• 제목/요약/키워드: Geostationary Ocean Color Sensor (GOCI)

검색결과 28건 처리시간 0.022초

Introduction to COMS Geostationary Ocean Color Imager

  • Kang Gumsil;Kim Jongah;Myung Hwan-Chun;Yeon Jeong-Heum;Kang Song-Doug;Youn Heong-Sik
    • 대한원격탐사학회:학술대회논문집
    • /
    • 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
    • /
    • pp.108-111
    • /
    • 2005
  • The Communication Ocean, Meteorological Satellite (COMS) as the one of the national space program has been developed by Korea Aerospace Research Institute (KARl). The Geostationary Ocean Color Imager (GOCI) is one of the main payloads ofCOMS which will provide consistent monitoring of ocean-colour around the Korean Peninsula from geostationary platforms. The ocean color observation from geostationary platform is required to remedy the coverage constraints imposed by polar orbiting platforms. In this paper the main characteristics of GOCI are described and compared with the current ocean color sensors. The GOCI will provide the measurement data of 6 visible channels and 2 nearinfrared channels (40Onm - 900nm). The high radiometric sensitivity is essential of ocean color sensor because of the weak water leaving radiance.

  • PDF

정지궤도 해색탑재체(GOCI) 자료를 위한 대기 및 BRDF 보정 연구 (Atmospheric and BRDF Correction Method for Geostationary Ocean Color Imagery (GOCI))

  • 민지은;유주형;안유환
    • 대한원격탐사학회지
    • /
    • 제26권2호
    • /
    • pp.175-188
    • /
    • 2010
  • 세계 최초로 정지 상태로 해색을 관측하는 정지궤도해색탑재체(GOCI, Geostationary Ocean Color Imager) 값의 보정을 위해서는 기존의 방법이 아닌 새로운 방법이 요구된다. 본 연구에서는 GOCI의 특별한 특성에 맞는 새로운 대기보정 방법과 양방향성 광반사 분포함수(BRDF, Bidirectional Reflectance Distribution Function) 보정 방법을 소개하고자 한다. GOCI의 대기보정을 위해서 스펙트럼 형태 조화기법(SSMM, Spectral Shape Matching Method)과 Sun Glint Correction Algorithm(SGCA)을 개발하였고, BRDF 보정을 위하여 해수의 고유광특성(IOP, Inherent Optical Property) 값을 이용하는 새로운 방법을 개발하였다. 각 방법은 한반도 주변 해역을 관측한 Sea Viewing Wide Field-of-view Sensor(SeaWiFS) 위성영상을 이용하여 적용하였다. 클로로필 농도 분포 영상을 만들어 본 결과 기존의 방법으로 얻기 어려웠던 탁도높은 해역과 에어로졸의 영향을 많이 받는 지역에서 보다 정확한 자료를 얻을 수 있었다.

해양환경변화관측을 위한 GOCI CDOM 자료 분석 (The Analysis of GOCI CDOM for Observation of Ocean Environment Change)

  • 정종철
    • 환경영향평가
    • /
    • 제22권4호
    • /
    • pp.389-395
    • /
    • 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.

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

  • 양현;윤석;한희정;허재무;박영제
    • 정보과학회 컴퓨팅의 실제 논문지
    • /
    • 제23권1호
    • /
    • pp.74-79
    • /
    • 2017
  • 세계 최초의 정지궤도 해양관측위성 센서인 천리안해양관측위성(Geostationary Ocean Color Imager; GOCI)은 적조, 녹조, 모자반, 냉수대, 태풍 등의 해양재해를 실시간으로 모니터링하여 피해를 최소화하는데 활용될 수 있다. 이와 같은 활용성을 극대화하기 위해, 이 논문에서는 천리안해양관측위성의 자료처리 방법 및 절차에 관하여 기술하고 있다. 천리안해양관측위성의 자료처리는 크게 수신, 처리, 저장, 배포로 구분되며, 자료의 종류는 Raw, Level 1, Level 2 등으로 나눠진다. Raw 자료는 위성으로부터 수신한 직후의 자료로 구조화되기 이전의 자료를 의미하고, Level 1 자료는 방사보정 및 기하보정을 통하여 2차원으로 구조화한 반사도 자료를 의미하며, Level 2 자료는 Level 1 반사도 자료에 다양한 해색 알고리즘을 적용하여 엽록소농도, 부유물질농도 등을 추출한 해색자료를 의미한다.

OVERVIEW OF KOREA OCEAN SATELLITE CENTER (KOSC) DEVELOPMENT

  • Yang, Chan-Su;Han, Hee-Jeong;Ahn, Yu-Hwan;Moon, Jeong-Eon;Lee, Nu-Ree
    • 대한원격탐사학회:학술대회논문집
    • /
    • 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume I
    • /
    • pp.75-78
    • /
    • 2006
  • The Korea Ocean Satellite Center (KOSC) is under development to establish in line with the launch of the first Korean multi-function geostationary satellite COMS (Communication, Ocean and Meteorological Satellite) scheduled in 2008. KOSC aims to receive, process and distribute Geostationary Ocean Color Sensor (GOCI) data on board COMS in near-real time. In this report, current status of KOSC development is presented in the following categories; site selection for KOSC, antenna design, GOCI data receiving and processing system, data distribution, future works.

  • PDF

Conceptual Study of GEO and LEO Sensors Characteristics for Monitoring Ocean Color around Korean Peninsula

  • Kang Gumsil;Kang Songdoug;Yong Sangsoon;Kim Jongah;Chang Youngjun;Youn Heongsik
    • 대한원격탐사학회:학술대회논문집
    • /
    • 대한원격탐사학회 2004년도 Proceedings of ISRS 2004
    • /
    • pp.505-508
    • /
    • 2004
  • Korea Aerospace Research Institute (KARI) has a plan to launch COMS for consistent monitoring of the Korean Peninsula. Korea Geostationary Ocean Color Imager (GOCI) is one of the main payloads of COMS which will provide a monitoring of ocean-colour around the Korean Peninsula from geostationary platforms. Ocean color observation from geostationary platform is required to achieve the proper spatial and temporal resolution for coastal observation mission. In this paper the characteristics of GOCI and LEO sensors are discussed. GOCI will provide the measurement data of 6 visible channels and 2 near-infrared channels (400nm ~ 900nm). The integration time and aperture diameter required to achieve the SNR specification of KGOCI are analyzed.

  • PDF

천리안해양관측위성을 활용한 해양 재난 검출 시스템 (Ocean Disaster Detection System(OD2S) using Geostationary Ocean Color Imager(GOCI))

  • 양현;유정미;한희정;유주형;박영제
    • 한국IT서비스학회지
    • /
    • 제11권sup호
    • /
    • pp.177-189
    • /
    • 2012
  • We developed the ocean disaster detection system(OD2S) which copes with the occurrences of ocean disasters (e. g. the red and green tide, the oil spill, the typhoon, and the sea ice) by converging and integrating the ocean color remote sensing using the satellite and the information technology exploiting the mass data processing and the pattern recognitions. This system which is based on the cosine similarity detects the ocean disasters in real time. The existing ocean color sensors which are operated in the polar orbit platforms cannot conduct the real time observation of ocean environments because they support the low temporal resolutions of one observation a day. However, geostationary ocean color imager(GOCI), the first geostationary ocean color sensor in the world, produces the ocean color images(e. g. the chlorophyll, the colored dissolved organic matter(CDOM), and the total suspended solid(TSS)), with high temporal resolutions of hourly intervals up to eight observations a day. The evaluation demonstrated that the OD2S can detect the excessive concentration of chlorophyll, CDOM, and TSS. Based on these results, it is expected that OD2S detects the ocean disasters in real time.

DEVELOPMENT OF CHLOROPHYLL ALGORITHM FOR GEOSTATIONARY OCEAN COLOR IMAGER (GOCI)

  • Min, Jee-Eun;Moon, Jeong-Eon;Shanmugam, Palanisamy;Ryu, Joo-Hyung;Ahn, Yu-Hwan
    • 대한원격탐사학회:학술대회논문집
    • /
    • 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
    • /
    • pp.162-165
    • /
    • 2007
  • Chlorophyll concentration is an important factor for physical oceanography as well as biological oceanography. For these necessity many oceanographic researchers have been investigated it for a long time. But investigation using vessel is very inefficient, on the other hands, ocean color remote sensing is a powerful means to get fine-scale (spatial and temporal scale) measurements of chlorophyll concentration. Geostationary Ocean Color Imager (GOCI), for ocean color sensor, loaded on COMS (Communication, Ocean and Meteorological Satellite), will be launched on late 2008 in Korea. According to the necessity of algorithm for GOCI, we developed chlorophyll algorithm for GOCI in this study. There are two types of chlorophyll algorithms. One is an empirical algorithm using band ratio, and the other one is a fluorescence-based algorithms. To develop GOCI chlorophyll algorithm empirically we used bands centered at 412 nm, 443 nm and 555 nm for the DOM absorption, chlorophyll maximum absorption and for absorption of suspended solid material respectively. For the fluorescence-based algorithm we analyzed in-situ remote sensing reflectance $(R_{rs})$ data using baseline method. Fluorescence Line Height $({\Delta}Flu)$ calculated from $R_{rs}$ at bands centered on 681 nm and 688 nm, and ${\Delta}Flu_{(area)}$ are used for development of algorithm. As a result ${\Delta}Flu_{(area)}$ method leads the best fitting for squared correlation coefficient $(R^2)$.

  • PDF

GOCI-II 태양광 보정시스템을 활용한 가시 채널 복사 보정 개선 및 센서 안정성 분석 (GOCI-IIVisible Radiometric Calibration Using Solar Radiance Observations and Sensor Stability Analysis)

  • 김민상;박명숙;안재현;강금실
    • 대한원격탐사학회지
    • /
    • 제39권6_2호
    • /
    • pp.1541-1551
    • /
    • 2023
  • 해색위성 원격탐사에서 광학센서에서 측정된 전자기 시그날을 태양광 복사휘도로 산출하는 것은 해양 환경 모니터링의 시작이 되는 중요 단계이다. 일반적으로 광학센서가 임무 기간 수많은 촬영을 하면서 감쇄가 일반적이며 이로 인해 발생하는 복사 보정의 불확도는 해수원격반사도, 엽록소-a 농도, 유색용존유기물 등 최종 산출물에 영향을 미치기 때문에, 국제적으로 해색위성의 임무기간 중 자료 연속성을 위한 복사보정의 중요성을 강조해 왔다. 본 연구는 Geostationary Ocean Color Imager-II (GOCI-II) 위성의 지속적인 품질과 정확성을 확보하기 위해 GOCI-II의 복사 보정 알고리즘을 개선 방법을 제시한다. GOCI-II는 궤도상 복사 보정 장치인 태양광 확산기(Solar Diffuser, SD)를 사용하여 gain을 지속적으로 측정하였다. 시계열 분석 결과 gain이 방위각에 따라 계절적 변동을 보임과 동시에 센서의 노후화 가능성을 고려해야 함을 확인하였다. 본 연구에서는 방위각 보정 모델을 도입하여 계절 주기성을 제거하였고, 센서 감쇄 보정 모델을 통해 복사 이득의 비선형적 추세를 산출하였다. 본 연구에서 개선된 복사 보정 알고리즘을 적용하여 대기 최상층(Top of Atmosphere, TOA) 복사휘도의 스펙트럼에 미치는 영향을 확인하였고, 이는 GOCI-II 데이터의 장기적인 안정성 확보를 통해 신뢰성 있는 위성 산출물을 제공함으로써 장기간 트렌드 분석 및 해양 환경 모니터링에 기여할 것으로 기대된다.

Improvement of Temporal Resolution for Land Surface Monitoring by the Geostationary Ocean Color Imager Data

  • Lee, Hwa-Seon;Lee, Kyu-Sung
    • 대한원격탐사학회지
    • /
    • 제32권1호
    • /
    • pp.25-38
    • /
    • 2016
  • With the increasing need for high temporal resolution satellite imagery for monitoring land surfaces, this study evaluated the temporal resolution of the NDVI composites from Geostationary Ocean Color Imager (GOCI) data. The GOCI is the first geostationary satellite sensor designed to provide continuous images over a $2,500{\times}2,500km^2$ area of the northeast Asian region with relatively high spatial resolution of 500 m. We used total 2,944 hourly images of the GOCI level 1B radiance data obtained during the one-year period from April 2011 to March 2012. A daily NDVI composite was produced by maximum value compositing of eight hourly images captured during day-time. Further NDVI composites were created with different compositing periods ranging from two to five days. The cloud coverage of each composite was estimated by the cloud detection method developed in study and then compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua cloud product and 16-day NDVI composite. The GOCI NDVI composites showed much higher temporal resolution with less cloud coverage than the MODIS NDVI products. The average of cloud coverage for the five-day GOCI composites during the one year was only 2.5%, which is a significant improvement compared to the 8.9%~19.3% cloud coverage in the MODIS 16-day NDVI composites.