# An Effective Water Body Extraction Method with New Water Index for Sentinel-2 Imagery
## 3 Methods  
### Analysis of the Spectral Response Mechanism  
By using the difference in the reflectance values between the target objects in different bands, the brightness value of the target objects can be enhanced and the brightness value of the background objects will be suppressed. Based on this principle, [PERSON] constructed the NDWI using green and NIR band extracted from the Landsat 5 data, which can effectively suppress soil and vegetation information and enhance water [14]. This formula is as follows.  
\[NDWI=\frac{\rho_{Green}-\rho_{NIR}}{\rho_{Green}+\rho_{NIR}} \tag{1}\]  
In the formula, \(\rho_{Green}\) denotes the reflectance of the green band (Band 3 of the Sentinel-2 data) and \(\rho_{NIR}\) denotes the reflectance of the near-infrared band (Band 8 of the Sentinel-2 imagery).  
[PERSON] found that the buildings would be easily confused with water using NDWI due to the near-infrared band and the reflectance of buildings is suddenly enhanced from the near-infrared to the SWIR band [15]. Therefore, the SWIR band is used instead of the NIR band in the MNDWI and the building noise can be effectively suppressed to enhance water bodies. This formula is as follows.  
\[MNDWI=\frac{\rho_{Green}-\rho_{SWIR}}{\rho_{Green}+\rho_{SWIR}} \tag{2}\]  
Figure 1: Locations of the study areas.  
In the formula, \(\rho_{Green}\) denotes the reflectance of the green band, which corresponds to Band 3 of the Sentinel-2 data, and \(\rho_{SWIR2}\) denotes the reflectance of the SWIR2 band, which corresponds to Band 11 of the Sentinel-2 imagery.  
For Sentinel-2, the spatial resolution of the SWIR2 band is 20 m and the spatial resolutions of the NIR and green bands are both 10 m. Thus, the NDWI can be directly calculated, while the MNDWI cannot be directly determined due to the different spatial resolutions. Compared with the Landsat sensor, the Sentinel-2 sensor has not only improved resolution but also introduced a vegetation-sensitive red-edge band. Therefore, the spectral response mechanism requires analysis to explore the new water index for Sentinel-2 imagery. The TOA reflectance was derived from different land cover types and water types to generate the spectral curves in Figure 2. Figure 2a shows the spectral curves of the ground objects in study area A and Figure 2b shows the spectral curves of the water bodies in study areas B, C, and D.  
As shown in Figure 2a, the reflectance of the general water gradually decreases. However, the reflectance values of buildings, vegetation, and bare land increased from the green band (Band 3) to the near-infrared band (Band 8) or from the VRE1 band (Band 5) to the SWIR2 band (Band 11). Therefore, Band 5 and Band 11 can effectively enhance the general water bodies and suppress the buildings and bare land noise. Relative to various water bodies, such as reflected in Figure 2b, the reflectance difference between turbid water and floating ice in the green and NIR band is small and the difference in the reflectance of salt water bodies between the VRE1 band (Band 5) and the SWIR2 band (Band 11) is significant. By utilizing the above analysis, Band 5 and Band 11 with same spatial resolution are suitable for constructing a water index for Sentinel-2 imagery. Thus, a novel water index data at 20 m resolution was constructed using Sentinel-2 imagery, which is reflected in the following formula.  
\[SWI=\frac{\rho_{VRE1}-\rho_{SWIR2}}{\rho_{VRE1}+\rho_{SWIR2}} \tag{3}\]  
In the formula, SWI represents the Sentinel-2 water index, \(\rho_{\text{VRE1}}\) represents the VRE1 band (Band 5 of the Sentinel-2 imagery), and \(\rho_{SWIR2}\) represents the SWIR2 band (Band 11 of the Sentinel-2 imagery).