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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Published in:Remote Sensing
Main Authors: Ilaria Cazzaniga, Frédéric Mélin
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2024
Subjects:
Q
Online Access:https://doi.org/10.3390/rs16101793
https://doaj.org/article/ebf4a4f554304d16a50b4f48e557dab3
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spelling 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
institution 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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