# An Effective Water Body Extraction Method with New Water Index for Sentinel-2 Imagery
## 1 Introduction  
As an important part of the global water cycle, surface water bodies have an irreplaceable role in global ecology and climate systems [1, 2]. Surface water usually includes rivers, lakes, and reservoirs with obvious seasonal variations [3, 4, 5]. Therefore, the rapid and accurate monitoring of surface water is of great significance to hydrological processes and water resource management [6, 7]. Unlike traditional field measurements, remote sensing imagery is macrographic, dynamic, and inexpensive and can obtain surface information in real time [8, 9]. Therefore, remote sensing technology has been widely used in regional-scale and global-scale surface water mapping [10, 11, 11]. The methods of extracting water bodies from optical imagery include the single-band threshold method [13], water indexmethod [14; 15; 16], remote sensing image classification method [17; 18], mixed pixel decomposition method [19; 20; 21], and multisource data combination method [20; 22]. However, considering the precision requirement and the complexity of the methods, the water index method is one of the most convenient and highly precise water extraction methods [23]. [PERSON] made full use of the near-infrared (NIR) and visible light green bands of the Landsat Multispectral Scanner (MSS) data and proposed the normalized difference water index (NDWI). The index can effectively highlight the water body information and eliminate soil and surface vegetation, but it misses built-up areas [14]. In the referenced paper [15], [PERSON] proposed the modified normalized difference water index (MNDWI) based on Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) data, which can not only overcome the shortcomings of NDWI but also reveal characteristic information, such as the water environment. The multiband water index, namely, the automated water extraction index (AWEI), was built for Landsat TM data, which can further handle mountain shadows caused by the terrain that the MNDWI fails to eliminate [23]. Although these indices have good effects for water extraction from Landsat series satellites, a slight change in the spectral range of the corresponding wavebands for different sensors may lead to a change in the water extraction results. Therefore, modified waters have been widely explored for various satellite sensors [16; 24]. In the referenced paper [25], the slope and NIR band are combined to construct the normalized difference vegetation index (NDVI) and NDWI and then the index is applied to HuanJing (HJ)-1A/B satellite images for water extraction; the result is then finally consistent with the MNDWI results based on the Landsat TM data. In the referenced paper [26], a water index, namely, the linear discriminant analysis water index (LDAWI), was proposed to identify water bodies in SPOT5 satellite imagery and the index achieved good performance with an overall accuracy of 98%. For Gaofen-1 satellite remote sensing imagery, the NDWI and modified two-mode method were combined to extract surface water and the results suggested that the proposed method has higher and stable mapping accuracy [27]. Sentinel-2 is a new satellite launched by the European Space Agency (ESA), which can obtain global satellite data with a wide width and multispectral band and has been successfully applied in surface water mapping [28; 29; 30; 31]. Due to the multispectral advantage of Sentinel-2, the NDWI with threshold adjustment is a simple and effective method to extract water bodies [32; 33]. In the referenced paper [33], the NDWI and MNDWI with different bands from Sentinel-2 was evaluated and the results suggested that object-level MNDWI with Band 11 can achieve feasible water extraction performance. Due to the different spatial resolutions between shortwave infrared (SWIR) bands and optical bands, spatial resampling or band sharpening should be conducted before calculating water indices [32; 33]. Recently, different pansharpening algorithm comparisons of NDWI and MNDWI water indices were conducted.