• Title/Summary/Keyword: GDPS(GOCI Data Processing System)

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Development the Geostationary Ocean Color Imager (GOCI) Data Processing System (GDPS) (정지궤도 해색탑재체(GOCI) 해양자료처리시스템(GDPS)의 개발)

  • Han, Hee-Jeong;Ryu, Joo-Hyung;Ahn, Yu-Hwan
    • Korean Journal of Remote Sensing
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    • v.26 no.2
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    • pp.239-249
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    • 2010
  • The Geostationary Ocean Color Imager (GOCI) data-processing system (GDPS), which is a software system for satellite data processing and analysis of the first geostationary ocean color observation satellite, has been developed concurrently with the development of th satellite. The GDPS has functions to generate level 2 and 3 oceanographic analytical data, from level 1B data that comprise the total radiance information, by programming a specialized atmospheric algorithm and oceanic analytical algorithms to the software module. The GDPS will be a multiversion system not only as a standard Korea Ocean Satellite Center(KOSC) operational system, but also as a basic GOCI data-processing system for researchers and other users. Additionally, the GDPS will be used to make the GOCI images available for distribution by satellite network, to calculate the lookup table for radiometric calibration coefficients, to divide/mosaic several region images, to analyze time-series satellite data. the developed GDPS system has satisfied the user requirement to complete data production within 30 minutes. This system is expected to be able to be an excellent tool for monitoring both long-term and short-term changes of ocean environmental characteristics.

STATUS OF GOCI DATA PROCESSING SYSTEM(GDPS) DEVELOPMENT

  • Han, Hee-Jeong;Ahn, Yu-Hwan;Ryu, Joo-Hyung
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.159-161
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    • 2007
  • Geostationary Ocean Color Imager (GOCI), the world-first ocean remote sensing instrument on geostationary Communication, Ocean, Meteorological Satellite (COMS), will be able to take a picture of a large region several times a day (almost with every one hour interval). We, KORDI, are in charge for developing the GOCI data processing system (GDPS) which is the basic software for processing the data from GOCI. The GDPS will be based on windows operating system to produce the GOCI level 2 data products (useful for oceanographic environmental analysis) automatically in real-time mode. Also, the GDPS will be a user-interactive program by well-organized graphical user interfaces for data processing and visualization. Its products will be the chlorophyll concentration, amount of total suspended sediments (TSS), colored dissolved organic matters (CDOM) and red tide from water leaving radiance or remote sensing reflectance. In addition, the GDPS will be able to produce daily products such as water current vector, primary productivity, water quality categorization, vegetation index, using individual observation data composed from several subscenes provided by GOCI for each slit within the target area. The resulting GOCI level 2 data will be disseminated through LRIT using satellite dissemination system and through online request and download systems. This software is carefully designed and implemented, and will be tested by sub-contractual company until the end of this year. It will need to be updated in effect with respect to new/improved algorithms and the calibration/validation activities.

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A Study on Data Processing Technology based on a open source R to improve utilization of the Geostationary Ocean Color Imager(GOCI) Products (천리안해양관측위성 산출물 활용성 향상을 위한 오픈소스 R 기반 데이터 처리기술 연구)

  • OH, Jung-Hee;CHOI, Hyun-Woo;LEE, Chol-Young;YANG, Hyun;HAN, Hee-Jeong
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.4
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    • pp.215-228
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    • 2019
  • HDF5 data format is used to effectively store and distribute large volume of Geostationary Ocean Color Imager(GOCI) satellite data. The Korea Ocean Satellite Center has developed and provided a GOCI Data Processing System(GDPS) for general users who are not familiar with HDF5 format. Nevertheless, it is not easy to merge and process Hierarchical Data Format version5(HDF5) data that requires an understanding of satellite data characteristics, needs to learn how to use GDPS, and stores location and attribute information separately. Therefore, the open source R and rhdf5, data.table, and matrixStats packages were used to develop algorithm that could easily utilize satellite data in HDF5 format without the need for the process of using GDPS.

DEVELOPMENT OF GOCI/COMS DATA PROCESSING SYSTEM

  • Ahn, Yu-Hwan;Shanmugam, Palanisamy;Han, Hee-Jeong;Ryu, Joo-Hyung
    • Proceedings of the KSRS Conference
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    • v.1
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    • pp.90-93
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    • 2006
  • The first Geostationary Ocean Color Imager (GOCI) onboard its Communication Ocean and Meteorological Satellite (COMS) is scheduled for launch in 2008. GOCI includes the eight visible-to-near-infrared (NIR) bands, 0.5km pixel resolution, and a coverage region of 2500 ${\times}$ 2500km centered at 36N and 130E. GOCI has had the scope of its objectives broadened to understand the role of the oceans and ocean productivity in the climate system, biogeochemical variables, geological and biological response to physical dynamics and to detect and monitor toxic algal blooms of notable extension through observations of ocean color. The special feature with GOCI is that like MODIS, MERIS and GLI, it will include the band triplets 660-680-745 for the measurements of sun-induced chlorophyll-a fluorescence signal from the ocean. The GOCI will provide SeaWiFS quality observations with frequencies of image acquisition 8 times during daytime and 2 times during nighttime. With all the above features, GOCI is considered to be a remote sensing tool with great potential to contribute to better understanding of coastal oceanic ecosystem dynamics and processes by addressing environmental features in a multidisciplinary way. To achieve the objectives of the GOCI mission, we develop the GOCI Data Processing System (GDPS) which integrates all necessary basic and advanced techniques to process the GOCI data and deliver the desired biological and geophysical products to its user community. Several useful ocean parameters estimated by in-water and other optical algorithms included in the GDPS will be used for monitoring the ocean environment of Korea and neighbouring countries and input into the models for climate change prediction.

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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.

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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Establishment Status of the Korea Ocean Satellite Center and GOCI-Data Distribution System (해양위성센터 구축 현황 및 GOCI 자료배포시스템 소개)

  • Yang, Chan-Su;Bae, Sang-Soo;Han, Hee-Jeong;Cho, Seong-Ick;Ahn, Yu-Hwan
    • Proceedings of the KSRS Conference
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    • 2009.03a
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    • pp.367-370
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    • 2009
  • 한국해양연구원에서는 2009년 발사 예정인 통신해양기상위성(COMS: Communication, Ocean and Meteorological Satellite)의 해색센서인 정지궤도 해양위성(GOCI: Geostationary Ocean Color Imager) 데이터의 수신, 처리, 배포를 위한 해양위성센터(KOSC: Korea Ocean Satellite Center)를 구축하고 있다. 2005년 "해양위성센터 구축사업"의 시작으로, 전파 수신 환경 등의 조건을 고려하여, 안산에 위치한 한국해양연구원 본원으로 해양위성센터의 위치를 최종 확정하여 구축을 진행하고 있다. 2009년 3월 현재 수신시스템(GDAS: GOCI Data Aquisition System), 자료전처리시스템(IMPS: Image Pre-processing System), 자료처리시스템(GDPS: GOCI Data Processing System), 자료관리 시스템(DMS: Data Management System), 통합감시제어시스템(TMC: Total Management & Controlling System), 기관간 자료교환시스템(EDES: External Data Exchange System) 등이 구축 완료되었고, 위성자료 배포시스템(DDS: Data Distribution System)을 구축하고 있다. 고용량 데이터의 원활한 전송을 위한 데이터센터를 비롯하여 사용자관점에서의 시스템 구축을 추진하고 있으며, 위성 발사 후 사용자 등록을 시작할 계획이다.

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Data Processing System for the Geostationary Ocean Color Imager (GOCI) (천리안해양관측위성을 위한 자료 처리 시스템)

  • Yang, Hyun;Yoon, Suk;Han, Hee-Jeong;Heo, Jae-Moo;Park, Young-Je
    • KIISE Transactions on Computing Practices
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    • v.23 no.1
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    • pp.74-79
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    • 2017
  • The Geostationary Ocean Color Imager (GOCI), the world's first ocean color sensor operated in a geostationary orbit, can be utilized to mitigate damages by monitoring marine disasters in real time such as red tides, green algae, sargassum, cold pools, typhoons, and so on. In this paper, we described a methodology and procedure for processing GOCI data in order to maximize its utilization potential. The GOCI data processing procedure is divided into data reception, data processing, and data distribution. The kinds of GOCI data are classified as raw, level 1, and level 2. "Raw" refers to an unstructured data type immediately generated after reception by satellite communications. Level 1 is defined as a radiance data type of two dimensions, generated after radiometric and geometric corrections for raw data. Level 2 indicates an ocean color data type from level-1 data using ocean color algorithms.