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Atmospheric and BRDF Correction Method for Geostationary Ocean Color Imagery (GOCI)

정지궤도 해색탑재체(GOCI) 자료를 위한 대기 및 BRDF 보정 연구

  • Min, Jee-Eun (Department of Ocean Engineering, Indian Institute of Technology Mardas) ;
  • Ryu, Joo-Hyung (Department of Ocean Engineering, Indian Institute of Technology Mardas) ;
  • Ahn, Yu-Hwan (Department of Ocean Engineering, Indian Institute of Technology Mardas) ;
  • Palanisamy, Shanmugam (Department of Ocean Engineering, Indian Institute of Technology Madras) ;
  • Deschamps, Pierre-Yves (Laboratoire d'Optique Atmospherique (LOA), Universite de Lille 1) ;
  • Lee, Zhong-Ping (Northern Gulf Institute, Mississippi State University)
  • 민지은 (한국해양연구원 해양위성센터) ;
  • 유주형 (한국해양연구원 해양위성센터) ;
  • 안유환 (한국해양연구원 해양위성센터) ;
  • ;
  • ;
  • Received : 2010.04.04
  • Accepted : 2010.04.23
  • Published : 2010.04.30

Abstract

A new correction method is required for the Geostationary Ocean Color Imager (GOCI), which is the world's first ocean color observing sensor in geostationary orbit. In this paper we introduce a new method of atmospheric and the Bidirectional Reflectance Distribution Function(BRDF) correction for GOCI. The Spectral Shape Matching Method(SSMM) and the Sun Glint Correction Algorithm(SGCA) were developed for atmospheric correction, and BRDF correction was improved using Inherent Optical Property(IOP) data. Each method was applied to the Sea-Viewing Wide Field-of-view Sensor(SeaWiFS) images obtained in the Korean sea area. More accurate estimates of chlorophyll concentrations could be possible in the turbid coastal waters as well as areas severely affected by aerosols.

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.

Keywords

Acknowledgement

Supported by : 한국해양연구원

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