Assessment of Chlorophyll-a concentration from Sentinel-3 satellite images at the Mediterranean Sea using CMEMS open source in situ data

The objective of this study is to evaluate the efficiency of two well-known algorithms (Ocean Colour 4 for MERIS [OC4Me] and neural net [NN]) used in the calculation of chlorophyll-a (Chl-a) from the Sentinel-3 Ocean and Land Colour Instrument (OLCI) compared to in situ measurements covering the Med...

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Autores principales:	Moutzouris-Sidiris Ioannis, Topouzelis Konstantinos
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2021
Materias:	mediterranean sea remote sensing chlorophyll-a sentinel-3 Geology QE1-996.5
Acceso en línea:	https://doaj.org/article/aa889d89f4974cfb94990e4b6cd82009
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spelling	oai:doaj.org-article:aa889d89f4974cfb94990e4b6cd820092021-12-05T14:10:48ZAssessment of Chlorophyll-a concentration from Sentinel-3 satellite images at the Mediterranean Sea using CMEMS open source in situ data2391-544710.1515/geo-2020-0204https://doaj.org/article/aa889d89f4974cfb94990e4b6cd820092021-01-01T00:00:00Zhttps://doi.org/10.1515/geo-2020-0204https://doaj.org/toc/2391-5447The objective of this study is to evaluate the efficiency of two well-known algorithms (Ocean Colour 4 for MERIS [OC4Me] and neural net [NN]) used in the calculation of chlorophyll-a (Chl-a) from the Sentinel-3 Ocean and Land Colour Instrument (OLCI) compared to in situ measurements covering the Mediterranean Sea. In situ data set, obtained from the Copernicus Marine Environmental Monitoring Service (CMEMS) and more specifically from the data set with the title INSITU_MED_NRT_OBSERVATIONS_013_035, and Chl-a values at different depths were extracted. The concentration of Chl-a at a penetration depth was calculated. Then, water was classified into two categories, Case-1 and Case-2. For Case-2 waters, the OC4Me presents a moderate correlation with the in situ data for a time window of 0–2 h. In contrast with the NN algorithm, where very weak correlations were calculated, lower values of the statistical index of Bias for Case-1 waters were calculated for the OC4Me algorithm. Higher values of Pearson correlation were calculated (r > 0.5) for OC4Me algorithm than NN. OC4Me performed better than NN.Moutzouris-Sidiris IoannisTopouzelis KonstantinosDe Gruyterarticlemediterranean searemote sensingchlorophyll-asentinel-3GeologyQE1-996.5ENOpen Geosciences, Vol 13, Iss 1, Pp 85-97 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	mediterranean sea remote sensing chlorophyll-a sentinel-3 Geology QE1-996.5
spellingShingle	mediterranean sea remote sensing chlorophyll-a sentinel-3 Geology QE1-996.5 Moutzouris-Sidiris Ioannis Topouzelis Konstantinos Assessment of Chlorophyll-a concentration from Sentinel-3 satellite images at the Mediterranean Sea using CMEMS open source in situ data
description	The objective of this study is to evaluate the efficiency of two well-known algorithms (Ocean Colour 4 for MERIS [OC4Me] and neural net [NN]) used in the calculation of chlorophyll-a (Chl-a) from the Sentinel-3 Ocean and Land Colour Instrument (OLCI) compared to in situ measurements covering the Mediterranean Sea. In situ data set, obtained from the Copernicus Marine Environmental Monitoring Service (CMEMS) and more specifically from the data set with the title INSITU_MED_NRT_OBSERVATIONS_013_035, and Chl-a values at different depths were extracted. The concentration of Chl-a at a penetration depth was calculated. Then, water was classified into two categories, Case-1 and Case-2. For Case-2 waters, the OC4Me presents a moderate correlation with the in situ data for a time window of 0–2 h. In contrast with the NN algorithm, where very weak correlations were calculated, lower values of the statistical index of Bias for Case-1 waters were calculated for the OC4Me algorithm. Higher values of Pearson correlation were calculated (r > 0.5) for OC4Me algorithm than NN. OC4Me performed better than NN.
format	article
author	Moutzouris-Sidiris Ioannis Topouzelis Konstantinos
author_facet	Moutzouris-Sidiris Ioannis Topouzelis Konstantinos
author_sort	Moutzouris-Sidiris Ioannis
title	Assessment of Chlorophyll-a concentration from Sentinel-3 satellite images at the Mediterranean Sea using CMEMS open source in situ data
title_short	Assessment of Chlorophyll-a concentration from Sentinel-3 satellite images at the Mediterranean Sea using CMEMS open source in situ data
title_full	Assessment of Chlorophyll-a concentration from Sentinel-3 satellite images at the Mediterranean Sea using CMEMS open source in situ data
title_fullStr	Assessment of Chlorophyll-a concentration from Sentinel-3 satellite images at the Mediterranean Sea using CMEMS open source in situ data
title_full_unstemmed	Assessment of Chlorophyll-a concentration from Sentinel-3 satellite images at the Mediterranean Sea using CMEMS open source in situ data
title_sort	assessment of chlorophyll-a concentration from sentinel-3 satellite images at the mediterranean sea using cmems open source in situ data
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/aa889d89f4974cfb94990e4b6cd82009
work_keys_str_mv	AT moutzourissidirisioannis assessmentofchlorophyllaconcentrationfromsentinel3satelliteimagesatthemediterraneanseausingcmemsopensourceinsitudata AT topouzeliskonstantinos assessmentofchlorophyllaconcentrationfromsentinel3satelliteimagesatthemediterraneanseausingcmemsopensourceinsitudata
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Assessment of Chlorophyll-a concentration from Sentinel-3 satellite images at the Mediterranean Sea using CMEMS open source in situ data

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