## 3 Results and Discussion
\begin{table}
\begin{tabular}{l c c c c c c c} \hline
2014 & CART & RF & SVM & 2017 & CART & RF & SVM \\ \hline \multicolumn{8}{c}{NDWI} \\ \hline Producer accuracy & 1 & 1 & 1 & Producer accuracy & 0.98 & 0.98 & 0.99 \\ User accuracy & 1 & 1 & 1 & User accuracy & 0.97 & 0.97 & 0.98 \\ Overall accuracy & 1 & 1 & 1 & Overall accuracy & 0.93 & 0.94 & 0.98 \\ Kappa & 1 & 1 & 1 & Kappa & 0.94 & 0.96 & 0.98 \\ F score & 1 & 1 & 1 & F score & 0.96 & 0.97 & 0.99 \\ \hline \multicolumn{8}{c}{MNDWI} \\ \hline Producer accuracy & 0.98 & 0.98 & 0.99 & Producer accuracy & 0.94 & 0.86 & 0.95 \\ User accuracy & 0.97 & 0.98 & 0.98 & User accuracy & 0.92 & 0.81 & 0.93 \\ Overall accuracy & 0.94 & 0.97 & 0.97 & Overall accuracy & 0.87 & 0.67 & 0.87 \\ Kappa & 0.95 & 0.98 & 0.98 & Kappa & 0.87 & 0.70 & 0.89 \\ F score & 0.97 & 0.98 & 0.99 & F score & 0.91 & 0.89 & 0.93 \\ \hline \multicolumn{8}{c}{AWEI} \\ \hline Producer accuracy & 1 & 1 & 1 & Producer accuracy & 0.99 & 0.99 & 1 \\ User accuracy & 1 & 1 & 1 & User accuracy & 0.99 & 0.98 & 1 \\ Overall accuracy & 1 & 1 & 1 & Overall accuracy & 0.99 & 0.99 & 1 \\ Kappa & 1 & 1 & 1 & Kappa & 0.98 & 0.98 & 1 \\ F score & 1 & 1 & 1 & F score & 0.99 & 0.99 & 1 \\ \hline \multicolumn{8}{c}{NDWI} \\ \hline Producer accuracy & 0.99 & 0.99 & 1 & Producer accuracy & 0.93 & 0.93 & 0.94 \\ User accuracy & 0.98 & 0.98 & 1 & User accuracy & 0.91 & 0.90 & 0.91 \\ Overall accuracy & 0.97 & 0.98 & 1 & Overall accuracy & 0.81 & 0.80 & 0.83 \\ Kappa & 0.98 & 0.98 & 1 & Kappa & 0.84 & 0.83 & 0.86 \\ F score & 0.98 & 0.99 & 1 & F score & 0.90 & 0.94 & 0.95 \\ \hline \multicolumn{8}{c}{MNDWI} \\ \hline Producer accuracy & 0.97 & 0.95 & 0.96 & Producer accuracy & 0.92 & 0.92 & 0.95 \\ User accuracy & 0.97 & 0.94 & 0.93 & User accuracy & 0.89 & 0.88 & 0.93 \\ Overall accuracy & 0.96 & 0.90 & 0.90 & Overall accuracy & 0.82 & 0.83 & 0.89 \\ Kappa & 0.95 & 0.91 & 0.92 & Kappa & 0.85 & 0.83 & 0.91 \\ F score & 0.97 & 0.93 & 0.94 & F score & 0.90 & 0.90 & 0.94 \\ \hline \multicolumn{8}{c}{AWEI} \\ \hline Producer accuracy & 0.97 & 0.99 & 0.98 & Producer accuracy & 1 & 0.99 & 1 \\ User accuracy & 0.94 & 0.98 & User accuracy & 1 & 0.99 & 1 \\ Overall accuracy & 0.95 & 0.99 & 0.97 & Overall accuracy & 1 & 0.98 & 1 \\ Kappa & 0.95 & 0.98 & 0.97 & Kappa & 1 & 0.98 & 1 \\ F score & 0.98 & 0.99 & 0.99 & F score & 1 & 0.99 & 1 \\ \hline \end{tabular}
\end{table} 
Table 2: Classification accuracies for different water indices and classification methods, that is, CART, RF, and SVM. and f score evaluation criteria obtained by using CART, SVM, and RF algorithms, NDWI and AWEI in 2014 were obtained as 100%. In 2017, the highest values of the producer accuracy, user accuracy, overall accuracy, kappa, and f score evaluation criteria obtained using the SVM algorithm and AWEI were obtained as 100%. The lowest values were obtained using the MNDWI and RF method as 0.86, 0.81, 0.67, 0.70, and 0.89, respectively. In 2020, the highest values of the producer accuracy, user accuracy, overall accuracy, kappa, and f score evaluation criteria obtained using the SVM algorithm and NDWI were obtained as 100%. Using the MNDWI and RF method at the lowest values, 0.95, 0.94, 0.90, 0.91, 0.93 were obtained, respectively. In 2023, the highest values of the producer accuracy, user accuracy, overall accuracy, kappa, and f score evaluation criteria obtained using SVM and CART algorithms and the AWEI were obtained as 100%. Using the MNDWI and NDWI and RF and CART methods at the lowest values in f score, 0.90 were obtained. The lake area results obtained by the band combination of MNDWI and B6 bands are displayed in Figure 6, and the classification results are also shown in Table 2. Water pixels are organized based on their greater NDWI and lower SWIR values due to greater water absorption at the SWIR2 wavelength. The NDWI aims to increase water reflectance, decrease low NIR reflectance from water features, and utilize green wavelengths by using the high NIR reflectance from plant and soil properties.