Development of ocean environmental algorithms for GOCI

Abstract

Several ocean color algorithms have been developed for GOCI (Geostationary Ocean Color Imager) using in-situ bio-optical data sets. These data sets collected around the Korean Peninsula during 1998 to 2009 include chlorophyll-a concentration (Chl-a), suspended sediment concentration (SS), absorption coeffi cient of dissolved organic matter (adom) and remote sensing refl ectance (Rrs) obtained from 1348 points. The GOCI Chl-a algorithm was developed using 4-bands remote sensing refl ectance ratio that account for the infl uence of suspended solid particle and dissolved organic matter. The GOCI Chl-a algorithm reproduced in-situ chlorophyll concentration better than the other algorithms. In the SeaWiFS images, this algorithm reduced an average error of 46 % from chlorophyll concentration retrieved by standard chlorophyll algorithms. For the GOCI SS algorithm, single band was used (Ahn et al., 2001) instead of a band ratio which is commonly usedin chlorophyll algorithms. The GOCI adom algorithm was derived from the relationship between remote sensing refl ectance band ratio (Rrs(412)/Rrs(555)) and adom. The GOCI Chl-a fl uorescence and GOCI red tide algorithms have been developed by Ahn andShanmugam(2007) and Ahn and Shanmugam(2006), respectively.If the launch of GOCI is successful, then the developed algorithms will be analyzed in the GOCI CAL/VAL processes, and improved by incorporating more data sets of the ocean optical properties data that will be obtained from waters around the Korean Peninsula.