Abstract
Abstract. Water body plays an irreplaceable role in the global ecosystem and climate system. Sentinel-2 is a new satellite data with higher spatial and spectral resolution. Through analysing spectral characteristics of Sentinel-2 satellite imagery, the brightness of water body in vegetation red edge band and shortwave infrared band showe sharply different than that of the not water body. Therefore, a new type of water index SWI (Sentinel-2 Water Index) was proposed by combing those two bands. Four representative water types, which included Taihu Lake, the Yangtze River Estuary, the ChaKa Salt Lake and the Chain Lake, were selected as experimental areas. Normalized difference water index (NDWI) and Sentinel-2 Water Index (SWI) with Otsu method were employed to extract water body. The results showed that overall accuracy and Kappa coefficient of SWI were higher than that of NDWI and SWI was efficient index to rapidly and accurately extract water for Sentinel-2 data. Therefore, SWI had application potential for larger scale water mapping in the future.
Highlights
As an important part of global water cycle, the surface water body has an irreplaceable role in global ecology and climate system (Donchyts et al, 2016; Jiang et al, 2020; Pekel et al, 2016)
To compare the performance of extracting water, the index accuracy of normalized difference water index (NDWI) and Sentinel-2 Water Index (SWI) is analysed by the difference index between the water body and the background
The difference index of water and background is employed to analyse the accuracy of NDWI and SWI index, and the experimental area water and not water samples are choose to calculate the corresponding mean
Summary
As an important part of global water cycle, the surface water body has an irreplaceable role in global ecology and climate system (Donchyts et al, 2016; Jiang et al, 2020; Pekel et al, 2016). McFeeters made full use of the near infrared and visible light green bands of Landsat MSS data, and proposed a normalized difference water index (NDWI) (McFeeters, 1996). The index can effectively highlight the water body information and eliminate the soil and surface vegetation noise. Xu constructed a modified normalized difference water index (MNDWI) based on Landsat TM/ETM+ data, which can overcome the shortcomings of NDWI index, and enhance water environment characteristic information (Xu, 2006). The index can further solve the mountain shadow caused by terrain that the MNDWI index failed to eliminate. These indices have good effects on water extraction from Landsat series satellites
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