## 4 Results
### Accuracy Assessment at Two Sites
#### 4.3.2 Comparison with the Otsu Method at the WeiFang Site  
To further test our proposed threshold, the results of images from the WeiFang site on 26 August 2018 were compared using the Otsu method. Table 3 showed that the difference between our proposed method regarding the global image and the high group in terms of overall accuracy was 0.01. The differences in the other three evaluation metrics were also small and were controlled within 0.05. However, in the low group and medium group images of a 20 km \(\times\) 20 km block, the classification results of our method were significantly better than those using the Otsu method, especially in the two sets of comparison results for medium and low groups. In the experiments of the medium group, the overall accuracies \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{**Data**} & **Overall Accuracy** & \multirow{2}{*}{**Kappa Coefficient**} & \multicolumn{2}{c}{**Commission Error**} & \multicolumn{2}{c}{**Omission Error**} \\ \cline{3-7}  & & **Lands** & **Water** & **Land** & **Water** \\ \hline
1 June 2019 & 95.00\% & 0.7715 & 3.41\% & 16.67\% & 2.30\% & 23.08\% \\
13 June 2019 & 96.00\% & 0.8172 & 2.84\% & 12.50\% & 1.72\% & 19.23\% \\
25 June 2019 & 94.50\% & 0.7443 & 3.95\% & 17.39\% & 2.30\% & 26.92\% \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Accuracy estimate of the Ji’An site using GF-3. Figure 8: Inundation range at the WeiFang site during the flood period. The blue portion represents the persistent open water. The green portion indicates the inundation range. The image on the right is a Sentinel-1 image from 21 July 2018.  
were 96% and 84%, respectively, with a difference of 0.12, and the kappa coefficients were about 0.2. However, it was found that the land commission error and water omission error of the two methods were similar, except that the land commission error and water omission error differed significantly, with the difference of \(-\)0.29 (9.63% vs. 38.16%) and \(-\)0.16 (3.33% vs. 19.33%), respectively. In the low group, the difference between the two methods was more obvious. The difference in overall accuracy was 0.17. The other five metrics also showed the same pattern as the medium group. This indicated that our method had better accuracy on small blocks. Moreover, the values of the four experimental groups were increasing as the area of water decreased, which indicated that the smaller the area of water in the image to be classified, the more obvious the something of our proposed method. It further illustrated the superiority of our method in areas with smaller bodies of water. Specifically, the two methods had a similar classification accuracy for water bodies, but the Otsu method for land showed less sensitivity. Figure 9 showed the classification images of the two methods. In addition, in terms of efficiency, the computation time of both methods showed that the proposed method was more efficient (Table 4). The average computation time of our method was 0.1 s, while the comparison of the Otsu method was 0.25 s (Table 5). In all nine sets of test experiments, the AT-EWC method outperformed the Otsu method in terms of speed.