## 4 Results  
Eleven NDWI models (Table 2) were used to extract water body information and map LSW from the ALI, TM, and ETM+ data. The results of the water body information detection and LSW maps derived from the ALI remote sensing images were compared with those derived from TM and ETM+ data at the three study sites. In the following section, we focus on analyzing the efficiency of the water body information enhancement and assessing the accuracy of LSW maps derived from the various images of the three regions generated using different NDWI models. We used TM data acquired on 2 May 2010, and ALI data acquired on 30 September 2010, in the comparative analysis of Region I. The contrast between water body features, including the Three Gorges Reservoir and the Yangtze River, and the background features, such as the Three Gorges Dam and the vegetation, is clear (Figure 2a,h). The subset of data from EO-1 ALI and Landsat TM images were used to generate eight water-body-enhanced images (Figure 2b,d,f,l,k,m,o,q). We used various thresholds (Table 3) applied to eight NDWI images to obtain eight LSW binary maps (Figure 2c,e,g,j,l,n,p,r). Each binary map has two classes: water and non-water areas. Visual interpretation indicates that the eight NDWI images of Region I all clearly show bodies of open water as the result of enhancement. Visual comparison also shows that the main water bodies were detected in the LSW maps (Figure 2c,e,g,j,l,n,p,r) and the boundaries of the mapped water bodies match the actual boundaries of the water bodies in the images closely. However, some inaccuracies and omissions occurred, for example, in Figure 2g,j,l,p,r. Figure 2: Original images and the resulting LSW maps from Landsat TM imagery and EO-1 ALI imagery in Region I. (**a**) Landsat TM image (2 May 2010) false-color composite (RGB: 752); (**b**) NDWI calculated from TM Bands 2 and 4; (**c**) LSW map of NDWI\({}_{\mathrm{T2,4}}\); (**d**) NDWI calculated from TM Bands 2 and 5; (**e**) LSW map of NDWI\({}_{\mathrm{T2,5}}\); (**f**) NDWI calculated from TM Bands 2 and 7; (**g**) LSW map of NDWI\({}_{\mathrm{T2,7}}\); (**h**) EO-1 ALI image (30 September 2010) false-color composite (RGB: 1094); (**i**) NDWI calculated from ALI Bands 4 and 6; (**j**) LSW map of NDWI\({}_{\mathrm{A4,6}}\); (**k**) NDWI calculated from ALI Bands 4 and 7; (**l**) LSW map of NDWI\({}_{\mathrm{A4,7}}\); (**m**) NDWI calculated from ALI Bands 4 and 8; (**n**) LSW map of NDWI\({}_{\mathrm{A4,8}}\); (**o**) NDWI calculated from ALI Bands 4 and 9; (**p**) LSW map of NDWI\({}_{\mathrm{A4,9}}\); (**q**) NDWI calculated from ALI Bands 4 and 10; (**r**) LSW map of NDWI\({}_{\mathrm{A4,10}}\). We then used the CV and BCV to assess the potential of eight NDWI models for water body information enhancement and the adaptability of image segmentation. The indexes OA and Kappa were used to evaluate the performance of LSW maps based on the eight NDWI images in Region I. First, we used the CV index to analyze the water body information enhancement of the eight NDWI images. The results of this quantitative assessment of Region I (Table 3) show that the maximum CV value of the five NDWI images derived from the ALI sensor is 0.713 (NDWI\({}_{A4,9}\)), followed by 0.638 (NDWI\({}_{A4,8}\)), 0.592 (NDWI\({}_{A4,10}\)), 0.438 (NDWI\({}_{A4,7}\)), and 0.341 (NDWI\({}_{A4,6}\)). According to the contrast method [34], the higher the CV value the better the enhancement of the water body features. These results mean that the combination of the green wavelength band (Band 4, 0.520-0.605 \(\upmu\)m) and the SWIR wavelength band (Band 9, 1.550-1.750 \(\upmu\)m) is the best indicator for water body information enhancement when the ALI data are employed to enhance water body information. Then, we used BCV to assess the image segmentation adaptability of the five NDWI images. Table 3 shows that the highest BCV value of the five ALI NDWI images was that of NDWI\({}_{A4,9}\) (0.111), followed by NDWI\({}_{A4,8}\) (0.090), NDWI\({}_{A4,10}\) (0.078), NDWI\({}_{A4,7}\) (0.043), and NDWI\({}_{A4,6}\) (0.026).