# Data-Free Area Detection and Evaluation for Marine Satellite Data Products
## 4 Discussion
### Analyses of the GOCI, MODIS and OLCI Ocean Color Product Differences  
#### 4.2.1 Cloud Detection Algorithm Variance Analysis  
Figures 9-13 show that GOCI and MODIS have striking similarities with respect to total missing rate, abnormal missing rate and the distribution of marine coverage objects. The number is much larger compared to OLCI. To further explain the obtained result, we correlated the differences in cloud detection algorithms for the data. In the processing of ocean water color remote sensing, cloud masking usually considers the threshold method of Rayleigh scattering corrected reflectance (\(\rho_{rc}\)) in the near-infrared band. The atmospheric correction scheme of using the Level 1 data of GOCI to generate the corresponding Level 2 data is the standard KOSC algorithm [70]. The algorithm is based on the SeaWiFS algorithm [71], and the threshold of \(\rho_{rc}(865\ \mathrm{nm})\geq 0.028\) is used to automatically mask cloud pixels in the standard atmospheric correction of the sensor. Moreover, the atmospheric correction scheme used by MODIS is the OCSSW algorithm in the NASA Earth Observation System SeaDAS software (i.e., it can automatically mask cloud pixels during atmospheric correction), with a threshold method of \(\rho_{rc}(869\ \mathrm{nm})\)\(\geq 0.027\)[2]. However, the methods only perform sufficiently at spatial locations in the open ocean, as some normal pixels are treated as masked clouds under complex ocean conditions. For example, high-sediment turbidity waters are prone to green tide algal hazards in summer, etc. [72]. The difference is that the atmospheric correction scheme used in OLCI is the Sen2 Cor algorithm in the SNAP software, which simultaneously identifies and classifies  
Figure 18: Schematic diagram of sea ice in the data-free areas: (**a**,**d**,**g**) the true color images at the spatial locations of the sea ice 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. clouds, cirrus, snow and water in the atmospheric correction step. The cloud mask effect in OLCI is much better than those in GOCI and MODIS, suggesting that the obtained ocean color products are also better with respect to information completeness and continuity quality. In contrast to GOCI and MODIS, the difference in the cloud detection selection bands is only 4 nm. It can be negligible and can be regarded as the same band signal, and the difference in the judgment thresholds is only 0.001. This contrast can help to explain the extremely high similarity between the spatial and temporal distribution characteristics of the data-free areas in GOCI and MODIS. Consequently, we selected the data-free area near the green tide algae mentioned above (Figure 15) and the surrounding pixels with retained information as the study area. Then, the different statuses of the spectral information within and around the data-free area were further explored. On the basis of the identification classification results, 80 sample points were evenly selected at the spatial location of green tide algae in the data-free area, the clean water location and the clean water location of the surrounding product data with retained information. A concomitant phenomenon of green tide algae is missing in the OLCI product. The green tide algae in the data-free areas are not adjacent to clean water. We selected the pixel of the retained reflectance of green tide algae in OLCI that is immediately adjacent to the data-free areas as the clean water in the data-free areas and then compared this with those in GOCI and MODIS. The reflectance values at the near-infrared band (GOCI: 865 nm, MODIS: 869.5 nm and OLCI: 865.3 nm) at the sample-point location of Level 1 data were obtained and then plotted as a box line graph. As shown in Figure 19, the reflectance identified as pixels of the green tide algae in the data-free areas of the three data is generally high and fluctuating.