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Development of Ocean Environmental Algorithms for Geostationary Ocean Color Imager (GOCI) (정지궤도 해색탑재체(GOCI) 해수환경분석 알고리즘 개발)

  • Moon, Jeong-Eon;Ahn, Yu-Hwan;Ryu, Joo-Hyung;Shanmugam, Palanisamy
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.189-207
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    • 2010
  • Several ocean color algorithms have been developed for GOCI (Geostationary Ocean Color Imager) using in-situ bio-optical data sets. These data sets collected around the Korean Peninsula between 1998 and 2009 include chlorophyll-a concentration (Chl-a), suspended sediment concentration (SS), absorption coefficient of dissolved organic matter ($a_{dom}$), and remote sensing reflectance ($R_{rs}$) obtained from 1348 points. The GOCI Chl-a algorithm was developed using a 4-band remote sensing reflectance ratio that account for the influence of suspended sediment and dissolved organic matter. The GOCI Chl-a algorithm reproduced in-situ chlorophyll concentration better than the other algorithms. In the SeaWiFS images, this algorithm reduced an average error of 46 % in chlorophyll concentration retrieved by standard chlorophyll algorithms of SeaWiFS. For the GOCI SS algorithm, a single band was used (Ahn et al., 2001) instead of a band ratio that is commonly used in chlorophyll algorithms. The GOCI $a_{dom}$ algorithm was derived from the relationship between remote sensing reflectance band ratio ($R_{rs}(412)/R_{rs}(555)$) and $a_{dom}(\lambda)$). The GOCI Chl-a fluorescence and GOCI red tide algorithms were developed by Ahn and Shanmugam (2007) and Ahn and Shanmugam (2006), respectively. If the launch of GOCI in June 2010 is successful, then the developed algorithms will be analyzed in the GOCI CAL/VAL processes, and improved by incorporating more data sets of the ocean optical properties data that will be obtained from waters around the Korean Peninsula.

A Study of Tasseled Cap Transformation Coefficient for the Geostationary Ocean Color Imager (GOCI) (정지궤도 천리안위성 해양관측센서 GOCI의 Tasseled Cap 변환계수 산출연구)

  • Shin, Ji-Sun;Park, Wook;Won, Joong-Sun
    • Korean Journal of Remote Sensing
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    • v.30 no.2
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    • pp.275-292
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    • 2014
  • The objective of this study is to determine Tasseled Cap Transformation (TCT) coefficients for the Geostationary Ocean Color Imager (GOCI). TCT is traditional method of analyzing the characteristics of the land area from multi spectral sensor data. TCT coefficients for a new sensor must be estimated individually because of different sensor characteristics of each sensor. Although the primary objective of the GOCI is for ocean color study, one half of the scene covers land area with typical land observing channels in Visible-Near InfraRed (VNIR). The GOCI has a unique capability to acquire eight scenes per day. This advantage of high temporal resolution can be utilized for detecting daily variation of land surface. The GOCI TCT offers a great potential for application in near-real time analysis and interpretation of land cover characteristics. TCT generally represents information of "Brightness", "Greenness" and "Wetness". However, in the case of the GOCI is not able to provide "Wetness" due to lack of ShortWave InfraRed (SWIR) band. To maximize the utilization of high temporal resolution, "Wetness" should be provided. In order to obtain "Wetness", the linear regression method was used to align the GOCI Principal Component Analysis (PCA) space with the MODIS TCT space. The GOCI TCT coefficients obtained by this method have different values according to observation time due to the characteristics of geostationary earth orbit. To examine these differences, the correlation between the GOCI TCT and the MODIS TCT were compared. As a result, while the GOCI TCT coefficients of "Brightness" and "Greenness" were selected at 4h, the GOCI TCT coefficient of "Wetness" was selected at 2h. To assess the adequacy of the resulting GOCI TCT coefficients, the GOCI TCT data were compared to the MODIS TCT image and several land parameters. The land cover classification of the GOCI TCT image was expressed more precisely than the MODIS TCT image. The distribution of land cover classification of the GOCI TCT space showed meaningful results. Also, "Brightness", "Greenness", and "Wetness" of the GOCI TCT data showed a relatively high correlation with Albedo ($R^2$ = 0.75), Normalized Difference Vegetation Index (NDVI) ($R^2$ = 0.97), and Normalized Difference Moisture Index (NDMI) ($R^2$ = 0.77), respectively. These results indicate the suitability of the GOCI TCT coefficients.

Introduction of Acquisition System, Processing System and Distributing Service for Geostationary Ocean Color Imager (GOCI) Data (정지궤도 해색탑재체(GOCI) 데이터의 수신.처리 시스템과 배포 서비스)

  • Yang, Chan-Su;Bae, Sang-Soo;Han, Hee-Jeong;Ahn, Yu-Hwan;Ryu, Joo-Hyung;Han, Tai-Hyun;Yoo, Hong-Rhyong
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.263-275
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    • 2010
  • KOSC(Korea Ocean Satellite Center), the primary operational organization for GOCI(Geostationary Ocean Color Imager), was established in KORDI(Korea Ocean Research & Development Institute). For a stable distribution service of GOCI data, various systems were installed at KOSC as follows: GOCI Data Acquisition System, Image Pre-processing System, GOCI Data Processing System, GOCI Data Distribution System, Data Management System, Total Management & Control System and External Data Exchange System. KOSC distributes the GOCI data 8 times to user at 1-hour intervals during the daytime in near-real time according to the distribution policy. Finally, we introduce the KOSC website for users to search, request and download GOCI data.

Missions and User Requirements of the 2nd Geostationary Ocean Color Imager (GOCI-II) (제2호 정지궤도 해양탑재체(GOCI-II)의 임무 및 요구사양)

  • Ahn, Yu-Hwan;Ryu, Joo-Hyung;Cho, Seong-Ick;Kim, Suk-Hwan
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.277-285
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    • 2010
  • Geostationary Ocean Color Imager(GOCI-I), the world's first space-borne ocean color observation geostationary satellite, will be launched on June 2010. Development of GOCI-I took about 6 years, and its expected lifetime is about 7 years. The mission and user requirements of GOCI-II are required to be defined at this moment. Because baseline of the main mission of GOCI-II must be defined during the development time and early operational period of GOCI-I. The main difference between these missions is the global-monitoring capability of GOCI-II, which will meet the necessity of the monitoring and research on climate change in the long-term. The user requirements of GOCI-II will have higher spatial resolution, $250m{\times}250m$, and 12 spectral bands to fulfill GOCI-I's user request, which could not be implemented on GOCI-I for technical reasons. A dedicated panchromatic band will be added for the nighttime observation to obtain fishery information. GOCI-II will have a new capability, supporting user-definable observation requests such as clear sky area without clouds and special-event areas, etc. This will enable higher applicability of GOCI-II products. GOCI-II will perform observations 8 times daily, the same as GOCI-I's. Additionally, daily global observation once or twice daily is planned for GOCI-II. In this paper, we present an improved development and organization structure to solve the problems that have emerged so far. The hardware design of the GOCI-II will proceed in conjunction with domestic or foreign space agencies.

ERROR ANALYSIS FOR GOCI RADIOMETRIC CALIBRATION

  • Kang, Gm-Sil;Youn, Heong-Sik
    • Proceedings of the KSRS Conference
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    • pp.187-190
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    • 2007
  • 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 nonlinear radiometric model for GOCI will be validated through ground test. The GOCI radiometric calibration is based on on-board calibration devices; solar diffuser, DAMD (Diffuser Aging Monitoring Device). In this paper, the GOCI radiometric error propagation is analyzed. The radiometric model error due to the dark current nonlinearity is analyzed 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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The Analysis of GOCI CDOM for Observation of Ocean Environment Change (해양환경변화관측을 위한 GOCI CDOM 자료 분석)

  • Jeong, Jong-Chul
    • Journal of Environmental Impact Assessment
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    • v.22 no.4
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    • pp.389-395
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    • 2013
  • Geostationary Ocean Color Imager(GOCI), the World's first spaceborne ocean color observation satellite operated in geostationary orbit, was successfully launched on May 2010. The main missions of GOCI is the coastal environment monitoring of GOCI in order to meet the necessity of long-term climate change monitoring and research. The GOCI have higher spatial resolution than MODIS, $500m{\times}500m$, and 8 spectral ocean color channels. GOCI have a capability for observation on the coastal environment change, GOCI perform the observation with 8 times a day. In this paper, we presented the more improved results for observation on the coastal environment change than MODIS ocean color sensor and detected the spatial difference of CDOM for monitoring coastal environment change.

Operational Atmospheric Correction Method over Land Surfaces for GOCI Images

  • Lee, Hwa-Seon;Lee, Kyu-Sung
    • Korean Journal of Remote Sensing
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    • v.34 no.1
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    • pp.127-139
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    • 2018
  • The GOCI atmospheric correction overland surfaces is essential for the time-series analysis of terrestrial environments with the very high temporal resolution. We develop an operational GOCI atmospheric correction method over land surfaces, which is rather different from the one developed for ocean surface. The GOCI atmospheric correction method basically reduces gases absorption and Rayleigh and aerosol scatterings and to derive surface reflectance from at-sensor radiance. We use the 6S radiative transfer model that requires several input parameters to calculate surface reflectance. In the sensitivity analysis, aerosol optical thickness was the most influential element among other input parameters including atmospheric model, terrain elevation, and aerosol type. To account for the highly variable nature of aerosol within the GOCI target area in northeast Asia, we generate the spatio-temporal aerosol maps using AERONET data for the aerosol correction. For a fast processing, the GOCI atmospheric correction method uses the pre-calculated look up table that directly converts at-sensor radiance to surface reflectance. The atmospheric correction method was validated by comparing with in-situ spectral measurements and MODIS reflectance products. The GOCI surface reflectance showed very similar magnitude and temporal patterns with the in-situ measurements and the MODIS reflectance. The GOCI surface reflectance was slightly higher than the in-situ measurement and MODIS reflectance by 0.01 to 0.06, which might be due to the different viewing angles. Anisotropic effect in the GOCI hourly reflectance needs to be further normalized during the following cloud-free compositing.

ERROR PROPAGATION ANALYSIS FOR IN-ORBIT GOCI RADIOMETRIC CALIBRATION

  • Kang, Gm-Sil;Youn, Heong-Sik
    • Proceedings of the KSRS Conference
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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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Radiometric Characteristics of Geostationary Ocean Color Imager (GOCI) for Land Applications

  • Lee, Kyu-Sung;Park, Sung-Min;Kim, Sun-Hwa;Lee, Hwa-Seon;Shin, Jung-Il
    • Korean Journal of Remote Sensing
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    • v.28 no.3
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    • pp.277-285
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    • 2012
  • The GOCI imagery can be an effective alternative to monitor short-term changes over terrestrial environments. This study aimed to assess the radiometric characteristics of the GOCI multispectral imagery for land applications. As an initial approach, we compared GOCI at-sensor radiance with MODIS data obtained simultaneously. Dynamic range of GOCI radiance was larger than MODIS over land area. Further, the at-sensor radiance over various land surface targets were tested by vicarious calibration. Surface reflectance were directly measured in field using a portable spectrometer and indirectly derived from the atmospherically corrected MODIS product over relatively homogeneous sites of desert, tidal flat, bare soil, and fallow crop fields. The GOCI radiance values were then simulated by radiative transfer model (6S). In overall, simulated radiance were very similar to the actual radiance extracted from GOCI data. Normalized difference vegetation index (NDVI) calculated from the GOCI bands 5 and 8 shows very close relationship with MODIS NDVI. In this study, the GOCI imagery has shown appropriate radiometric quality to be used for various land applications. Further works are needed to derive surface reflectance over land area after atmospheric correction.

Creating Atmospheric Scattering Corrected True Color Image from the COMS/GOCI Data (천리안위성 해양탑재체 자료를 이용한 대기산란 효과가 제거된 컬러합성 영상 제작)

  • Lee, Kwon-Ho
    • 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.