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Improving Super-Resolution Flood Inundation Mapping for Multispectral Remote Sensing Image by Supplying More Spectral Information

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Super-resolution mapping is an effective technique in mapping flood inundation for multispectral remote sensing image. However, the traditional super-resolution flood inundation mapping (SRFIM) is unable to fully utilize the spectral… Click to show full abstract

Super-resolution mapping is an effective technique in mapping flood inundation for multispectral remote sensing image. However, the traditional super-resolution flood inundation mapping (SRFIM) is unable to fully utilize the spectral information from multispectral remote sensing image band. In order to resolve this problem, a novel SRFIM by supplying more spectral information (SRFIM-MSI) is proposed to improve mapping accuracy. In the proposed SRFIM-MSI, the spectral information from the multispectral band is calculated by the normalized difference water index (NDWI). A spectral term constituted by NDWI is added into the traditional SRFIM. The proposed method is evaluated by using two Landsat 8 OLI multispectral data from the study area in Cambodia. The obtained results demonstrate that the proposed SRFIM-MSI produces better results than the traditional SRFIM methods.

Keywords: spectral information; remote sensing; flood inundation; super resolution

Journal Title: IEEE Geoscience and Remote Sensing Letters
Year Published: 2019

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