Poster + Paper
17 October 2023 Utilization of blended chlorophyll-a based on geostationary and near-polar orbiting ocean color satellite data: a case study of red tide occurred in the East Sea in 2013
Hye-Kyeong Shin, Jae-yeop Kwon, Tae-ho Kim
Author Affiliations +
Conference Poster
Abstract
Chlorophyll-a is an Essential Climate Variables in the global climate observation system, and thus it’s necessary to have long-term time series data without any gaps. Composite images are commonly produced by merging ocean-color satellite images from near-polar orbiting satellites or compositing over periods of more than 8 days. In this study, we generated chlorophyll-a daily composite data using a production method based on remote sensing reflectance of a multi-near-polar orbiting ocean color satellite, a technique provided by the European Space Agency Climate Change Initiative. In contrast to the European Space Agency Climate Change Initiative products based on multi-near-polar orbiting ocean color satellite sensors such as VIIRS, MODIS and OLCI, we used the GOCI (500 m resolution) and GOCI-II (250 m resolution) sensors on a geostationary satellite. These sensors can monitor around the Korean Peninsula eight to ten times per day. We merged remote sensing reflectance of five sensors at 443, 490, 510, and 555 nm between 01 and 05 UTC and applied the OC4 (Four-band Ocean Color) algorithm. Using this method, we compared the results of detecting a red tide event on the west coast of the East Sea in August 2013 using a single GOCI data and the OC-CCI data (4 km resolution).
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Hye-Kyeong Shin, Jae-yeop Kwon, and Tae-ho Kim "Utilization of blended chlorophyll-a based on geostationary and near-polar orbiting ocean color satellite data: a case study of red tide occurred in the East Sea in 2013", Proc. SPIE 12728, Remote Sensing of the Ocean, Sea Ice, Coastal Waters, and Large Water Regions 2023, 127280L (17 October 2023); https://doi.org/10.1117/12.2680234
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KEYWORDS
Sensors

Satellites

Reflectivity

Remote sensing

MODIS

Satellite imaging

Bias correction

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