Algorithm for retrieval of aerosol optical properties over the ocean from the Geostationary Ocean Color Imager SCIE SCOPUS

DC Field Value Language
dc.contributor.author Lee, Jaehwa -
dc.contributor.author Kim, Jhoon -
dc.contributor.author Song, Chul H. -
dc.contributor.author Ryu, Joo-Hyung -
dc.contributor.author Ahn, Yu-Hwan -
dc.contributor.author Song, C. K. -
dc.date.accessioned 2020-04-20T08:40:29Z -
dc.date.available 2020-04-20T08:40:29Z -
dc.date.created 2020-01-28 -
dc.date.issued 2010-05-17 -
dc.identifier.issn 0034-4257 -
dc.identifier.uri https://sciwatch.kiost.ac.kr/handle/2020.kiost/4096 -
dc.description.abstract An aerosol retrieval algorithm for the first Geostationary Ocean Color Imager (GOCI) to be launched in March 2010 onboard the Communication, Ocean, and Meteorological Satellite (COMS) is presented. The algorithm retrieves aerosol optical depth (AOD), fine-mode fraction (FMIF), and aerosol type in 500 m x 500 m resolution. All the products are retrieved over clear water which is defined by surface reflectance ratio between 640 nm and 860 nm (SRR) less or equal to 2.5, while only AOD is retrieved over turbid water (SRR>2.5) due to high surface reflectance. To develop optimized algorithm for the target area of GOCI, optical properties of aerosol are analyzed from extensive observation of AERONET sunphotometers to generate lookup table. Surface reflectance of turbid water is determined from 30-day composite of Rayleigh- and gas corrected reflectance. By applying the present algorithm to MODIS top-of-the atmosphere reflectance, three different aerosol cases dominated by anthropogenic aerosol contains black carbon (BC), dust, and non-absorbing aerosol are analyzed to test the algorithm. The algorithm retrieves AOD, and size information together with aerosol type which are consistent with results inferred by RGB image in a qualitative way. The comparison of the retrieved AOD with those of MODIS collection 5 and AERONET sunphotometer observations shows reliable results. Especially, the application of turbid water algorithm significantly increases the accuracy in retrieving AOD at Anmyon station. The sensitivity study between MODIS and GOCI instruments in terms of relative sensitivity and scattering angle shows promising applicability of the present algorithm to future GOCI measurements. (C) 2010 Elsevier Inc. All rights reserved. -
dc.description.uri 1 -
dc.language English -
dc.publisher ELSEVIER SCIENCE INC -
dc.subject VALIDATION -
dc.subject MTSAT-1R -
dc.subject CHANNELS -
dc.subject AVHRR -
dc.title Algorithm for retrieval of aerosol optical properties over the ocean from the Geostationary Ocean Color Imager -
dc.type Article -
dc.citation.endPage 1088 -
dc.citation.startPage 1077 -
dc.citation.title REMOTE SENSING OF ENVIRONMENT -
dc.citation.volume 114 -
dc.citation.number 5 -
dc.contributor.alternativeName 유주형 -
dc.contributor.alternativeName 안유환 -
dc.identifier.bibliographicCitation REMOTE SENSING OF ENVIRONMENT, v.114, no.5, pp.1077 - 1088 -
dc.identifier.doi 10.1016/j.rse.2009.12.021 -
dc.identifier.scopusid 2-s2.0-76349089302 -
dc.identifier.wosid 000275780800013 -
dc.type.docType Article -
dc.description.journalClass 1 -
dc.subject.keywordPlus VALIDATION -
dc.subject.keywordPlus MTSAT-1R -
dc.subject.keywordPlus CHANNELS -
dc.subject.keywordPlus AVHRR -
dc.subject.keywordAuthor Remote sensing -
dc.subject.keywordAuthor Algorithm -
dc.subject.keywordAuthor Aerosol optical depth -
dc.subject.keywordAuthor Fine-mode fraction -
dc.subject.keywordAuthor Aerosol type -
dc.subject.keywordAuthor Geostationary -
dc.relation.journalWebOfScienceCategory Environmental Sciences -
dc.relation.journalWebOfScienceCategory Remote Sensing -
dc.relation.journalWebOfScienceCategory Imaging Science & Photographic Technology -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.relation.journalResearchArea Environmental Sciences & Ecology -
dc.relation.journalResearchArea Remote Sensing -
dc.relation.journalResearchArea Imaging Science & Photographic Technology -
Appears in Collections:
Marine Digital Resources Department > Korea Ocean Satellite Center > 1. Journal Articles
Files in This Item:
There are no files associated with this item.

qrcode

Items in ScienceWatch@KIOST are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse