王树东等:A Simple Enhanced Water Index (EWI) for Percent Surface Water Estimation Using Landsat Data
被阅读 2185 次
2015-04-03
A Simple Enhanced Water Index (EWI) for Percent Surface Water Estimation Using Landsat Data
作者:Wang, SD (Wang, Shudong)[ 1 ] ; Baig, MHA (Baig, Muhammad Hasan Ali)[ 1 ] ; Zhang, LF (Zhang, Lifu)[ 1 ] ; Jiang, HL (Jiang, Hailiang)[ 2 ] ; Ji, YH (Ji, Yuhe)[ 3 ] ; Zhao, HQ (Zhao, Hengqian)[ 1 ] ; Tian, JG (Tian, Jingguo)
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
卷: 8  期: 1  页: 90-97
DOI: 10.1109/JSTARS.2014.2387196
出版年: JAN 2015
 
摘要
To timely obtain accurate pixel water surface proportion information through remote sensing is extremely significant to the ecological restoration in inland river basins and for the precise management of water resources. In respect to the insufficient extraction of water surface proportion information present in pixels in most of the current water information models, a simple model Enhanced Water Index (EWI) based on Modified Normalized Difference Water Index (MNDWI) has been introduced. EWI, which is oriented toward the sub-pixel level analysis of water surface proportion mapping of inland river basin, has been put forward based on the analysis of typical spectral signatures such as desert, soil, and vegetation along with MNDWI in accordance with the Landsat TM band features. The analysis is done by using methods of pixel-based EWI value with different water proportions which are analyzed through the introduction of the linear hybrid simulation between the water body and the corresponding background. Lastly, the effect of EWI model has been tested in the medium and lower reaches of Tarim. The correction coefficient for sub-pixel level water surface proportion predicted by the EWI model and the experimental data is R-2 = 0.72. Results showed that the model was able to effectively extract the information about pixel water surface proportion in inland river basins. This study proves that EWI model has great potential in its application for water proportion mapping applications.
 
通讯作者地址: Zhang, LF (通讯作者)
Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.
地址:
[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
[ 2 ] Peking Univ, Inst Remote Sensing & GIS, Beijing 100871, Peoples R China
[ 3 ] Chinese Acad Meteorol Sci, Beijing 100081, Peoples R China