• Journal of Korean Society for Atmospheric Environment
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• v.29 no.2
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• pp.199-210
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• 2013

Detailed 3 dimensional structure of Asian dust plume has been analyzed from the retrieved aerosol data from two different satellites which are the Korea's $1^{st}$ geostationary satellite, namely the Communication, Ocean, Meteorological Satellite (COMS) spacecraft launched in 2010, and the NASA's Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). COMS spacecraft provides the first time resolved aerial aerosol maps by the systematically well-calibrated multispectral measurements from the Geostationary Ocean Color Imager (GOCI) instrument. GOCI data are used here to evaluate intensity, spatial distribution, and long-range transport of Asian dust plume during 1~2 May 2011. We found that the strong Asian dust plume showing AOT of 2~5 was lofted to the altitude around 2~4 km above the Earth's surface and transported over Yellow Sea with a speed of about 25 km/hr. The CALIPSO extinction coefficient and particulate depolarization ratio (PDR) profiles confirmed that nonspherical dust particles were enriched in the dust plume. This study is a first example of quantitative integration of GOCI and CALIOP measurements for clarifying the overall structure of an Asian dust event.

• Journal of the Korean Association of Geographic Information Studies
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• v.16 no.1
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• pp.36-46
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• 2013

The Geostationary Ocean Color Imager (GOCI), the first geostationary ocean color observation instrument launched in 2010 on board the Communication, Ocean, and Meteorological Satellite (COMS), has been generating the operational level 1 data. This study describes a methodology for creating the GOCI true color image and data processing software, namely the GOCI RGB maker. The algorithm uses a generic atmospheric correction and reprojection technique to produce the color composite image. Especially, the program is designed for educational purpose in a way that the region of interest and image size can be determined by the user. By distributing software to public, it would maximize the understanding and utilizing the GOCI data. Moreover, images produced from the geostationary observations are expected to be an excellent tool for monitoring environmental changes.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.307-312
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• 1998

The paper first describes the atmospheric correction algorithm for the Ocean Color and Temperature Scanner (OCTS) visible band data used at Earth Observation Center (EOC) of National Space Development Agency of Japan (NASDA). It uses 10 candidate aerosol models including "Asian dust model" introduced in consideration of the unique feature of aerosols over the east Asian waters. Based on the observations at 670 and 865 nm bands where the reflectance of the water body can be discarded, the algorithm selects a pair of aerosol models that accounts best for the observed spectral reflectances to synthesize the aerosol reflectance in other bands. The paper also evaluates the performance of the algorithm by comparing the satellite estimates of water-leaving radiance and chlorophyll-a concentration with selected buoy-and ship-measured data. In comparison with the old CZCS-type atmospheric correction algorithm where the aerosol reflectance is as-sumed to be spectrally independent, the OCTS algorithm records factor 2-3 less error in estimating the normalized water-leaving radiances. In terms of chlorophyll-a concentration estimation, however, the accuracy stays vey similar compared to that of the CZCS-type algorithm. This is considered to be due to the nature of in-water algorithm which relies on spectral ratio of water-leaving radiances.

• Korean Journal of Remote Sensing
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• v.14 no.3
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• pp.262-276
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• 1998

The paper first describes the atmospheric correction algorithm for the Ocean Color and Temperature Scanner (OCTS) visible band data used at Earth Observation Center (EOC) of National Space Development Agenrr of japan (NASDA). It uses 10 candidate aerosol models including "Asian dust model" introduced in consideration of the unique feature of aerosols over the east Asian waters. Based on the observations at 670 and 865 nm bands where the reflectance of the water body can be discarded, the algorithm selects a pair of aerosol models that accounts best for the observed spectral reflectances to synthesize the aerosol reflectance in other bands. The paper also evaluates the performance of the algorithm by comparing the satellite estimates of water-leaving radiance and chlorophyll-a concentration with selected buoy- and ship-measured data. In comparison with the old CZCS-type atmospheric correction algorithm where the aerosol reflectance is assumed to be spectrally independent, the OCTS algorithm records factor 2-3 less error in estimating the normalized water-leaving radiances. In terms of chlorophyll-a concentration estimation, however, the accuracy stays very similar compared to that of the CZCS-type algorithm. This is considered to be due to the nature of in-water algorithm which relies on spectral ratio of water-leaving radiances.

• Korean Journal of Remote Sensing
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• v.30 no.4
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• pp.455-464
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• 2014

After launching the Geostationary Ocean Color Imager (GOCI) on June 2010, field campaigns were performed routinely around Korean peninsula to collect in-situ data for calibration and validation. Key measurements in the campaigns are radiometric ones with field radiometers such as Analytical Spectral Devices FieldSpec3 or TriOS RAMSES. The field radiometers must be regularly calibrated. We, in the paper, introduce the optical laboratory built in KOSC and the relative calibration method for in-situ measurement spectroradiometer. The laboratory is equipped with a 20-inch integrating sphere (USS-2000S, LabSphere) in 98% uniformity, a reference spectrometer (MCPD9800, Photal) covering wavelengths from 360 nm to 1100 nm with 1.6 nm spectral resolution, and an optical table ($3600{\times}1500{\times}800mm^3$) having a flatness of ${\pm}0.1mm$. Under constant temperature and humidity maintainance in the room, the reference spectrometer and the in-situ measurement instrument are checked with the same light source in the same distance. From the test of FieldSpec3, we figured out a slight difference among in-situ instruments in blue band range, and also confirmed the sensor spectral performance was changed about 4.41% during 1 year. These results show that the regular calibrations are needed to maintain the field measurement accuracy and thus GOCI data reliability.

• Korean Journal of Remote Sensing
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• v.24 no.6
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• pp.559-569
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• 2008

The Geostationary Ocean Color Imager (GOCI) on board the Communication Ocean Meteorological Satellite (COMS), the first geostationary ocean color sensor, requires accurate atmospheric correction since its eight bands are also affected by atmospheric constituents such as gases, molecules and atmospheric aerosols. Unlike gases and molecules in the atmosphere, aerosols can interact with sunlight by complex scattering and absorption properties. For the purpose of qualified ocean remote sensing, understanding of aerosol-radiation interactions is needed. In this study, we show micro-physical and optical properties of aerosols using the Optical Property of Aerosol and Cloud (OPAC) aerosol models. Aerosol optical properties, then, were used to analysis the relationship between theoretical satellite measured radiation from radiative transfer calculations and aerosol optical thickness (AOT) under various environments (aerosol type and loadings). It is found that the choice of aerosol type makes little different in AOT retrieval for AOT<0.2. Otherwise AOT differences between true and retrieved increase as AOT increases. Furthermore, the differences between the AOT and angstrom exponent from standard algorithms and this study, and the comparison with ground based sunphotometer observations are investigated. Over the northeast Asian region, these comparisons suggest that spatially averaged mean AOT retrieved from this study is much better than from standard ocean color algorithm. Finally, these results will be useful for aerosol retrieval or atmospheric correction of COMS/GOCI data processing.

• Korean Journal of Remote Sensing
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• v.39 no.6_2
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• pp.1523-1528
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• 2023

Since the successful launch of Geostationary Ocean Color Imager-II (GOCI-II) in February 2020, various studies for improving the accuracies of the product have been underway through full-scale Cal/Val (calibration and validation) activities. This special issue examines the algorithm for GOCI-II data quality management at present, two years after the start of studies on Cal/Val and algorithm improvement of GOCI-II data, and introduces accuracy improvement and application progress along with the related research results. We expect that highly accurate data will be provided and utilized through continuous Cal/Val activities for GOCI-II data.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.100-103
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• 2008

COMS(Communication, Ocean and Meteorological Satellite) has multiple payloads; Meteorological Image(MI), Ocean Color Imager(GOCI) and Ka-band communication payloads. MI has 4 IR and 1 visible channel. In order to improve the quality of IR image, two calibration sources are used; black body image and cold space look data. In case of COMS, the space look is performed at 10.4 degree away from the nadir in east/west direction. During space look, SUN or moon intrusions are strictly forbidden, because it would degrade the quality of collected IR channel calibration data. Therefore we shall pay attention to select space look side depending on SUN and moon location. This paper proposes and discusses a simple and complete space look side selection logic based on SUN and moon intrusion event file. Computer simulation has been performed to analyze the performance of the proposed algorithm in term of east/west angular distance between space look position and hazardous intrusion sources; SUN and moon.

• Proceedings of the KSRS Conference
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• 1999.11a
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• pp.390-395
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• 1999

Ocean Scanning Multispectral Imager (OSMI) is a payload on the Korean Multi-purpose SATellite (KOMPSAT) to perform worldwide ocean color monitoring for the study of biological oceanography KOMPSAT will be launched in the middle of November this year. The radiometric performance of OSMI is analyzed for various gain settings in the viewpoint of the instrument developer for OSMI calibration and application based on its ground performance measurement data for 8 primary spectral bands of OSMI. The radiometric response linearity and dynamic range are analyzed for the image radiometric calibration and the estimation of OSMI image quality for the ocean remote sensing area. The dynamic range is compared with the nominal input radiance for the ocean and the land. The noise equivalent radiance (NER) corresponding to the instrument radiometric noise is compared with the radiometric resolution of signal digitization (1-count equivalent radiance). The best gain setting of OSMI for ocean monitoring is recommended. This analysis is considered to be useful for the OSMI mission and operation planning, the OSMI image data calibration, and users' understanding about OSMI image quality.

• Korean Journal of Remote Sensing
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• v.16 no.2
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• pp.135-143
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• 2000

Ocean Scanning Multispectral Imager (OSMI) is a payload on the Korean Multi-Purpose SATellite (KOMPSAT) to perform global ocean color monitoring for the study of biological oceanography. HOMPSAT was launched 21 December 1999. The radiometric performance of OSMI is analyzed for various gain settings in the viewpoint of the instrument developer for OSMI calibration and application based on its ground performance data measured before launch. The radiometric response linearity and dynamic range are analyzed and the dynamic range is compared with the nominal input radiance for the ocean and the land. The noise equivalent radiance (NER) corresponding to the instrument radiometric noise is compared with the radiometric resolution of signal digitization (1-count equivalent radiance). The best gain setting of OSMI for ocean monitoring is recommended. This analysis is considered to be useful for the OSMI mission and operation planning, the OSMI image data calibration, and users' understanding about OSMI image quality.