TJ8.5
Inter-Sensor Comparison of Satellite Ocean Color Products from GOCI and MODIS

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Monday, 7 January 2013: 5:00 PM
Inter-Sensor Comparison of Satellite Ocean Color Products from GOCI and MODIS
Room 18B (Austin Convention Center)
Ruhul Amin, NRL, Stennis Space Center, MS; and R. Gould, S. Ladner, I. Shulman, J. Jolliff, P. Sakalaukus, A. Lawson, P. Martinolich, and R. Arnone
Manuscript (1016.7 kB)

Poster PDF (5.1 MB)

The Geostationary Ocean Color Imager (GOCI) was launched by the Republic of Korea on 27 June 2010 and is the first geostationary ocean color sensor in orbit that provides coastal bio-optical properties (such as chlorophyll concentration, absorption and backscattering coefficients) at unprecedented high spatial and temporal resolution. GOCI has 8 spectral bands covering 2,500 km × 2,500 km (centered 130E, 36N) at 500 m spatial resolution. Unlike polar-orbiting satellites which provide only one or two images of the same geographic area per day, GOCI collects images every hour from 10am to 5pm (eight images per day). This high temporal resolution can lead to improved understanding of short time scale bio-optical variability in the ocean surface. However, retrieving ocean color products accurately can be challenging particularly in turbid coastal waters due to imperfect atmospheric correction. In this study, we process GOCI data through US Naval Research Lab's Automated Processing System (APS) and the standard GOCI Data Processing System (GDPS) distributed by the Korea Ocean Satellite Center (KOSC), and compare the retrieved ocean color products from the two processing systems. We use corresponding Moderate Resolution Imaging Spectroradiometer (MODIS) and Medium Resolution Imaging Spectrometer (MERIS) images as the ground truth to assess the performance of the two processing systems. Since all three sensors can retrieve Fluorescence Line Height (FLH) which is less sensitive to atmospheric correction and colored dissolved organic matter (CDOM), we also compare the FLH products from these sensors, in addition to other ocean color products. Furthermore, we demonstrate the use of hourly GOCI images to detect and track features such as sediment plumes in the ocean surface.