# Development of Fog Detection Algorithm Using GK2A/AMI and Ground Data
## 3 Results
### Validation Results of Fog Detection Algorithm  
#### 3.2.1 Fog Detection Results  
Fog detection results from the GK2A/AMI data set are shown in Figures 7-10 along with the fog detection results of CMDPS, fog product of RGB composite using GK2A, image of the visible channel (0.64 \(\upmu\)m), and ground-observed visibility data. Qualitative analysis was conducted by selecting two fog cases from the training cases (Figures 7 and 8) and validation cases (Figures 9 and 10), respectively. To qualitatively evaluate the detection level based on fog intensity, the two fog cases (strong and wide area, weak and local fogs) were used. As shown in the visibility meter and color composite (Figure 7b,d), the fog was strong and widespread in most parts of South Korea. This was a typical radiation fog that occurred in the inland areas of South Korea during fall. The visual comparison of fog detection results with the visibility data and color composite indicated that both GK2A_FDA and CMDPS effectively detected the fog in terms of spatial distribution in South Korea (Figure 7a,c). Compared to the visibility and color composite map, GK2A_FDA appeared to slightly over-detect the fog. Figure 6: Frequency distribution of the optical/textural properties of fog pixels in the training cases at nighttime (**a**,**b**) and daytime (**c**,**d**) on the coast. (**a**) DCD, (**b**,**d**) \(\Delta\)FTs, and (**c**) \(\Delta\)VIS. Figure 8: _Cont._  
Figure 7: Sample image of fog detection results at 05:00 KST (South Korea Standard Time) 24 September 2019. (**a**) Fog image of GK2A_FDA, (**b**) ground-observed visibility, (**c**) fog image of CMDPS, and (**d**) fog product of GK2A RGB. Sky blue color in (**a**) indicates foggy pixels. Figure 8: Sample image of fog detection results at 08:00 KST on 25 August 2019. (**a**) Fog image of GK2A_FDA, (**b**) ground-observed visibility, (**c**) fog image of CMDPS, and (**d**) image of visible channel (0.64 \(\upmu\)m). Sky blue color in (**a**) indicates foggy pixels. Figure 9: Sample image of fog detection results at 09:00 KST on 20 October 2019. (**a**) Fog image of GK2A_FDA, (**b**) ground-observed visibility, (**c**) fog image of CMDPS, and (**d**) image of visible channel (0.64 \(\upmu\)m). Sky blue color in (**a**) indicates foggy pixels. Figure 8 shows a relatively weak and localized case of fog. The visibility meter showed that fog occurred only at the very few stations located in the central to northern parts of South Korea; however, the visibility in most inland areas in South Korea was less than 2 km. Moreover, the image of the visible channel showed a wide distribution of fog/low cloud and middle cloud over the central and northern parts of South Korea. GK2A_FDA and CMDPS were found to effectively detect the spatial pattern of the fog over the central and northern parts of South Korea. However, compared to the visibility meter (Figure 8b), both algorithms certainly over-detected the fog. This over-detection was attributed to the dissipation pattern of radiation fog after sunrise. The solar heating of the land surface can increase the land surface and surface boundary layer temperatures, thereby dissipating the lowest layer fog. Thus, the visibility is increased to the level of mist, and fog is changed into low cloud, with no changes taking place at the top of the fog. This could be a main cause of false detection of low cloud as fog during daytime. In the validation case (Figure 9), both GK2A_FDA and CMDPS effectively detected the fog similar to the training case (Figure 7). In this case, GK2A_FDA slightly over-detected the fog and CMDPS under-detected the fog compared to the visibility meter and image of the visible channel, in particular, in the south-western part of South Korea. Figure 10 shows the case of a localized fog with mid to high clouds. Fog was observed to occur in most parts of South Korea, significantly scattered with a widespread low visibility over South Korea.