## 4 Results
### Sea Fog Identification
#### 4.1.2 Sea Fog Statistics  
We applied the constructed sea fog identification algorithm to AHI data to get the sea fog information of 1442 days in the study area from 2016 to 2019, and calculated the sea fog occurrence of each grid in the four seasons. The location of Bohai Sea is about 37\({}^{\circ}\) N, and according to the climate of the region, we set February to April as spring, May to July as summer, August to October as autumn, and November to January of the next year as winter. Following these classifications, the fog occurrence of the four seasons in the study area is shown in Figure 10.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Methods** & **POD** & **PMD** & **PFD** & **ETS** \\ \hline MLP & 81.48\% & 7.62\% & 18.51\% & 59.22\% \\ NDSI threshold & 88.89\% & 33.63\% & 11.11\% & 31.61\% \\ \hline \hline \end{tabular}
\end{table}
Table 6: Accuracy of sea fog classification.  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **Sea Fog** & **Non-Sea Fog** \\ \hline \multirow{3}{*}{Sea fog} & H & F \\ \cline{2-3}  & MLP & 88 & 17 \\  & NDSI & 96 & 75 \\ \hline \multirow{3}{*}{Non-sea-fog} & M & C \\ \cline{2-3}  & MLP & 20 & 206 \\  & NDSI & 12 & 148 \\ \hline \hline \end{tabular}
\end{table}
Table 5: Confusion matrix of sea fog classification.  
The sea fog in the study areas begins from the winter, and goes until the next autumn. The occurrence frequencies of sea fog in spring and summer are higher, while those in autumn and winter are lower; thus, the seasonal occurrence of sea fog shows obvious differences. From winter to the next autumn, the high incidence area of sea fog shows a trend of developing from south to north, and from west to north.  
From the perspective of spatial distribution, in winter, the higher frequency areas of sea fog are in the west of Bohai Sea, and with an eastward movement tendency with time. In spring, higher frequency areas of sea fog are in the Yellow Sea and south of Bohai Sea, with a northward movement tendency with time. The two tendencies gather in the south of Bohai Bay in summer, when the frequency of sea fog reaches its highest value in the whole year.  
On the other side, the frequency of sea fog in spring and summer is greater than that in autumn and winter, and in winter, strong winds are frequent, which have a greater impact on navigation than sea fog (Kal  
The matching degree of the navigation risk evaluation model is 69.9%. In summer, the matching degree reaches 85%, where only one accident point is not successfully matched. In winter, the matching rate is low, only 33%, and four accident points are not successfully matched. Of the four unsuccessfully matched accident points in winter, three are concentrated on the eastern side of Bohai Sea, and occur around a similar time (within three days) and in a similar area. The concentrated accidents have high randomness, leading to a low matching degree in winter. Except for winter, the matching degrees of accidents in the other three seasons are good, where only 1-2 points are not matched successfully. In the fog season (spring and summer), the matching degree of the proposed model reaches 80%; thus, the evaluation performance is great in the fog season.  
It should be noted that the small amount of accident information is distributed randomly in space and time. The overall matching degree of the model is 69.9%, and the matching degree during the fog season is 80%. It can be considered that the model has a good matching ability to accidents in the case of limited accident data, especially for fog seasons.