# An Effective Water Body Extraction Method with New Water Index for Sentinel-2 Imagery
## 5 Discussion  
Sentinel-2 produces widely used remote sensor imagery with high spatial resolution and a short return period and this imagery has great application potential in large-scale surface water mapping [39; 40]. By investigating the spectral response mechanism of Sentinel-2, a new water index, namely, the SWI, was proposed to extract various water body types with [PERSON]'s method. Moreover, the extraction performance and precision suggest that the novel method is simple and effective. However, there is still some matters with respect to the application scope that requires discussion. Firstly, the spatial resolution and selected SWI response band were balanced. The highest spatial resolution of Sentinel-2 is 10 m, while Band 5 and Band 11 with 20 m spatial resolution were employed to establish the SWI to enhance the water body information. By comparing the enhancement performance of the NDWI at a 10 m spatial resolution with that of the SWI at a 20 m spatial resolution (Figure 7), the results demonstrate that the enhancement performance of the SWI is better than that of the NDWI (Figure 7b,c). Compared with the extraction results of the NDWI, the extracted water bodies of the SWI are more complete and accurate and a comparison (Figure 7f) shows that the river channels are missed using NDWI at a 10-m resolution [41]. In addition, a previous study generated 10m MNDWI from Sentinel-2 imagery by sharpening the SWIR band and the results demonstrated that MNDWI can produce more accurate extraction results [32]. However, the complexity of the pansharpening algorithm restricts the efficiency of water body mapping. Therefore, from the perspective of water extraction performance and efficiency comparing the various water indices, the selection of response bands is more important than spatial resolution. Secondly, the applicability of the proposed method in urban areas was assessed. Due to the complex background of urban areas and building shadows, it is a great challenge to use water indices to extract water bodies in urban areas [42]. In order to investigate the applicability of the SWI in urban areas, four cities surrounding Taihu Lake, namely, Suzhou, Jiaxing, Wuxi, and Huzhou, were selected to conduct the water body extraction performance comparison using the NDWI and SWI. The extraction results are shown in Figure 8. Blue regions indicate water bodies extracted by both the NDWI and SWI; red regions indicate water bodies extracted by the SWI but not by the NDWI; and purple regions indicate water bodies extracted by the NDWI but not by the SWI. Hence, the blue and red regions represent water bodies extracted by the SWI and the blue and purple regions indicate water bodies extracted by the NDWI. The results of water body extraction in urban areas (Figure 8) have yielded several findings: (1) Large water bodies can be extracted well with both the SWI and NDWI, especially the lakes and connected open water bodies in Figure 8b,c; (2) wide river channels are significantly missed using the NDWI in Figure 8d but are accurately extracted by the SWI; (3) severe mixing of building shadows and water bodies occurs when using the NDWI in Figure 8(a1,c1), which may indicate that the NDWI has difficulty eliminating shadow noise; (4) the NDWI can accurately extract small water bodies and narrow river channels in Figure 8(b1,c1). This pattern is due to the difference in the resolution between the SWI and the NDWI and the SWI cannot effectively extract the subpixel water bodies from the super-resolution maps. Therefore, the SWI can accurately extract large water bodies and wide river channels in urban areas but cannot effectively extract narrow rivers because the SWI is calculated based on 20 m response bands. There are two reasons why SWI can result in better extraction performance regarding the various water body types.