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Spatio-Temporal Variability of Phytoplankton Functional Types in Alboran Sea from Remote Sensing Images
During the last two decades, several satellite algorithms have been proposed to retrieve information about phytoplankton groups using ocean color data. One of these algorithms, the so-called PHYSAT -Med, has been developed specifically for the Mediterranean Sea due to the optical peculiarities of th...
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creator | Navarro, Gabriel Almaraz, Pablo Caballero, Isabel Vazquez, Agueda Huertas, y I. Emma |
description | During the last two decades, several satellite algorithms have been proposed to retrieve information about phytoplankton groups using ocean color data. One of these algorithms, the so-called PHYSAT -Med, has been developed specifically for the Mediterranean Sea due to the optical peculiarities of this basin. The method allows detection from ocean color images of phytoplankton groups, such as nanoeukaryotes, Prochlorococcus, Synechococcus and diatoms. In this work, the PHYSAT-Med updated version has been used to analyze the annual cycles of major phytoplankton groups in the Alboran Sea and extract periodic components of variability using wavelet analysis. According to the PHYSAT - Med OC-CCI outputs, the algorithm represents a useful tool for the spatio-temporal monitoring of dominant phytoplankton groups in Alboran Sea. |
doi_str_mv | 10.1109/IGARSS.2018.8517869 |
format | conference_proceeding |
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Emma</creator><creatorcontrib>Navarro, Gabriel ; Almaraz, Pablo ; Caballero, Isabel ; Vazquez, Agueda ; Huertas, y I. Emma</creatorcontrib><description>During the last two decades, several satellite algorithms have been proposed to retrieve information about phytoplankton groups using ocean color data. One of these algorithms, the so-called PHYSAT -Med, has been developed specifically for the Mediterranean Sea due to the optical peculiarities of this basin. The method allows detection from ocean color images of phytoplankton groups, such as nanoeukaryotes, Prochlorococcus, Synechococcus and diatoms. In this work, the PHYSAT-Med updated version has been used to analyze the annual cycles of major phytoplankton groups in the Alboran Sea and extract periodic components of variability using wavelet analysis. According to the PHYSAT - Med OC-CCI outputs, the algorithm represents a useful tool for the spatio-temporal monitoring of dominant phytoplankton groups in Alboran Sea.</description><identifier>EISSN: 2153-7003</identifier><identifier>EISBN: 9781538671504</identifier><identifier>EISBN: 1538671506</identifier><identifier>DOI: 10.1109/IGARSS.2018.8517869</identifier><language>eng</language><publisher>IEEE</publisher><subject>Alboran Sea ; Image color analysis ; OC-CCI database ; Oceans ; PHYSAT-Med algorithm ; Phytoplankton functional types ; Remote sensing ; Satellites ; Sensors ; Time series analysis ; Wavelet analysis</subject><ispartof>IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium, 2018, p.963-966</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/8517869$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,27925,54555,54932</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/8517869$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Navarro, Gabriel</creatorcontrib><creatorcontrib>Almaraz, Pablo</creatorcontrib><creatorcontrib>Caballero, Isabel</creatorcontrib><creatorcontrib>Vazquez, Agueda</creatorcontrib><creatorcontrib>Huertas, y I. Emma</creatorcontrib><title>Spatio-Temporal Variability of Phytoplankton Functional Types in Alboran Sea from Remote Sensing Images</title><title>IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium</title><addtitle>IGARSS</addtitle><description>During the last two decades, several satellite algorithms have been proposed to retrieve information about phytoplankton groups using ocean color data. One of these algorithms, the so-called PHYSAT -Med, has been developed specifically for the Mediterranean Sea due to the optical peculiarities of this basin. The method allows detection from ocean color images of phytoplankton groups, such as nanoeukaryotes, Prochlorococcus, Synechococcus and diatoms. In this work, the PHYSAT-Med updated version has been used to analyze the annual cycles of major phytoplankton groups in the Alboran Sea and extract periodic components of variability using wavelet analysis. According to the PHYSAT - Med OC-CCI outputs, the algorithm represents a useful tool for the spatio-temporal monitoring of dominant phytoplankton groups in Alboran Sea.</description><subject>Alboran Sea</subject><subject>Image color analysis</subject><subject>OC-CCI database</subject><subject>Oceans</subject><subject>PHYSAT-Med algorithm</subject><subject>Phytoplankton functional types</subject><subject>Remote sensing</subject><subject>Satellites</subject><subject>Sensors</subject><subject>Time series analysis</subject><subject>Wavelet analysis</subject><issn>2153-7003</issn><isbn>9781538671504</isbn><isbn>1538671506</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2018</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotkEFOwzAURA0SEqX0BN34Ain-cRzby6qiJVIlUFPYVnb6XQyJHSVhkdsTqV3NjPRmFkPIEtgKgOmXYrc-lOUqZaBWSoBUub4jCy0VCK5yCYJl92SWTimRjPFH8tT3P5NRKWMzcilbM_iYHLFpY2dq-mU6b6yv_TDS6OjH9zjEtjbhd4iBbv9CNdFh4o5jiz31ga5rOxUDLdFQ18WGHrCJA0459D5caNGYC_bP5MGZusfFTefkc_t63Lwl-_ddsVnvEw9SDIlwIPkZrdaycozz6mwVKokoQORaulSoHKVUxvHMgKi0PVsJmRNOZhYr4HOyvO56RDy1nW9MN55uv_B_MpRZIw</recordid><startdate>201807</startdate><enddate>201807</enddate><creator>Navarro, Gabriel</creator><creator>Almaraz, Pablo</creator><creator>Caballero, Isabel</creator><creator>Vazquez, Agueda</creator><creator>Huertas, y I. Emma</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201807</creationdate><title>Spatio-Temporal Variability of Phytoplankton Functional Types in Alboran Sea from Remote Sensing Images</title><author>Navarro, Gabriel ; Almaraz, Pablo ; Caballero, Isabel ; Vazquez, Agueda ; Huertas, y I. 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Emma</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE/IET Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Navarro, Gabriel</au><au>Almaraz, Pablo</au><au>Caballero, Isabel</au><au>Vazquez, Agueda</au><au>Huertas, y I. Emma</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Spatio-Temporal Variability of Phytoplankton Functional Types in Alboran Sea from Remote Sensing Images</atitle><btitle>IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium</btitle><stitle>IGARSS</stitle><date>2018-07</date><risdate>2018</risdate><spage>963</spage><epage>966</epage><pages>963-966</pages><eissn>2153-7003</eissn><eisbn>9781538671504</eisbn><eisbn>1538671506</eisbn><abstract>During the last two decades, several satellite algorithms have been proposed to retrieve information about phytoplankton groups using ocean color data. One of these algorithms, the so-called PHYSAT -Med, has been developed specifically for the Mediterranean Sea due to the optical peculiarities of this basin. The method allows detection from ocean color images of phytoplankton groups, such as nanoeukaryotes, Prochlorococcus, Synechococcus and diatoms. In this work, the PHYSAT-Med updated version has been used to analyze the annual cycles of major phytoplankton groups in the Alboran Sea and extract periodic components of variability using wavelet analysis. According to the PHYSAT - Med OC-CCI outputs, the algorithm represents a useful tool for the spatio-temporal monitoring of dominant phytoplankton groups in Alboran Sea.</abstract><pub>IEEE</pub><doi>10.1109/IGARSS.2018.8517869</doi><tpages>4</tpages></addata></record> |
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subjects | Alboran Sea Image color analysis OC-CCI database Oceans PHYSAT-Med algorithm Phytoplankton functional types Remote sensing Satellites Sensors Time series analysis Wavelet analysis |
title | Spatio-Temporal Variability of Phytoplankton Functional Types in Alboran Sea from Remote Sensing Images |
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