A record-breaking agglomeration of Sargassum was packed along the northern Jeju coast in Korea in 2021, and laborers suffered from removing them from the beach. If remote sensing can be used to detect the locations at which Sargassum accumulated in a timely and accurate manner, we could remove them before their arrival and reduce the damage caused by Sargassum. This study aims to detect Sargassum distribution on the coast of Jeju Island using the Geostationary KOMPSAT 2B (GK2B) Geostationary Ocean Color Imager-II (GOCI-II) imagery that was launched in February 2020, with measurements available since October 2020. For this, we used GOCI-II imagery during the first 6 months and machine learning models including Fine Tree, a Fine Gaussian support vector machine (SVM), and Gentle adaptive boosting (GentleBoost). We trained the models with the GOCI-II Rayleigh-corrected reflectance (RhoC) image and a ground truth map extracted from high-resolution images as input and output, respectively. Qualitative and quantitative assessments were carried out using the three machine learning models and traditional methods such as Sargassum indexes. We found that GentleBoost showed a lower false positive (6.2%) and a high F-measure level (0.82), and a more appropriate Sargassum distribution compared to other methods. The application of the machine learning model to GOCI-II images in various atmospheric conditions is therefore considered successful for mapping Sargassum extent quickly, enabling reduction of laborers’ efforts to remove them.

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An instrumented ferry made two transects per day across two current systems which are the North Korean Cold Current and the East Korean Warm Current over the years 2012-2013 from Gangneung to Ulleungdo in the southwestern East Sea. Seawater properties of these transects were measured with high spatial and temporal resolution for an extended period of time. Here the salinity records from the transects with the oceanographic observation data from East Sea Fisheries Institute of NFRDI, AVISO daily current chart and GOCI Chlorophylla image in 2012 and 2013 are used to study the time-series variation of salinity at the surface. The high salinity section with the range of 33.15~34.12 occurred on the transect mainly in the middle of eddy, and western boundary of strong northward current from June to October. We can found low salinity waters in both sides of the high salinity section. It is estimated that the western low salinity waters with the range of 30.58~33.20 accompanied by southward current were derived from the NKCC and the eastern waters with the range of 31.30~33.24 accompanied by northward current were derived from the Tsushima Surface Water. The lowest salinity of NKCC is confirmed in this study as 30.36. It is found that the western waters below 33.00 extended extremely toward the east about 110 km area from Gangneung and toward the south around Jukbyon coastal area as a 5~10 m layer. We can find its volume of low saline waters transport is not neglectable compared with that of Tsushima Current region in the western part of the East Sea. In this study we named it as the North Korean Low Saline Surface Water in summer.

In this study, we investigated the seasonal variation of SST(Sea Surface Temperature)