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13 October 2008 Red tide detection simulation for integrated ray tracing model in-orbit performance verification with GOCI
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Abstract
The Geostationary Ocean Colour Instrument (GOCI) is a satellite ocean colour instrument on board the Communication-Ocean-Meteorology Satellite (COMS) scheduled to be launched into a geostationary orbit sometime after late 2009. GOCI primary science objectives are i) to monitor the marine environments around Korean peninsula, ii) to produce the fishery information such as chlorophyll concentration and iii) to monitor the long-term and short-term changes in marine ecosystem. We report a new end-to-end optical model for GOCI in-orbit radiometric and imaging performance verification. The model includes the source (i.e. the sun), target (i.e. a 2500 km x 2500 km region of the Earth's surface) and the payload (i.e. GOCI optical system) incorporated in the single optical ray tracing environment. It was then applied for the measurement simulation for red tide infection commonly observed in the Korean coastal water environment. The simulation results show that the estimated water leaving radiance (WLR) of 14 red tide-infected case-I water target scenes exhibits a close proximity to those obtained from the COART model, and satisfies the red tide detection criteria reported elsewhere. The simulated WLR results were also used to check the validity of 14 chlorophyll algorithms commonly used in the ocean science field. This demonstrates the practical usefulness of the model, as an important mission-support and analysis tool. It is also envisaged that the model deployment can bring a significant improvement, in the process throughput, to the GOCI pre-flight and in-flight performance verification phases. The model concept, simulation results and implications are described in detail.
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Sun Jeong Ham, Sug-Whan Kim, Hyung Sik Yun, and Sun Hee Yoo "Red tide detection simulation for integrated ray tracing model in-orbit performance verification with GOCI", Proc. SPIE 7105, Remote Sensing of the Ocean, Sea Ice, and Large Water Regions 2008, 710506 (13 October 2008); https://doi.org/10.1117/12.800158
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