## 3 Results
### Performance Comparison of RTI and U-Net  
Figure 8 shows ground-truth and red tide maps generated through RTI and four U-Net models from a PlanetScope image around the coast of Goheung on 29 July 2018, at 01:42 GMT. Referring to the ground truths, the red tide pattern from RTI appeared relatively appropriate. However, RTI tended to identify the turbid waters as the red tide waters. In the red tide map based on U-Net #1 and U-Net #2, which were trained using only red tide patches, red tide areas were overestimated in all water types. In particular, the edge pixels of each patch tended to be identified as red tide pixels. Even some land areas were recognized as red tide pixels. On the other hand, red tide maps based on U-Net #3 and U-Net #4, which were trained with the mixed red tide and non-red tide patches, showed reasonable red tide patterns compared to the other U-Net models. However, in the case of U-Net #3, the edge pixels of patches and the turbid waters were still recognized as \begin{table}
\begin{tabular}{l l c c c c c c c c c c} \hline \hline  & \multirow{2}{*}{\begin{tabular}{c} **Random** \\ **Sampling** \\ \end{tabular} } & \multicolumn{3}{c}{**Pixel Ratio**} & \multicolumn{3}{c}{**Patches of Test Datasets**} & \multicolumn{3}{c}{**36 PlanetScope Images**} \\ \cline{3-13}  & & \
\begin{tabular}{c} **Non-Red** \\ **Tide Pixel** \\ \end{tabular} &
\begin{tabular}{c} **Red Tide** \\ **Pixel** \\ \end{tabular} & \multirow{2}{*}{**Accu.**} & \multirow{2}{*}{**Sens.**} & \multirow{2}{*}{**Prec.**} & \multicolumn{2}{c}{**F-**} & \multirow{2}{*}{**Accu.**} & \multirow{2}{*}{**Sens.**} & \multirow{2}{*}{**Prec.**} & \multicolumn{2}{c}{**F-**} \\ \cline{3-13}  & & & & & & & & & & **Measure** & & **Measure** \\ \hline U-Net \#1 & Yes & 0.45 & 0.55 & 0.61 & 0.73 & 0.62 & 0.67 & 0.82 & 0.69 & 0.05 & 0.08 \\ U-Net \#2 & No & 0.45 & 0.55 & 0.60 & 0.74 & 0.61 & 0.67 & 0.77 & 0.76 & 0.03 & 0.06 \\ U-Net \#3 & Yes & 0.66 & 0.34 & 0.65 & 0.37 & 0.48 & 0.42 & 0.94 & 0.39 & 0.09 & 0.10 \\ U-Net \#4 & No & 0.66 & 0.34 & 0.71 & 0.61 & 0.61 & 0.61 & 0.88 & 0.60 & 0.07 & 0.11 \\ \hline \hline \end{tabular}  
* Accu.: Accuracy; Sens.: Sensitivity; Prec.: Precision.  
\end{table} 
Table 5: Quantitative performance of U-Net models trained (50 mini-batches, 50 epochs) with four different training and test datasets. Four datasets were chosen randomly or non-randomly with different ratios of non-red tide and red tide pixels. Four FOMs of the models were evaluated using patches of test datasets and 36 PlanetScope images. red tide pixels. U-Net #4 trained with non-randomly selected non-red tide and red-tide patches showed the most reasonable red tide patterns in all water areas. We compared the quantitative performances of RTI and U-Net #4 for the 36 PlanetScope images in Table 6. We evaluated FOMs for three different areas of red tide occurrence: low extent (LE), middle extent (ME), and high extent (HE) groups. LE indicates red tide areas <5 km\({}^{2}\), ME refers to areas of 5-10 km\({}^{2}\), and HE refers to an area of more than 10 km\({}^{2}\). For the performance of the RTI and U-Net #4, the accuracy was similar in each group. However, compared with the RTI, the FOMs of U-Net #4 were improved. The sensitivity of U-Net #4 in the LE and HE groups increased by 22% and 32%, respectively. The precision of U-Net #4 in LE, ME, and HE increased by 33%, 78%, and 40%, respectively. The F-measure of U-Net #4 in the ME and HE groups increased by 57% and 35%, respectively. Figure 9 shows the red tide areas extracted from the RTI, U-Net #4, and ground-truth  
Figure 8: Ground-truth and red tide maps generated by RTI and four U-Net models in the three water types of turbid, surrounding, and red tide waters from a PlanetScope image acquired on 29 July 2018 at 01:42 GMT near the coast of Goheung. Red tide pixel was marked in red. maps of 36 PlanetScope images. The red tide areas extracted from the RTI and U-Net #4 were wider than those in the ground-truth areas.