Abstract

Satellite-based remote sensing is important for monitoring the spatial distribution of water resources. The water index is currently one of the most widely used water body extraction methods. Based on Sentinel-2 remote sensing image, this study combines area-to-point regression kriging interpolation, bilinear interpolation, and the Gram–Schmidt (GS) pan-sharpening method with the water indices MNDWI, AWEIsh and WI2015 to compare different water body extraction methods. The experimental results showed that all water indices have satisfactory extraction ability, with the kappa coefficient as an accuracy threshold above 0.8. Moreover, the GS downscaling method combined with the WI2015 yielded the best performance. This research demonstrates the efficacy of the WI2015 method to extract water bodies in urban areas and its ability to comprehensively describe river water bodies. The findings indicate that high-resolution band information is particularly important for improving low-resolution band downscaling results and can significantly minimize erroneous water body extraction.

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