词	hyperspectral remote sensing water extraction spectral analysis
ISSN号	1931-3195
DOI	10.1117/1.JRS.15.042605
通讯作者	Xiong, Junnan(neu_xjn@163.com)
英文摘要	Surface water is an essential carrier for the balance of ecosystems and human existence. As applied hyperspectral remote sensing has improved, the research into water extraction from the hyperspectral image gradually attracted more attention. However, delineating water from the hyperspectral image is challenging due to shadows of buildings and trees, and other dark pixels. Furthermore, water indexes that come from multispectral imagery are directly applied to hyperspectral imagery leads to some defects, such as underutilized abundant information and higher misclassifications. Here, we proposed a decision tree water index (DTWI) method to extract water bodies from hyperspectral imagery. Combining the threshold of the nearinfrared reflectance and the magnitude of the difference between reflectance of 700 and 730 nm, the DTWI method could effectively extract water from hyperspectral imagery. Three hyperspectral images derived from the study areas within the city, a mixture of city and suburban zone, and suburban zone only, were applied to test the feasibility and flexibility of this method in various sensors and environments. Four alternative methods were used to verify the robustness of the proposed method, including hyperspectral difference water index, normalized difference water index, shaded building index, and support vector machine (SVM). Our results indicated that the proposed method was better suited to extracting water bodies from hyperspectral imagery when compared with other methods and could effectively capture water on different hyperspectral sensors, various heterogeneous surroundings, and multi-spatial scales. The proposed DTWI method has high stability in threshold and band selection, which is comparable to the SVM method in the mean overall accuracy and kappa coefficient (DTWI: 0.98 and 0.81; SVM: 0.98 and 0.82). For the view of elapsed time, calculation, and applicability, the proposed method has the potential of better utilization and rapid response for water extraction in hyperspectral imagery. (C) 2021 Society of Photo-Optical Instrumentation Engineers (SPIE)
资助项目	Key R&D project of Sichuan Science and Technology Department[2021YFQ0042] ; Science and Technology Project of Xizang Autonomous Region[XZ201901-GA-07] ; scientific research starting project of Southwest Petroleum University[2019QHZ020]
WOS关键词	SUPPORT VECTOR MACHINES ; SURFACE-WATER ; BODY EXTRACTION ; LONG-TERM ; CLASSIFICATION ; LAKE ; INFORMATION ; FEATURES ; CLIMATE ; REGION
WOS研究方向	Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
语种	英语
出版者	SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
WOS记录号	WOS:000693617700001
资助机构	Key R&D project of Sichuan Science and Technology Department ; Science and Technology Project of Xizang Autonomous Region ; scientific research starting project of Southwest Petroleum University
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/165497]
专题	中国科学院地理科学与资源研究所
通讯作者	Xiong, Junnan
作者单位	1.Southwest Petr Univ, Sch Civil Engn & Geomat, Chengdu, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Yang, Jiawei,Wang, Xin,Wang, Jiyan,et al. Water extraction of hyperspectral imagery based on a fast and effective decision tree water index[J]. JOURNAL OF APPLIED REMOTE SENSING,2021,15(4):19.
APA	Yang, Jiawei,Wang, Xin,Wang, Jiyan,Ye, Chongchong,&Xiong, Junnan.(2021).Water extraction of hyperspectral imagery based on a fast and effective decision tree water index.JOURNAL OF APPLIED REMOTE SENSING,15(4),19.
MLA	Yang, Jiawei,et al."Water extraction of hyperspectral imagery based on a fast and effective decision tree water index".JOURNAL OF APPLIED REMOTE SENSING 15.4(2021):19.