Retrieval of suspended sediment concentration in the coastal waters of yellow Sea from Geostationary Ocean Color Imager (GOCI)

Abstract

In this study we developed two different types of SSC algorithms, one is the empirical algorithm and the other one is the semi-analytical model based algorithm. For the algorithm development, 197 in situ measurements for chlorophyll, SS concentration, surface remote sensing reflectance (Rrs) and IOPs were obtained on the coastal waters of Yellow Sea from 2011 to 2012. To validate SSC algorithms, we used Geostationary Ocean Color Imager (GOCI) which was captured around the time of field sampling. GOCI, the world’s first geostationary ocean color observation satellite, can obtain data at every hour during the daytime. Owing to this advantage of GOCI, we took much more matching data than polar orbit sensors such as SeaWiFS and MODIS. Atmospheric correction of GOCI was carried out using MUMM method. To verify the accuracy for the newly developed SSC algorithms in this study, we also examined existing GOCI standard SS algorithm, YOC algorithm and single-band exponential format algorithm for comparison. The results from new SSC algorithm based on the semi-analytical model showed good correlation with the in situ SSC. But in the area of extremely high SSC (> 100 g/m3) GOCI-derived SSC was underestimated. In the future we will continuously enhance the semi-analytical model based SSC algorithm using much more GOCI-matching dataset.centration, surface remote sensing reflectance (Rrs) and IOPs were obtained on the coastal waters of Yellow Sea from 2011 to 2012. To validate SSC algorithms, we used Geostationary Ocean Color Imager (GOCI) which was captured around the time of field sampling. GOCI, the world’s first geostationary ocean color observation satellite, can obtain data at every hour during the daytime. Owing to this advantage of GOCI, we took much more matching data than polar orbit sensors such as SeaWiFS and MODIS. Atmospheric correction of GOCI was carried out using MUMM method. To verify the accuracy for the newly developed SSC algorithms in this study, we also examined existing GOCI standard SS algorithm, YOC algorithm and single-band exponential format algorithm for comparison. The results from new SSC algorithm based on the semi-analytical model showed good correlation with the in situ SSC. But in the area of extremely high SSC (> 100 g/m3) GOCI-derived SSC was underestimated. In the future we will continuously enhance the semi-analytical model based SSC algorithm using much more GOCI-matching dataset.