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The Extraction of Urban Surface Water from Hyperspectral Data Based on Spectral Indices

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Abstract

To prevent confusion between water and buildings in the extraction of urban surface water from hyperspectral data, we analyzed the spectra of shadows and water in hyperspectral images, and proposed an anti-shadow water extraction method. This method first uses the normalized difference vegetation index (NDVI) for initial water extraction, then uses the height of the reflectance peak at 588 nm to eliminate the shadow of buildings. The method was validated by two hyperspectral datacubes, which were obtained for Jiaxing City and Zhoushan City in Zhejiang Province, China. Compared to the common spectral indices used to extract a water body, such as the NDVI, normalized difference water index, hyperspectral difference water index, and index of water index, the proposed method could effectively eliminate the shadow of buildings. The commission error reduced from more than 40% to about 15%, and the Kappa coefficient was increased from 60 and 70% to over 80% for the two datacubes. This indicated that the proposed method can inhibit the shadow of buildings and does not have a regional dependence.

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Correspondence to Feng Xie.

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Yang, J., Liu, C., Shu, R. et al. The Extraction of Urban Surface Water from Hyperspectral Data Based on Spectral Indices. J Indian Soc Remote Sens 46, 1749–1759 (2018). https://doi.org/10.1007/s12524-018-0828-5

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  • DOI: https://doi.org/10.1007/s12524-018-0828-5

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