# Data-Free Area Detection and Evaluation for Marine Satellite Data Products
## 4 Discussion
### Spatial and Temporal Distribution of Marine Coverage Objects Contained in Data-Free Areas
Figure 15: Schematic diagram of green tide algae in the data-free areas: (**a**,**d**,**g**) the true color images at the spatial locations of the green tide algae for GOCI, MODIS and OLCI data, respectively; (**b**,**e**,**h**) the condition of the data-free area; (**c**,**f**,**i**) the identifi-cation status of the marine objects in the data-free area. Thus, in this study, we opted to initially crop sea ice and some surrounding areas prior to analyzing them separately. Then, overall statistics and analyses were employed. The data-free areas of GOCI and MODIS show sea ice similar to the shape of clouds, resulting in missing information and clumps aggregated without dispersion. These areas are located in the sea of Liaodong Bay, where the near-shore ecological environment is complex and where people usually gather. The pixels at the sea ice edge mainly correspond to turbid waters (eutrophic and high phytoplankton biology; Figure 18c,f). The thin ice areas of sea ice in OLCI generally do not cause missing information, but most thick ice areas are missing. As a result, the missing pixels have a fragmented distribution. As opposed to the products of OLCI, the products of GOCI and MODIS do not usually appear separately for the different types of ocean coverage objects in the data-free area. For example, as shown in Figures 14-17, clouds, green tide algae or turbid waters are usually accompanied by abundant clean water. Similarly, as shown in Figure 18, sea ice is surrounded by turbid water because this sea ice is located in Liaodong Bay, a region of the Bohai Sea that is heavily eutrophic all year round. The phenomenon of accompanying ocean cover objects in the data-free area is obvious. It can explain to a certain extent the over-representation of clean water in the data-free area. Figure 16: Schematic diagram of the missing OLCI data in the Yangtze River Delta region (Red for clouds, yellow for turbid water). The above discussion can also tentatively explain the phenomenon depicted in Figure 10. The missing amount of clean water in the data-free areas of GOCI and MODIS has a positive relationship with the missing amount of clouds, whereas the missing amount of turbid water has a significant inverse relationship. On the one hand, clean water, as a normal image element, should not appear to be masked. However, the concomitant effects of ocean cover objects in the data-free area and the concomitant occurrence of clouds and clean water bodies cause a phenomenon of increasing and decreasing. On the other hand, the information of turbid water pertaining to anomalous image pixels with high reflectivity may be masked as clouds [2]. However, clouds float over the ocean, and ocean color satellites can hardly penetrate clouds and fog. Clouds are given priority over turbid seawater during identification classification. Therefore, when clouds are in the same spatial position as seawater, they are identified as clouds. Clouds obscure turbid seawater when they are excessively large, thus causing a decrease in the sufficient identification of turbid water and vice versa. As a result, the missing amount of turbid water shows a significant inverse increase and decrease with the missing amount of clouds. Figure 17: Schematic diagram of turbid water in the data-free areas: (**a,d,g**) the true color images at the spatial locations of the turbid water for GOCI, MODIS and OLCI data, respectively; (**b,e,h**) the condition of the data-free area; (**c,f,i**) the identifi-cation status of the marine objects in the data-free area. The red boxes in (**a,d,g**) represent the main turbid water areas.