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Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS

This study evaluated the ability to improve Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels’ benthic class. The form of the Ocean Color (OC) algorithm was assumed for this study. The operational atmos...

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Autores principales: Blakey, Tara, Melesse, Assefa, Sukop, Michael C., Tachiev, Georgio, Whitman, Dean, Miralles-Wilhelm, Fernando
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5087534/
https://www.ncbi.nlm.nih.gov/pubmed/27775626
http://dx.doi.org/10.3390/s16101749
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author Blakey, Tara
Melesse, Assefa
Sukop, Michael C.
Tachiev, Georgio
Whitman, Dean
Miralles-Wilhelm, Fernando
author_facet Blakey, Tara
Melesse, Assefa
Sukop, Michael C.
Tachiev, Georgio
Whitman, Dean
Miralles-Wilhelm, Fernando
author_sort Blakey, Tara
collection PubMed
description This study evaluated the ability to improve Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels’ benthic class. The form of the Ocean Color (OC) algorithm was assumed for this study. The operational atmospheric correction producing Level 2 SeaWiFS data was retained since the focus of this study was on establishing the benefit from the alternative specification of the bio-optical algorithm. Benthic class was determined through satellite image-based classification methods. Accuracy of the chl-a algorithms evaluated was determined through comparison with coincident in situ measurements of chl-a. The regionally-tuned models that were allowed to vary by benthic class produced more accurate estimates of chl-a than the single, unified regionally-tuned model. Mean absolute percent difference was approximately 70% for the regionally-tuned, benthic class-specific algorithms. Evaluation of the residuals indicated the potential for further improvement to chl-a estimation through finer characterization of benthic environments. Atmospheric correction procedures specialized to coastal environments were recognized as areas for future improvement as these procedures would improve both classification and algorithm tuning.
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spelling pubmed-50875342016-11-07 Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS Blakey, Tara Melesse, Assefa Sukop, Michael C. Tachiev, Georgio Whitman, Dean Miralles-Wilhelm, Fernando Sensors (Basel) Article This study evaluated the ability to improve Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) chl-a retrieval from optically shallow coastal waters by applying algorithms specific to the pixels’ benthic class. The form of the Ocean Color (OC) algorithm was assumed for this study. The operational atmospheric correction producing Level 2 SeaWiFS data was retained since the focus of this study was on establishing the benefit from the alternative specification of the bio-optical algorithm. Benthic class was determined through satellite image-based classification methods. Accuracy of the chl-a algorithms evaluated was determined through comparison with coincident in situ measurements of chl-a. The regionally-tuned models that were allowed to vary by benthic class produced more accurate estimates of chl-a than the single, unified regionally-tuned model. Mean absolute percent difference was approximately 70% for the regionally-tuned, benthic class-specific algorithms. Evaluation of the residuals indicated the potential for further improvement to chl-a estimation through finer characterization of benthic environments. Atmospheric correction procedures specialized to coastal environments were recognized as areas for future improvement as these procedures would improve both classification and algorithm tuning. MDPI 2016-10-20 /pmc/articles/PMC5087534/ /pubmed/27775626 http://dx.doi.org/10.3390/s16101749 Text en © 2016 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 (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Blakey, Tara
Melesse, Assefa
Sukop, Michael C.
Tachiev, Georgio
Whitman, Dean
Miralles-Wilhelm, Fernando
Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS
title Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS
title_full Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS
title_fullStr Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS
title_full_unstemmed Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS
title_short Developing Benthic Class Specific, Chlorophyll-a Retrieving Algorithms for Optically-Shallow Water Using SeaWiFS
title_sort developing benthic class specific, chlorophyll-a retrieving algorithms for optically-shallow water using seawifs
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5087534/
https://www.ncbi.nlm.nih.gov/pubmed/27775626
http://dx.doi.org/10.3390/s16101749
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