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Bayesian Model for Matching the Radiometric Measurements of Aerospace and Field Ocean Color Sensors

A Bayesian model is developed to match aerospace ocean color observation to field measurements and derive the spatial variability of match-up sites. The performance of the model is tested against populations of synthesized spectra and full and reduced resolutions of MERIS data. The model derived the...

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Detalles Bibliográficos
Autores principales: Salama, Mhd. Suhyb, Su, Zhongbo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231150/
https://www.ncbi.nlm.nih.gov/pubmed/22163615
http://dx.doi.org/10.3390/s100807561
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author Salama, Mhd. Suhyb
Su, Zhongbo
author_facet Salama, Mhd. Suhyb
Su, Zhongbo
author_sort Salama, Mhd. Suhyb
collection PubMed
description A Bayesian model is developed to match aerospace ocean color observation to field measurements and derive the spatial variability of match-up sites. The performance of the model is tested against populations of synthesized spectra and full and reduced resolutions of MERIS data. The model derived the scale difference between synthesized satellite pixel and point measurements with R(2) > 0.88 and relative error < 21% in the spectral range from 400 nm to 695 nm. The sub-pixel variabilities of reduced resolution MERIS image are derived with less than 12% of relative errors in heterogeneous region. The method is generic and applicable to different sensors.
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spelling pubmed-32311502011-12-07 Bayesian Model for Matching the Radiometric Measurements of Aerospace and Field Ocean Color Sensors Salama, Mhd. Suhyb Su, Zhongbo Sensors (Basel) Article A Bayesian model is developed to match aerospace ocean color observation to field measurements and derive the spatial variability of match-up sites. The performance of the model is tested against populations of synthesized spectra and full and reduced resolutions of MERIS data. The model derived the scale difference between synthesized satellite pixel and point measurements with R(2) > 0.88 and relative error < 21% in the spectral range from 400 nm to 695 nm. The sub-pixel variabilities of reduced resolution MERIS image are derived with less than 12% of relative errors in heterogeneous region. The method is generic and applicable to different sensors. Molecular Diversity Preservation International (MDPI) 2010-08-11 /pmc/articles/PMC3231150/ /pubmed/22163615 http://dx.doi.org/10.3390/s100807561 Text en © 2010 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
Salama, Mhd. Suhyb
Su, Zhongbo
Bayesian Model for Matching the Radiometric Measurements of Aerospace and Field Ocean Color Sensors
title Bayesian Model for Matching the Radiometric Measurements of Aerospace and Field Ocean Color Sensors
title_full Bayesian Model for Matching the Radiometric Measurements of Aerospace and Field Ocean Color Sensors
title_fullStr Bayesian Model for Matching the Radiometric Measurements of Aerospace and Field Ocean Color Sensors
title_full_unstemmed Bayesian Model for Matching the Radiometric Measurements of Aerospace and Field Ocean Color Sensors
title_short Bayesian Model for Matching the Radiometric Measurements of Aerospace and Field Ocean Color Sensors
title_sort bayesian model for matching the radiometric measurements of aerospace and field ocean color sensors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3231150/
https://www.ncbi.nlm.nih.gov/pubmed/22163615
http://dx.doi.org/10.3390/s100807561
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