How Representative Are European AERONET-OC Sites of European Marine Waters?
Data from the Ocean Color component of the Aerosol Robotic Network (AERONET-OC) have been extensively used to assess Ocean Color radiometric products from various satellite sensors. This study, focusing on Ocean Color radiometric operational products from the Sentinel-3 Ocean and Land Colour Instrum...
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2024
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Online Access: | https://doi.org/10.3390/rs16101793 https://doaj.org/article/ebf4a4f554304d16a50b4f48e557dab3 |
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ftdoajarticles:oai:doaj.org/article:ebf4a4f554304d16a50b4f48e557dab3 2024-09-15T17:35:13+00:00 How Representative Are European AERONET-OC Sites of European Marine Waters? Ilaria Cazzaniga Frédéric Mélin 2024-05-01T00:00:00Z https://doi.org/10.3390/rs16101793 https://doaj.org/article/ebf4a4f554304d16a50b4f48e557dab3 EN eng MDPI AG https://www.mdpi.com/2072-4292/16/10/1793 https://doaj.org/toc/2072-4292 doi:10.3390/rs16101793 2072-4292 https://doaj.org/article/ebf4a4f554304d16a50b4f48e557dab3 Remote Sensing, Vol 16, Iss 10, p 1793 (2024) optical water types remote sensing reflectance AERONET-OC classification ocean color OLCI Science Q article 2024 ftdoajarticles https://doi.org/10.3390/rs16101793 2024-08-05T17:49:20Z Data from the Ocean Color component of the Aerosol Robotic Network (AERONET-OC) have been extensively used to assess Ocean Color radiometric products from various satellite sensors. This study, focusing on Ocean Color radiometric operational products from the Sentinel-3 Ocean and Land Colour Instrument (OLCI), aims at investigating where in the European seas the results of match-up analyses at the European marine AERONET-OC sites could be applicable. Data clustering is applied to OLCI remote sensing reflectance <semantics> R R S ( λ ) </semantics> from the various sites to define different sets of optical classes, which are later used to identify class-based uncertainties. A set of fifteen classes grants medium-to-high classification levels to most European seas, with exceptions in the South-East Mediterranean Sea, the Atlantic Ocean, or the Gulf of Bothnia. In these areas, <semantics> R R S ( λ ) </semantics> spectra are very often identified as novel with respect to the generated set of classes, suggesting their under-representation in AERONET-OC data. Uncertainties are finally mapped onto European seas according to class membership. The largest uncertainty values are obtained in the blue spectral region for almost all classes. In clear waters, larger values are obtained in the blue bands. Conversely, larger values are shown in the green and red bands in coastal and turbid waters. Article in Journal/Newspaper Aerosol Robotic Network Directory of Open Access Journals: DOAJ Articles Remote Sensing 16 10 1793 |
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Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
optical water types remote sensing reflectance AERONET-OC classification ocean color OLCI Science Q |
spellingShingle |
optical water types remote sensing reflectance AERONET-OC classification ocean color OLCI Science Q Ilaria Cazzaniga Frédéric Mélin How Representative Are European AERONET-OC Sites of European Marine Waters? |
topic_facet |
optical water types remote sensing reflectance AERONET-OC classification ocean color OLCI Science Q |
description |
Data from the Ocean Color component of the Aerosol Robotic Network (AERONET-OC) have been extensively used to assess Ocean Color radiometric products from various satellite sensors. This study, focusing on Ocean Color radiometric operational products from the Sentinel-3 Ocean and Land Colour Instrument (OLCI), aims at investigating where in the European seas the results of match-up analyses at the European marine AERONET-OC sites could be applicable. Data clustering is applied to OLCI remote sensing reflectance <semantics> R R S ( λ ) </semantics> from the various sites to define different sets of optical classes, which are later used to identify class-based uncertainties. A set of fifteen classes grants medium-to-high classification levels to most European seas, with exceptions in the South-East Mediterranean Sea, the Atlantic Ocean, or the Gulf of Bothnia. In these areas, <semantics> R R S ( λ ) </semantics> spectra are very often identified as novel with respect to the generated set of classes, suggesting their under-representation in AERONET-OC data. Uncertainties are finally mapped onto European seas according to class membership. The largest uncertainty values are obtained in the blue spectral region for almost all classes. In clear waters, larger values are obtained in the blue bands. Conversely, larger values are shown in the green and red bands in coastal and turbid waters. |
format |
Article in Journal/Newspaper |
author |
Ilaria Cazzaniga Frédéric Mélin |
author_facet |
Ilaria Cazzaniga Frédéric Mélin |
author_sort |
Ilaria Cazzaniga |
title |
How Representative Are European AERONET-OC Sites of European Marine Waters? |
title_short |
How Representative Are European AERONET-OC Sites of European Marine Waters? |
title_full |
How Representative Are European AERONET-OC Sites of European Marine Waters? |
title_fullStr |
How Representative Are European AERONET-OC Sites of European Marine Waters? |
title_full_unstemmed |
How Representative Are European AERONET-OC Sites of European Marine Waters? |
title_sort |
how representative are european aeronet-oc sites of european marine waters? |
publisher |
MDPI AG |
publishDate |
2024 |
url |
https://doi.org/10.3390/rs16101793 https://doaj.org/article/ebf4a4f554304d16a50b4f48e557dab3 |
genre |
Aerosol Robotic Network |
genre_facet |
Aerosol Robotic Network |
op_source |
Remote Sensing, Vol 16, Iss 10, p 1793 (2024) |
op_relation |
https://www.mdpi.com/2072-4292/16/10/1793 https://doaj.org/toc/2072-4292 doi:10.3390/rs16101793 2072-4292 https://doaj.org/article/ebf4a4f554304d16a50b4f48e557dab3 |
op_doi |
https://doi.org/10.3390/rs16101793 |
container_title |
Remote Sensing |
container_volume |
16 |
container_issue |
10 |
container_start_page |
1793 |
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1810444990918164480 |