Young-Je Park

TL;DR: The GOCI Data Processing System (GDPS) as mentioned in this paper was developed for real-time generation of various products, such as images, data, and data analysis algorithms, which can be improved through continuous Cal/Val.

TL;DR: In this paper, an atmospheric correction algorithm for Geostationary Ocean Color Imager (GOCI) and its early phase evaluation is described, which is based on the standard SeaWiFS method, which accounts for multiple scattering effects and partially updated in terms of turbid case-2 water correction, optimized aerosol models and solar angle correction per slot.

TL;DR: GOCI-derived ocean color data can provide an effective tool to monitor ocean phenomenon in the region such as tide-induced re-suspension of sediments, diurnal variation of ocean optical and biogeochemical properties, and horizontal advection of river discharge.

TL;DR: In this article, the authors compared the potential of the MODIS, the Medium Resolution Imaging Spectrometer (MERIS), and the Geostationary Ocean Color Imager (GOCI) in retrieving the particulate backscattering coefficient, robust proxy of the concentration of suspended particulate matter (SPM), in the turbid waters of the East China Sea, then combined ocean color satellite data to field data recorded by an autonomous bio-optical profiling float to reconstitute and explain the dynamics of SPM within the whole water column in the middle of the

TL;DR: In this article, the applicability of the Geostationary Ocean Color Imager (GOCI) for estimating hourly variations in ocean surface currents, which provide significant information on seawater circulation for fisheries, shipping controls, and more.