Please use this identifier to cite or link to this item: http://repositorio.unitau.br/jspui/handle/20.500.11874/2772
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dc.contributor.authorPinto, Cibele T.pt_BR
dc.contributor.authorPonzoni, Flavio J.pt_BR
dc.contributor.authorCastro, Ruy M.pt_BR
dc.contributor.authorLeigh, Larrypt_BR
dc.contributor.authorKaewmanee, Morakotpt_BR
dc.contributor.authorAaron, Davidpt_BR
dc.contributor.authorHelder, Dennispt_BR
dc.date.accessioned2019-09-12T16:53:47Z-
dc.date.available2019-09-12T16:53:47Z-
dc.date.issued2016-
dc.citation.volume7pt_BR
dc.citation.issue9pt_BR
dc.citation.spage837-
dc.citation.epage846-
dc.identifier.doi10.1080/2150704X.2016.1190474pt_BR
dc.identifier.issn2150-704X-
dc.identifier.issn2150-7058-
dc.identifier.urihttp://repositorio.unitau.br/jspui/handle/20.500.11874/2772-
dc.description.abstractCross-calibration is one of the various methods applied for Earth Observation Satellites sensor calibration. In the cross-calibration procedure, one sensor is calibrated against another sensor, in which the radiometric calibration is better known, via near-simultaneous imaging of a common ground target. One of the most important steps during the cross-calibration is the Spectral Band Adjustment Factor (SBAF) assessment. The SBAF is used to compensate the differences in the spectral responses of the sensors, avoiding large uncertainties in cross-calibration results. The investigation described in this work focussed on the evaluation of the SBAF's inherent uncertainties using Monte Carlo Simulation method. Basically, the Monte Carlo approach is based on calculating multiple integral by random sampling. The SBAFs were developed for analogous Landsat 8 Operational Land Imager and CBERS 4 Multispectral Camera spectral bands. The Hyperion hyperspectral sensor on-board Earth Observing-1 was utilized to understand the spectral profile of the target and to derive the SBAF. This study was performed over two pseudo invariant calibration sites: Algodones Dunes and Libya-4. The spectral uncertainty of the SBAFs using Monte Carlo was found to be within 0.01-1.79%. The results suggested that the uncertainty of the SBAFs is dependent on the correlation between the input variables: the higher the correlation, the lowest is the SBAF uncertainty.en
dc.description.provenanceMade available in DSpace on 2019-09-12T16:53:47Z (GMT). No. of bitstreams: 0 Previous issue date: 2016en
dc.description.sponsorshipConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)pt_BR
dc.description.sponsorshipCoordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)pt_BR
dc.languageInglêspt_BR
dc.publisherTaylor & Francis Ltd-
dc.publisher.countryInglaterrapt_BR
dc.relation.ispartofRemote Sensing Letters-
dc.rightsEm verificaçãopt_BR
dc.sourceWeb of Sciencept_BR
dc.subject.otherAbsolute Radiometric Calibrationen
dc.subject.otherSatellite Sensorsen
dc.subject.otherSiteen
dc.titleEvaluation of the uncertainty in the spectral band adjustment factor (SBAF) for cross-calibration using Monte Carlo simulationen
dc.typeArtigo de Periódicopt_BR
dc.identifier.wosWOS:000378926400003-
dc.description.affiliation[Pinto, Cibele T.; Ponzoni, Flavio J.] Natl Inst Space Res, Div Remote Sensing, Sao Jose Dos Campos, Brazil-
dc.description.affiliation[Castro, Ruy M.] Inst Adv Studies, Div Geointelligence, Sao Jose Dos Campos, Brazil-
dc.description.affiliation[Castro, Ruy M.] Universidade de Taubaté (Unitau), Div Math & Phys-
dc.description.affiliation[Leigh, Larry; Kaewmanee, Morakot; Aaron, David; Helder, Dennis] S Dakota State Univ, Coll Engn, Off Engn Res, Brookings, SD 57007 USA-
dc.subject.wosareaRemote Sensingen
dc.subject.wosareaImaging Science & Photographic Technologyen
dc.subject.researchareaRemote Sensingen
dc.subject.researchareaImaging Science & Photographic Technologyen
Appears in Collections:Artigos de Periódicos

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