• Title/Summary/Keyword: Ocean Color Imager

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Current Status and Results of In-orbit Function, Radiometric Calibration and INR of GOCI-II (Geostationary Ocean Color Imager 2) on Geo-KOMPSAT-2B (정지궤도 해양관측위성(GOCI-II)의 궤도 성능, 복사보정, 영상기하보정 결과 및 상태)

  • Yong, Sang-Soon;Kang, Gm-Sil;Huh, Sungsik;Cha, Sung-Yong
    • Korean Journal of Remote Sensing
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    • v.37 no.5_2
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    • pp.1235-1243
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    • 2021
  • Geostationary Ocean Color Imager 2 (GOCI-II) on Geo-KOMPSAT-2 (GK2B)satellite was developed as a mission successor of GOCI on COMS which had been operated for around 10 years since launch in 2010 to observe and monitor ocean color around Korean peninsula. GOCI-II on GK2B was successfully launched in February of 2020 to continue for detection, monitoring, quantification, and prediction of short/long term changes of coastal ocean environment for marine science research and application purpose. GOCI-II had already finished IAC and IOT including early in-orbit calibration and had been handed over to NOSC (National Ocean Satellite Center) in KHOA (Korea Hydrographic and Oceanographic Agency). Radiometric calibration was periodically conducted using on-board solar calibration system in GOCI-II. The final calibrated gain and offset were applied and validated during IOT. And three video parameter sets for one day and 12 video parameter sets for a year was selected and transferred to NOSC for normal operation. Star measurement-based INR (Image Navigation and Registration) navigation filtering and landmark measurement-based image geometric correction were applied to meet the all INR requirements. The GOCI2 INR software was validated through INR IOT. In this paper, status and results of IOT, radiometric calibration and INR of GOCI-II are analysed and described.

Introduction of GOCI-II Atmospheric Correction Algorithm and Its Initial Validations (GOCI-II 대기보정 알고리즘의 소개 및 초기단계 검증 결과)

  • Ahn, Jae-Hyun;Kim, Kwang-Seok;Lee, Eun-Kyung;Bae, Su-Jung;Lee, Kyeong-Sang;Moon, Jeong-Eon;Han, Tai-Hyun;Park, Young-Je
    • Korean Journal of Remote Sensing
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    • v.37 no.5_2
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    • pp.1259-1268
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    • 2021
  • The 2nd Geostationary Ocean Color Imager (GOCI-II) is the successor to the Geostationary Ocean Color Imager (GOCI), which employs one near-ultraviolet wavelength (380 nm) and eight visible wavelengths(412, 443, 490, 510, 555, 620, 660, 680 nm) and three near-infrared wavelengths(709, 745, 865 nm) to observe the marine environment in Northeast Asia, including the Korean Peninsula. However, the multispectral radiance image observed at satellite altitude includes both the water-leaving radiance and the atmospheric path radiance. Therefore, the atmospheric correction process to estimate the water-leaving radiance without the path radiance is essential for analyzing the ocean environment. This manuscript describes the GOCI-II standard atmospheric correction algorithm and its initial phase validation. The GOCI-II atmospheric correction method is theoretically based on the previous GOCI atmospheric correction, then partially improved for turbid water with the GOCI-II's two additional bands, i.e., 620 and 709 nm. The match-up showed an acceptable result, with the mean absolute percentage errors are fall within 5% in blue bands. It is supposed that part of the deviation over case-II waters arose from a lack of near-infrared vicarious calibration. We expect the GOCI-II atmospheric correction algorithm to be improved and updated regularly to the GOCI-II data processing system through continuous calibration and validation activities.

Prelaunch Study of Validation for the Geostationary Ocean Color Imager (GOCI) (정지궤도 해색탑재체(GOCI) 자료 검정을 위한 사전연구)

  • Ryu, Joo-Hyung;Moon, Jeong-Eon;Son, Young-Baek;Cho, Seong-Ick;Min, Jee-Eun;Yang, Chan-Su;Ahn, Yu-Hwan;Shim, Jae-Seol
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.251-262
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    • 2010
  • In order to provide quantitative control of the standard products of Geostationary Ocean Color Imager (GOCI), on-board radiometric correction, atmospheric correction, and bio-optical algorithm are obtained continuously by comprehensive and consistent calibration and validation procedures. The calibration/validation for radiometric, atmospheric, and bio-optical data of GOCI uses temperature, salinity, ocean optics, fluorescence, and turbidity data sets from buoy and platform systems, and periodic oceanic environmental data. For calibration and validation of GOCI, we compared radiometric data between in-situ measurement and HyperSAS data installed in the Ieodo ocean research station, and between HyperSAS and SeaWiFS radiance. HyperSAS data were slightly different in in-situ radiance and irradiance, but they did not have spectral shift in absorption bands. Although all radiance bands measured between HyperSAS and SeaWiFS had an average 25% error, the 11% absolute error was relatively lower when atmospheric correction bands were omitted. This error is related to the SeaWiFS standard atmospheric correction process. We have to consider and improve this error rate for calibration and validation of GOCI. A reference target site around Dokdo Island was used for studying calibration and validation of GOCI. In-situ ocean- and bio-optical data were collected during August and October, 2009. Reflectance spectra around Dokdo Island showed optical characteristic of Case-1 Water. Absorption spectra of chlorophyll, suspended matter, and dissolved organic matter also showed their spectral characteristics. MODIS Aqua-derived chlorophyll-a concentration was well correlated with in-situ fluorometer value, which installed in Dokdo buoy. As we strive to solv the problems of radiometric, atmospheric, and bio-optical correction, it is important to be able to progress and improve the future quality of calibration and validation of GOCI.

A Preliminary Performance Analysis of the Meteorological and Ocean Data Communication Subsystem in COMS (통신해양기상위성 기상해양데이터통신계의 예비 성능 해석)

  • Kim, Jung-Pyo;Yang, Gun-Ho
    • Journal of Satellite, Information and Communications
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    • v.1 no.2
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    • pp.25-31
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    • 2006
  • The COMS (Communication, Ocean, and Meteorological Satellite) performing meteorological and ocean monitoring and providing communication service with meteorological, ocean and Ka-band payload in the geostationary orbit includes MODCS (Meteorological and Ocean Data Communication Subsystem) which provides transmitting the raw data collected by meteorological payload called MI (Meteorological Imager) and ocean payload named GOCI (Geostationary Ocean Color Imager) to the ground station and relaying the meteorological data processed on the ground to the end-user stations. MODCS comprises of two channels: SD channel which formats the raw data according to CCSDS recommendation, amplifies and transmits its signal to the ground station; MPDR channel which relays to the end-user stations the ground-processed meteorological data in the data format of LRIT/HRIT recommended by CGMS. This paper constructs the architecture of MODCS for transmitting and relating the observed data, and investigates that the key performance parameters have the required margin through the preliminary performance analyses.

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LRIT DESIGN OF COMS

  • KOO In-Hoi;PARK Durk-Jong;SEO Seok-Bae;AHN Sang-Il;KIM Eun-Kyou
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.305-308
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    • 2005
  • The COMS, Korea's first geostationary multipurpose satellite program will accommodate 3 kind of payloads; Ka-Band communication transponder, GOCI (Geostationary Ocean Color Imager), and MI (Meteorological Imager). MI raw data will be transferred to ground station via L-band link. The ground station will perform image data processing for raw data, generate them into the LRIT/HRIT format, the user dissemination data recommended by the CGMS. The LRIT/HRIT are disseminated via satellite to user stations. This paper shows the COMS LRIT data generation procedure based on COMS LRIT specification and its verification results using the LRIT user station.

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High Resolution Ocean Color Products Estimation in Fjord of Svalbard, Arctic Sea using Landsat-8 OLI (Landsat-8 OLI를 이용한 북극해 스발바드 피요르드의 고해상도 Ocean Color Product 산출)

  • Kim, Sang-Il;Kim, Hyun-Cheol;Hyun, Chang-Uk
    • Korean Journal of Remote Sensing
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    • v.30 no.6
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    • pp.809-816
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    • 2014
  • Ocean Color products have been used to understand marine ecosystem. In high latitude region, ice melting optically influences the ocean color products. In this study, we assessed optical properties in fjord around Svalbard Arctic sea, and estimated distribution of chlorophyll-a and suspended sediment by using high resolution satellite data, Landsat-8 Operational Land Imager (OLI). To estimate chlorophyll-a and suspended sediment concentrations, various regression models were tested with different band ratio. The regression models were not shown high correlation because of temporal difference between satellite data and in-situ data. However, model-derived distribution of ocean color products from OLI showed a possibility that fjord and coastal areas around Arctic Sea can be monitored with high resolution satellite data. To understand climate change pattern around Arctic Sea, we need to understand ice meting influences on marine ecosystem change. Results of this study will be used to high resolution monitoring of ice melting and its influences on the marine ecosystem change at high latitude. KOPRI (Korea Polar Research Institute) has been operated the Dasan station on Svalbard since 2002, and study was conducted using Arctic station.

ERROR PROPAGATION ANALYSIS FOR IN-ORBIT GOCI RADIOMETRIC CALIBRATION

  • Kang, Gm-Sil;Youn, Heong-Sik
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.92-95
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    • 2008
  • The Geostationary Ocean Color Imager (GOCI) is under development to provide a monitoring of ocean-color around the Korean Peninsula from geostationary platforms. It is planned to be loaded on Communication, Ocean, and Meteorological Satellite (COMS) of Korea. The GOCI has been designed to provide multi-spectral data to detect, monitor, quantify, and predict short term changes of coastal ocean environment for marine science research and application purpose. The target area of GOCI observation covers sea area around the Korean Peninsula. Based on the nonlinear radiometric model, the GOCI calibration method has been derived. The radiometric model of GOCI has been validated through radiometric ground test. From this ground test result, GOCI radiometric model has been changed from second order to third order. In this paper, the radiometric test performed to evaluate the radiometric nonlinearity is described and the GOCI radiometric error propagation is analyzed. The GOCI radiometric calibration is based on onboard calibration devices; solar diffuser, DAMD (Diffuser Aging Monitoring Device). The radiometric model error due to the dark current nonlinearity is considered as a systematic error. Also the offset correction error due to gain/offset instability is considered. The radiometric accuracy depends mainly on the ground characterization accuracies of solar diffuser and DAMD.

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Vignetting Analysis of GOCI Optical System

  • Yeon, Jeoung-Heum;Youn, Heong-Sik
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.195-198
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    • 2007
  • GOCI(Geostationary Ocean Color Imager) is the core paryload of the geostationary satellite COMS(Communication, Ocean and Meteological Satellite) for ocean monitoring. It is scheduled to be launched at the end of 2008. GOCI observes ocean color around the Korean Peninsula over $2500km{\times}2500km$ area. Whole field of view is divided into 16 solts and scan mechanism enables to point each slot position. Tilted two-axis scan method is used to observe entire field of view with great pointing stability. Vignetting of the optical system appears when the partial obscuration by intermediate optical components occurs. It leads to the variation of the illumination in the image and gradual fading near the edge of the field. It should be prohibited for the stable radiometric performances. In this work, vignetting analysis of GOCI optical system is performed. For the systematic approach, GOCI optical system is divided into scan mechanism part and telescope part. Vignetting analysis of each part is performed and each result is combined for the overall vignetting performances. The analyzed results can be applied to the selection of slot acquisition angle of scan mechanism to minimize vignetting effects.

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Noise PDF Analysis of Nonlinear Image Sensor Model;GOCI Case

  • Myung, Hwan-Chun;Youn, Heong-Sik
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.191-194
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    • 2007
  • The paper clarifies all the noise sources of a CMOS image sensor, with which the GOCI (Geostationary Ocean Color Imager) is equipped, and analyzes their contribution to a nonlinear image sensor model. In particular, the noise PDF (Probability Density Function) is derived in terms of sensor-gain coefficients: a linear and a nonlinear gains. As a result, the relation between the noise characteristic and the sensor gains is studied.

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Development of the Bio-Optical Algorithms to Retrieve the Ocean Environmental Parameters from GOCI

  • Ryu, Joo-Hyung;Moon, Jeong-Eon;P., Shanmugam;Min, Jee-Eun;Ahn, Yu-Hwan
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.82-85
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    • 2006
  • The Geostationary Ocean Color Imager (GOCI) will be loaded in Communication, Ocean and Meteorological Satellite (COMS). To efficiently apply the GOCI data in the variety of fields, it is essential to develop the standard algorithm for estimating the concentration of ocean environmental components (, , and ). For developing the empirical algorithm, about 300 water samples and in situ measurements were collected from sea water around the Korean peninsula from 1998 to 2006. Two kinds of chlorophyll algorithms are developed by using statistical regression and fluorescence technique considering the bio-optical properties in Case-II waters. The single band algorithm for is derived by relationship between Rrs (555) and in situ concentration. The CDOM is estimated by absorption coefficient and ratio of Rrs(412)/Rrs(555). These standard algorithms will be programmed as a module of GOCI Data Processing System (GDPS) until 2008.

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