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Remote Sens. 2015, 7(9), 12336-12355; doi:10.3390/rs70912336

High-Resolution Mapping of Urban Surface Water Using ZY-3 Multi-Spectral Imagery

1
State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
Department of Environmental Sciences, University of Puerto Rico, San Juan 00931, PR, USA
4
National Engineering Research Center for Geoinformatics, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
*
Author to whom correspondence should be addressed.
Academic Editors: Deepak R. Mishra, Eurico J. D’Sa, Sachidananda Mishra and Prasad S. Thenkabail
Received: 4 July 2015 / Revised: 8 September 2015 / Accepted: 14 September 2015 / Published: 22 September 2015
(This article belongs to the Special Issue Remote Sensing of Water Resources)
View Full-Text   |   Download PDF [2058 KB, uploaded 22 September 2015]   |  

Abstract

Accurate information of urban surface water is important for assessing the role it plays in urban ecosystem services under the content of urbanization and climate change. However, high-resolution monitoring of urban water bodies using remote sensing remains a challenge because of the limitation of previous water indices and the dark building shadow effect. To address this problem, we proposed an automated urban water extraction method (UWEM) which combines a new water index, together with a building shadow detection method. Firstly, we trained the parameters of UWEM using ZY-3 imagery of Qingdao, China. Then we verified the algorithm using five other sub-scenes (Aksu, Fuzhou, Hanyang, Huangpo and Huainan) ZY-3 imagery. The performance was compared with that of the Normalized Difference Water Index (NDWI). Results indicated that UWEM performed significantly better at the sub-scenes with kappa coefficients improved by 7.87%, 32.35%, 12.64%, 29.72%, 14.29%, respectively, and total omission and commission error reduced by 61.53%, 65.74%, 83.51%, 82.44%, and 74.40%, respectively. Furthermore, UWEM has more stable performances than NDWI’s in a range of thresholds near zero. It reduces the over- and under-estimation issues which often accompany previous water indices when mapping urban surface water under complex environmental conditions. View Full-Text
Keywords: ZY-3; Urban water bodies; Water index; Threshold stability; Shadow detection; Urban remote sensing; Support Vector Machine ZY-3; Urban water bodies; Water index; Threshold stability; Shadow detection; Urban remote sensing; Support Vector Machine
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Yao, F.; Wang, C.; Dong, D.; Luo, J.; Shen, Z.; Yang, K. High-Resolution Mapping of Urban Surface Water Using ZY-3 Multi-Spectral Imagery. Remote Sens. 2015, 7, 12336-12355.

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