Assessment of ocean color atmospheric correction methods and development of a regional ocean color operational dataset for the Baltic Sea based on Sentinel-3 OLCI
The Baltic Sea is characterized by large gradients in salinity, high concentrations of colored dissolved organic matter, and a phytoplankton phenology with two seasonal blooms. Satellite retrievals of chlorophyll- a concentration (chl- a ) are hindered by the optical complexity of this basin and the...
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Online Access: | http://dx.doi.org/10.3389/fmars.2023.1256990 https://www.frontiersin.org/articles/10.3389/fmars.2023.1256990/full |
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crfrontiers:10.3389/fmars.2023.1256990 2024-04-21T07:43:49+00:00 Assessment of ocean color atmospheric correction methods and development of a regional ocean color operational dataset for the Baltic Sea based on Sentinel-3 OLCI González Vilas, Luis Brando, Vittorio Ernesto Di Cicco, Annalisa Colella, Simone D’Alimonte, Davide Kajiyama, Tamito Attila, Jenni Schroeder, Thomas H2020 Excellent Science 2024 http://dx.doi.org/10.3389/fmars.2023.1256990 https://www.frontiersin.org/articles/10.3389/fmars.2023.1256990/full unknown Frontiers Media SA https://creativecommons.org/licenses/by/4.0/ Frontiers in Marine Science volume 10 ISSN 2296-7745 Ocean Engineering Water Science and Technology Aquatic Science Global and Planetary Change Oceanography journal-article 2024 crfrontiers https://doi.org/10.3389/fmars.2023.1256990 2024-03-26T08:33:54Z The Baltic Sea is characterized by large gradients in salinity, high concentrations of colored dissolved organic matter, and a phytoplankton phenology with two seasonal blooms. Satellite retrievals of chlorophyll- a concentration (chl- a ) are hindered by the optical complexity of this basin and the reduced performance of the atmospheric correction in its highly absorbing waters. Within the development of a regional ocean color operational processing chain for the Baltic Sea based on Sentinel-3 Ocean and Land Colour Instrument (OLCI) full-resolution data, the performance of four atmospheric correction processors for the retrieval of remote-sensing reflectance ( Rrs ) was analyzed. Assessments based on three Aerosol Robotic Network-Ocean Color (AERONET-OC) sites and shipborne hyperspectral radiometers show that POLYMER was the best-performing processor in the visible spectral range, also providing a better spatial coverage compared with the other processors. Hence, OLCI Rrs spectra retrieved with POLYMER were chosen as input for a bio-optical ensemble scheme that computes chl- a as a weighted sum of different regional multilayer perceptron neural nets. This study also evaluated the operational Rrs and chl- a datasets for the Baltic Sea based on OC-CCI v.6. The chl- a retrievals based on OC-CCI v.6 and OLCI Rrs , assessed against in-situ chl- a measurements, yielded similar results (OC-CCI v.6: R 2 = 0.11, bias = −0.22; OLCI: R 2 = 0.16, bias = −0.03) using a common set of match-ups for the same period. Finally, an overall good agreement was found between chl- a retrievals from OLCI and OC-CCI v.6 although differences between Rrs were amplified in terms of chl- a estimates. Article in Journal/Newspaper Aerosol Robotic Network Frontiers (Publisher) Frontiers in Marine Science 10 |
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Open Polar |
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Frontiers (Publisher) |
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crfrontiers |
language |
unknown |
topic |
Ocean Engineering Water Science and Technology Aquatic Science Global and Planetary Change Oceanography |
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Ocean Engineering Water Science and Technology Aquatic Science Global and Planetary Change Oceanography González Vilas, Luis Brando, Vittorio Ernesto Di Cicco, Annalisa Colella, Simone D’Alimonte, Davide Kajiyama, Tamito Attila, Jenni Schroeder, Thomas Assessment of ocean color atmospheric correction methods and development of a regional ocean color operational dataset for the Baltic Sea based on Sentinel-3 OLCI |
topic_facet |
Ocean Engineering Water Science and Technology Aquatic Science Global and Planetary Change Oceanography |
description |
The Baltic Sea is characterized by large gradients in salinity, high concentrations of colored dissolved organic matter, and a phytoplankton phenology with two seasonal blooms. Satellite retrievals of chlorophyll- a concentration (chl- a ) are hindered by the optical complexity of this basin and the reduced performance of the atmospheric correction in its highly absorbing waters. Within the development of a regional ocean color operational processing chain for the Baltic Sea based on Sentinel-3 Ocean and Land Colour Instrument (OLCI) full-resolution data, the performance of four atmospheric correction processors for the retrieval of remote-sensing reflectance ( Rrs ) was analyzed. Assessments based on three Aerosol Robotic Network-Ocean Color (AERONET-OC) sites and shipborne hyperspectral radiometers show that POLYMER was the best-performing processor in the visible spectral range, also providing a better spatial coverage compared with the other processors. Hence, OLCI Rrs spectra retrieved with POLYMER were chosen as input for a bio-optical ensemble scheme that computes chl- a as a weighted sum of different regional multilayer perceptron neural nets. This study also evaluated the operational Rrs and chl- a datasets for the Baltic Sea based on OC-CCI v.6. The chl- a retrievals based on OC-CCI v.6 and OLCI Rrs , assessed against in-situ chl- a measurements, yielded similar results (OC-CCI v.6: R 2 = 0.11, bias = −0.22; OLCI: R 2 = 0.16, bias = −0.03) using a common set of match-ups for the same period. Finally, an overall good agreement was found between chl- a retrievals from OLCI and OC-CCI v.6 although differences between Rrs were amplified in terms of chl- a estimates. |
author2 |
H2020 Excellent Science |
format |
Article in Journal/Newspaper |
author |
González Vilas, Luis Brando, Vittorio Ernesto Di Cicco, Annalisa Colella, Simone D’Alimonte, Davide Kajiyama, Tamito Attila, Jenni Schroeder, Thomas |
author_facet |
González Vilas, Luis Brando, Vittorio Ernesto Di Cicco, Annalisa Colella, Simone D’Alimonte, Davide Kajiyama, Tamito Attila, Jenni Schroeder, Thomas |
author_sort |
González Vilas, Luis |
title |
Assessment of ocean color atmospheric correction methods and development of a regional ocean color operational dataset for the Baltic Sea based on Sentinel-3 OLCI |
title_short |
Assessment of ocean color atmospheric correction methods and development of a regional ocean color operational dataset for the Baltic Sea based on Sentinel-3 OLCI |
title_full |
Assessment of ocean color atmospheric correction methods and development of a regional ocean color operational dataset for the Baltic Sea based on Sentinel-3 OLCI |
title_fullStr |
Assessment of ocean color atmospheric correction methods and development of a regional ocean color operational dataset for the Baltic Sea based on Sentinel-3 OLCI |
title_full_unstemmed |
Assessment of ocean color atmospheric correction methods and development of a regional ocean color operational dataset for the Baltic Sea based on Sentinel-3 OLCI |
title_sort |
assessment of ocean color atmospheric correction methods and development of a regional ocean color operational dataset for the baltic sea based on sentinel-3 olci |
publisher |
Frontiers Media SA |
publishDate |
2024 |
url |
http://dx.doi.org/10.3389/fmars.2023.1256990 https://www.frontiersin.org/articles/10.3389/fmars.2023.1256990/full |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Frontiers in Marine Science volume 10 ISSN 2296-7745 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3389/fmars.2023.1256990 |
container_title |
Frontiers in Marine Science |
container_volume |
10 |
_version_ |
1796933541018206208 |