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Development of atmospheric correction algorithm for Geostationary Ocean Color Imager (GOCI)
Ocean Science Journal, 2012This paper describes an atmospheric correction algorithm for Geostationary Ocean Color Imager (GOCI) and its early phase evaluation. This algorithm was implemented in GOCI Data Processing System (GDPS) version 1.1. The algorithm is based on the standard SeaWiFS method, which accounts for multiple scattering effects and partially updated in terms of ...
Jae-Hyun Ahn +2 more
exaly +2 more sources
Earth Resources and Environmental Remote Sensing/GIS Applications X, 2019 Using the world’s first ocean color sensor at a geostationary orbit (Geostationary Ocean Color Imager; GOCI), we examine the relationship between satellite-derived chlorophyll-a concentration and MH events over the East China Sea during recent summers from 2016 to 2018. MH events usually arise in July and August over the study domain.
Seonju Lee, Myung-Sook Park
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Harmful algal bloom (HAB) in the East Sea identified by the Geostationary Ocean Color Imager (GOCI)
Harmful Algae, 2014Abstract Harmful Cochlodinium polykrikoides blooms have frequently appeared and caused fatal harm to aquaculture in Korean coastal waters since 1995. We investigated the applicability of GOCI, the world's first Geostationary Ocean Color Imager, in monitoring the distribution and temporal movement of a harmful algal bloom (HAB) that was discovered in ...
Jong-Kuk Choi +2 more
exaly +2 more sources
Remote Sensing of Environment, 2016
Abstract Estimation of chlorophyll concentration in the marine biosphere has been the central topic of ocean color remote sensing since its advent. While various algorithms were proposed in the literature so far and tested for oceanic waters of diverse constituent composition, an independent algorithm evaluation is needed for local ocean waters that ...
Wonkook Kim +2 more
exaly +2 more sources
Abstract Estimation of chlorophyll concentration in the marine biosphere has been the central topic of ocean color remote sensing since its advent. While various algorithms were proposed in the literature so far and tested for oceanic waters of diverse constituent composition, an independent algorithm evaluation is needed for local ocean waters that ...
Wonkook Kim +2 more
exaly +2 more sources
IEEE Transactions on Geoscience and Remote Sensing, 2015
The radiometric calibration of satellite data is critical in many environmental studies and applications that are based on remote sensing data. The Geostationary Ocean Color Imager (GOCI) has suffered from what is called an interslot radiometric discrepancy (ISRD), which creates clear inconsistency between the adjacent slots in GOCI Level 1B (L1B ...
Wonkook Kim +2 more
exaly +2 more sources
The radiometric calibration of satellite data is critical in many environmental studies and applications that are based on remote sensing data. The Geostationary Ocean Color Imager (GOCI) has suffered from what is called an interslot radiometric discrepancy (ISRD), which creates clear inconsistency between the adjacent slots in GOCI Level 1B (L1B ...
Wonkook Kim +2 more
exaly +2 more sources
Remote Sensing of Environment, 2022 For the past three decades, polar-orbiting ocean color satellites have provided local, regional to global scale estimates of oceanic net primary production that have greatly aided studies of ocean carbon cycling, food web dynamics and climate change ...
Jinghui Wu +14 more
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Marine Disaster Detection Using the Geostationary Ocean Color Imager (GOCI)
International Journal of u- and e- Service, Science and Technology, 2016Recently, harmful algae (e.g., red tide) has damaged human and marine ecosystems. To address this, a response system should be developed to quickly cope with these ocean disasters. However, it is difficult to simultaneously monitor the vast ocean areas.
Hyun Yang +4 more
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Observations of ocean diurnal variations from the Korean geostationary ocean color imager (GOCI)
SPIE Proceedings, 2014The first geostationary ocean color satellite sensor, Geostationary Ocean Color Imager (GOCI) onboard the Korean Communication, Ocean, and Meteorological Satellite (COMS), which was launched in June of 2010 and has eight spectral bands from the blue to the near-infrared (NIR) wavelengths in 412–865 nm, can monitor and measure ocean phenomenon over a ...
Menghua Wang +3 more
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Applications of Surface Velocity Current Derived from Geostationary Ocean Color Imager (GOCI)
2018 OCEANS - MTS/IEEE Kobe Techno-Oceans (OTO), 2018We study turbulent oceanic flows in the context of ocean color. Observations of the submesoscale processes with scales of O(1km) and O(1day) has been difficult from a satellite because spatial and temporal sampling frequencies of satellite data do not typically meet the range of submesoscale oceanic processes.
Jun Myoung Choi, Wonkook Kim
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SPIE Proceedings, 2010
The first geostationary ocean color sensor, Geostationary Ocean Color Imager (GOCI), on board the Korean Communication Ocean and Meteorological Satellite (COMS), was successfully launched on June 26 of 2010. GOCI includes 8 spectral bands in visible and near-infrared wavelengths with a coverage area of 2,500×2,500 km2 centered at 36°N and 130°E over
SeungHyun Son, Menghua Wang
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The first geostationary ocean color sensor, Geostationary Ocean Color Imager (GOCI), on board the Korean Communication Ocean and Meteorological Satellite (COMS), was successfully launched on June 26 of 2010. GOCI includes 8 spectral bands in visible and near-infrared wavelengths with a coverage area of 2,500×2,500 km2 centered at 36°N and 130°E over
SeungHyun Son, Menghua Wang
openaire +1 more source