## 4 Results
We next used the OA and Kappa to quantitatively assess the accuracy of the eight NDWI LSW maps of Region I. This quantitative assessment was performed in three steps. First, the reference data were selected. As water bodies and the LSW distribution move and change over time [11,40], it is best to use high-spatial-resolution data or a multispectral image taken at the same time as the reference data to minimize any time-dependent effects. The acquisition dates of the ALI and TM data used in Region I were September 2010, and May 2010, respectively. Thus, we selected the ALI panchromatic image, which has 10 m spatial resolution and was acquired at the same time as the ALI multispectral images, as the reference data to assess the accuracy of the five LSW maps derived from the ALI sensor. We used the false-color composite image acquired at the same time as TM, _i.e.,_ RGB752, which best enhances the water body information [11], as the reference data to evaluate the accuracy of the three LSW maps resulting from the Landsat TM images. Second, the selected reference data were visually interpreted by one person and checked by two people to produce the reference data; all three people were familiar with the study area. Next, we used the pixel-by-pixel comparison method [34,46] to assess the accuracy of these LSW maps using the reference data. Then, error matrixes were created to obtain OA and Kappa. Table 3 shows that the accuracy is relatively stable among the five ALI LSW maps, with the maps of \(\mathrm{NDWI_{A4,6}}\), \(\mathrm{NDWI_{A4,7}}\), \(\mathrm{NDWI_{A4,8}}\), \(\mathrm{NDWI_{A4,9}}\), and \(\mathrm{NDWI_{A4,10}}\) having OA of 94.23%, 95.54%, 95.89%, 96.67%, and 95.86%, respectively, and Kappa of 0.8673, 0.8962, 0.9040, 0.9235, and 0.9034, respectively. The quantitative assessment results (Table 3) show that \(\mathrm{NDWI_{A4,9}}\) had the highest OA and Kappa values; next highest were \(\mathrm{NDWI_{A4,8}}\), \(\mathrm{NDWI_{A4,10}}\), \(\mathrm{NDWI_{A4,7}}\), and \(\mathrm{NDWI_{A4,6}}\). The maximum values of OA and Kappa for the TM sensor come from \(\mathrm{NDWI_{T2,5}}\), followed by \(\mathrm{NDWI_{T2,7}}\), and \(\mathrm{NDWI_{T2,4}}\). The accuracy of LSW maps as assessed using OA and Kappa are consistent with the results of the analysis based on CV and BCV. The areas of LSW in Region I identified from the TM data were 22.89 \(\mathrm{km}^{2}\) (as measured by \(\mathrm{NDWI_{T2,4}}\)), 20.85 \(\mathrm{km}^{2}\) (\(\mathrm{NDWI_{T2,5}}\)), or 20.77 \(\mathrm{km}^{2}\) (\(\mathrm{NDWI_{T2,7}}\)) (Table 3). The LSW areas derived from the ALI data were 22.43 \(\mathrm{km}^{2}\) (\(\mathrm{NDWI_{A4,6}}\)), 21.57 \(\mathrm{km}^{2}\) (\(\mathrm{NDWI_{A4,7}}\)), 21.33 \(\mathrm{km}^{2}\) (\(\mathrm{NDWI_{A4,8}}\)), 20.73 \(\mathrm{km}^{2}\) (\(\mathrm{NDWI_{A4,9}}\)), or 21.34 \(\mathrm{km}^{2}\) (\(\mathrm{NDWI_{A4,10}}\)). Based on the above analyses, we conclude that the normalized difference water index based on the green band (_i.e.,_ Band 4 of ALI or Band 2 of TM) and the SWIR band (_i.e.,_ Band 9 of ALI or Band 5 of TM) with the spectrum region of 1.550-1.750 \(\upmu\)m, that is, Xu's NDWI or MNDWI, is the optimal choice for water body information enhancement and LSW mapping. Figure 3: Original images and the LSW map results from Landsat TM imagery and EO-1 ALI imagery in Region II.