Estimation of ocean environmental information from the Geostationary Ocean Color Imager (GOCI) series

Abstract

The ocean color provides environmental information from underwater colored constituents such as phytoplankton, inorganic suspended particles, detritus, and dissolved organic matter. Remotely sensing the ocean color using visible (VIS) to near-infrared (NIR) wavelengths at a satellite level has successfully extracted oceanic environmental information on a large spatial and temporal scale. The first Geostationary Ocean Color Imager (GOCI) has offered the regional synoptic view of coastal and open ocean phenomena in the Northeast Asia Seas, making history as the first space-borne ocean color sensor to take daytime images with unprecedented temporal resolution [1,2]. On the successful operation of GOCI, the second GOCI (GOCI-II) has operated since 2020 with enhanced spatial and spectral resolution [3]. In this work, we first introduce the GOCI series’ primary ocean-color products, algorithms, and their Cal/Val activities [4-6]. Lastly, drawing from the experiences and lessons learned from GOCI and GOCI-II, we propose an improved design for a nextgeneration geostationary ocean color mission [7]