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

Remote Sensing

Fangfang Yao¹  Chao Wang³  Di Dong¹  Jiancheng Luo¹  Zhanfeng Shen⁴  Kehan Yang¹  Deepak R. Mishra²  Eurico J. D’Sa²  Sachidananda Mishra² 

[1] State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China; E-Mails:State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China;;Department of Environmental Sciences, University of Puerto Rico, San Juan 00931, PR, USA; E-Mail:;National Engineering Research Center for Geoinformatics, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China; E-Mail:

关键词: ZY-3;    Urban water bodies;    Water index;    Threshold stability;    Shadow detection;    Urban remote sensing;    Support Vector Machine;   

DOI  :  10.3390/rs70912336

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.