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High-Resolution Mapping of Urban Surface Water Using ZY-3 Multi-Spectral Imagery
by
Yao, Fangfang
, Yang, Kehan
, Wang, Chao
, Shen, Zhanfeng
, Dong, Di
, Luo, Jiancheng
in
Buildings
/ Climate change
/ Construction
/ Ecosystem services
/ Environmental conditions
/ Imagery
/ Mapping
/ Performance indices
/ Remote sensing
/ Shadow detection
/ Shadows
/ Support Vector Machine
/ Surface water
/ Threshold stability
/ Urban areas
/ Urban remote sensing
/ Urban water bodies
/ Urbanization
/ Water index
/ ZY-3
2015
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High-Resolution Mapping of Urban Surface Water Using ZY-3 Multi-Spectral Imagery
by
Yao, Fangfang
, Yang, Kehan
, Wang, Chao
, Shen, Zhanfeng
, Dong, Di
, Luo, Jiancheng
in
Buildings
/ Climate change
/ Construction
/ Ecosystem services
/ Environmental conditions
/ Imagery
/ Mapping
/ Performance indices
/ Remote sensing
/ Shadow detection
/ Shadows
/ Support Vector Machine
/ Surface water
/ Threshold stability
/ Urban areas
/ Urban remote sensing
/ Urban water bodies
/ Urbanization
/ Water index
/ ZY-3
2015
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Do you wish to request the book?
High-Resolution Mapping of Urban Surface Water Using ZY-3 Multi-Spectral Imagery
by
Yao, Fangfang
, Yang, Kehan
, Wang, Chao
, Shen, Zhanfeng
, Dong, Di
, Luo, Jiancheng
in
Buildings
/ Climate change
/ Construction
/ Ecosystem services
/ Environmental conditions
/ Imagery
/ Mapping
/ Performance indices
/ Remote sensing
/ Shadow detection
/ Shadows
/ Support Vector Machine
/ Surface water
/ Threshold stability
/ Urban areas
/ Urban remote sensing
/ Urban water bodies
/ Urbanization
/ Water index
/ ZY-3
2015
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High-Resolution Mapping of Urban Surface Water Using ZY-3 Multi-Spectral Imagery
Journal Article
High-Resolution Mapping of Urban Surface Water Using ZY-3 Multi-Spectral Imagery
2015
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Overview
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.
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