## 4 Results
### Experiment in Abrupt Change Area (Flood)  
From the visual comparison, only FSDAF and EFSDAF can capture the information of land cover change in Figure 7, it can be more clearly and accurately seen from the zoom-in black area in Figure 8. In addition, the spatial details restored by EFSDAF are most complete and most similar with the true image from the yellow elliptical circles of Figure 7. From the yellow elliptical circles of Figure 8, the small flood change information can be accurately captured by EFSDAF, but it cannot be captured by FSDAF. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & **STARFM** & **STRUM** & **FSDAF** & **EFSDAF** \\ \hline \multirow{6}{*}{AD} & B1 & 0.0267 & 0.0264 & 0.0262 & 0.0260 \\  & B2 & 0.0205 & 0.0203 & 0.0197 & 0.0197 \\  & B3 & 0.0176 & 0.0182 & 0.0169 & 0.0167 \\  & B4 & 0.0442 & 0.0480 & 0.0385 & 0.0379 \\  & B5 & 0.0244 & 0.0237 & 0.0233 & 0.0209 \\  & B7 & 0.0250 & 0.0266 & 0.0237 & 0.0226 \\  & Mean & 0.0264 & 0.0272 & 0.0247 & 0.0225 \\ \hline \multirow{6}{*}{RMSE} & B1 & 0.0319 & 0.0299 & 0.0295 & 0.0284 \\  & B2 & 0.0270 & 0.0250 & 0.0245 & 0.0229 \\  & B3 & 0.0249 & 0.0244 & 0.0232 & 0.0212 \\  & B4 & 0.0588 & 0.0646 & 0.0542 & 0.0504 \\  & B5 & 0.0329 & 0.0322 & 0.0310 & 0.0270 \\  & B7 & 0.0341 & 0.0363 & 0.0322 & 0.0297 \\  & Mean & 0.0349 & 0.0354 & 0.0324 & 0.0299 \\ \hline \multirow{6}{*}{CC} & B1 & 0.653 & 0.732 & 0.778 & 0.803 \\  & B2 & 0.724 & 0.781 & 0.812 & 0.845 \\  & B3 & 0.852 & 0.869 & 0.895 & 0.915 \\  & B4 & 0.891 & 0.850 & 0.897 & 0.914 \\  & B5 & 0.856 & 0.871 & 0.880 & 0.918 \\  & B7 & 0.865 & 0.853 & 0.886 & 0.905 \\  & Mean & 0.807 & 0.826 & 0.858 & 0.883 \\ \hline \multirow{6}{*}{SSIM} & B1 & 0.504 & 0.575 & 0.617 & 0.632 \\  & B2 & 0.683 & 0.744 & 0.798 & 0.804 \\ \cline{1-1}  & B3 & 0.836 & 0.852 & 0.865 & 0.890 \\ \cline{1-1}  & B4 & 0.885 & 0.848 & 0.893 & 0.902 \\ \cline{1-1}  & B5 & 0.854 & 0.869 & 0.887 & 0.908 \\ \cline{1-1}  & B7 & 0.862 & 0.848 & 0.881 & 0.892 \\ \cline{1-1}  & Mean & 0.771 & 0.789 & 0.823 & 0.839 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: The quantitative assessment of the Landsat-like images by STARFM, STRUM, FSDAF, and EFSDAF in dataset 1. Figure 7: Visual comparison of Landsat-like images predicted by STARFM, STRUM, FSDAF, and EFSDAF in dataset 2 (flood). From left to right, green-red-NIR (standard false color) composites of (**a**) true Landsat image of 12 December 2004; (**b–e**) predicted images of 12 December 2004 by STARFM, STRUM, FSDAF, and EFSDAF, respectively. (Figure 7 presents the predicted Landsat-like images of 12 December 2004 by four fusion methods in the abrupt change area, and the yellow elliptical circles of Figure 7 represent the differences of the four fusion methods. The zoom-in black square areas marked in Figure 7 are used to more clearly compare the fusion results by the four methods in the land cover change area (Figure 8)). Comparing the results of the quantitative indices in Table 2, STARFM and STRUM present similar results, and EFSDAF is better than FSDAF (CC 0.808 vs. 0.827, SSIM 0.796 vs. 0.815 for band 4). Furthermore, since the water body information shows lower reflectivity for band 4 (NIR), we compare the scatter plots of band 4 for the four methods in Figure 9. It can be concluded that FSDAF and EFSDAF are far superior to STARFM and STRUM, and EFSDAF is better than FSDAF.