Detection of macroalgae blooms by complex SAR imagery
•Complex SAR imagery enables better recognition of macroalgae patches.•Combination of different information in SAR matrix forms new index factors.•Proposed index factors contribute to unsupervised recognition of macroalgae. Increased frequency and enhanced damage to the marine environment and to hum...
Gespeichert in:
| Veröffentlicht in: | Marine pollution bulletin 2014-01, Vol.78 (1-2), p.190-195 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 195 |
|---|---|
| container_issue | 1-2 |
| container_start_page | 190 |
| container_title | Marine pollution bulletin |
| container_volume | 78 |
| creator | Shen, Hui Perrie, William Liu, Qingrong He, Yijun |
| description | •Complex SAR imagery enables better recognition of macroalgae patches.•Combination of different information in SAR matrix forms new index factors.•Proposed index factors contribute to unsupervised recognition of macroalgae.
Increased frequency and enhanced damage to the marine environment and to human society caused by green macroalgae blooms demand improved high-resolution early detection methods. Conventional satellite remote sensing methods via spectra radiometers do not work in cloud-covered areas, and therefore cannot meet these demands for operational applications. We present a methodology for green macroalgae bloom detection based on RADARSAT-2 synthetic aperture radar (SAR) images. Green macroalgae patches exhibit different polarimetric characteristics compared to the open ocean surface, in both the amplitude and phase domains of SAR-measured complex radar backscatter returns. In this study, new index factors are defined which have opposite signs in green macroalgae-covered areas, compared to the open water surface. These index factors enable unsupervised detection from SAR images, providing a high-resolution new tool for detection of green macroalgae blooms, which can potentially contribute to a better understanding of the mechanisms related to outbreaks of green macroalgae blooms in coastal areas throughout the world ocean. |
| doi_str_mv | 10.1016/j.marpolbul.2013.10.044 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1668254722</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0025326X13006656</els_id><sourcerecordid>1668254722</sourcerecordid><originalsourceid>FETCH-LOGICAL-c434t-23ee52c85305864048351418dfb09388ed94e77311a4f17690fc9183a764ebbd3</originalsourceid><addsrcrecordid>eNqFkctKAzEUhoMotlZfQWcjuJma6ySzLPUKBcELuAuZzJkyJdPUpBX79qa01mVXB3K-k5z_C0JXBA8JJsXtbNiZsPCuWrkhxYSl0yHm_Aj1iZJlzljBjlEfYypyRovPHjqLcYYxllSSU9SjnLKSYdVH4g6WYJetn2e-yTpjgzduaiCrnPddzKp1Zn23cPCTvY1es7YzUwjrc3TSGBfhYlcH6OPh_n38lE9eHp_Ho0luOePLnDIAQa0SDAtVcMwVE4QTVTcVLplSUJccpGSEGN4QWZS4sSVRzMiCQ1XVbIButvcugv9aQVzqro0WnDNz8KuoSVEoKrik9DDKSywlV2KDyi2awsYYoNGLkIKFtSZYb_Tqmd7r1Ru9m0bSmyYvd4-sqg7q_dyfzwRc7wATrXFNMHPbxn9O0TKxInGjLQfJ3ncLQUfbwtxC3Yb0Hbr27cFlfgGyrZof</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1490774852</pqid></control><display><type>article</type><title>Detection of macroalgae blooms by complex SAR imagery</title><source>MEDLINE</source><source>Elsevier ScienceDirect Journals Complete</source><creator>Shen, Hui ; Perrie, William ; Liu, Qingrong ; He, Yijun</creator><creatorcontrib>Shen, Hui ; Perrie, William ; Liu, Qingrong ; He, Yijun</creatorcontrib><description>•Complex SAR imagery enables better recognition of macroalgae patches.•Combination of different information in SAR matrix forms new index factors.•Proposed index factors contribute to unsupervised recognition of macroalgae.
Increased frequency and enhanced damage to the marine environment and to human society caused by green macroalgae blooms demand improved high-resolution early detection methods. Conventional satellite remote sensing methods via spectra radiometers do not work in cloud-covered areas, and therefore cannot meet these demands for operational applications. We present a methodology for green macroalgae bloom detection based on RADARSAT-2 synthetic aperture radar (SAR) images. Green macroalgae patches exhibit different polarimetric characteristics compared to the open ocean surface, in both the amplitude and phase domains of SAR-measured complex radar backscatter returns. In this study, new index factors are defined which have opposite signs in green macroalgae-covered areas, compared to the open water surface. These index factors enable unsupervised detection from SAR images, providing a high-resolution new tool for detection of green macroalgae blooms, which can potentially contribute to a better understanding of the mechanisms related to outbreaks of green macroalgae blooms in coastal areas throughout the world ocean.</description><identifier>ISSN: 0025-326X</identifier><identifier>EISSN: 1879-3363</identifier><identifier>DOI: 10.1016/j.marpolbul.2013.10.044</identifier><identifier>PMID: 24239308</identifier><identifier>CODEN: MPNBAZ</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Animal and plant ecology ; Animal, plant and microbial ecology ; Applied ecology ; Biological and medical sciences ; Ecotoxicology, biological effects of pollution ; Environmental Monitoring - methods ; Eutrophication ; Fundamental and applied biological sciences. Psychology ; Green macroalgae blooms ; High resolution early detection ; Marine and brackish environment ; Radar ; Remote Sensing Technology ; Satellite Imagery ; Sea water ecosystems ; Seaweed - growth & development ; Spacecraft ; Synecology ; Synthetic aperture radar (SAR) ; Unsupervised SAR index factor</subject><ispartof>Marine pollution bulletin, 2014-01, Vol.78 (1-2), p.190-195</ispartof><rights>2013</rights><rights>2015 INIST-CNRS</rights><rights>Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c434t-23ee52c85305864048351418dfb09388ed94e77311a4f17690fc9183a764ebbd3</citedby><cites>FETCH-LOGICAL-c434t-23ee52c85305864048351418dfb09388ed94e77311a4f17690fc9183a764ebbd3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.marpolbul.2013.10.044$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28292425$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24239308$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Shen, Hui</creatorcontrib><creatorcontrib>Perrie, William</creatorcontrib><creatorcontrib>Liu, Qingrong</creatorcontrib><creatorcontrib>He, Yijun</creatorcontrib><title>Detection of macroalgae blooms by complex SAR imagery</title><title>Marine pollution bulletin</title><addtitle>Mar Pollut Bull</addtitle><description>•Complex SAR imagery enables better recognition of macroalgae patches.•Combination of different information in SAR matrix forms new index factors.•Proposed index factors contribute to unsupervised recognition of macroalgae.
Increased frequency and enhanced damage to the marine environment and to human society caused by green macroalgae blooms demand improved high-resolution early detection methods. Conventional satellite remote sensing methods via spectra radiometers do not work in cloud-covered areas, and therefore cannot meet these demands for operational applications. We present a methodology for green macroalgae bloom detection based on RADARSAT-2 synthetic aperture radar (SAR) images. Green macroalgae patches exhibit different polarimetric characteristics compared to the open ocean surface, in both the amplitude and phase domains of SAR-measured complex radar backscatter returns. In this study, new index factors are defined which have opposite signs in green macroalgae-covered areas, compared to the open water surface. These index factors enable unsupervised detection from SAR images, providing a high-resolution new tool for detection of green macroalgae blooms, which can potentially contribute to a better understanding of the mechanisms related to outbreaks of green macroalgae blooms in coastal areas throughout the world ocean.</description><subject>Animal and plant ecology</subject><subject>Animal, plant and microbial ecology</subject><subject>Applied ecology</subject><subject>Biological and medical sciences</subject><subject>Ecotoxicology, biological effects of pollution</subject><subject>Environmental Monitoring - methods</subject><subject>Eutrophication</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Green macroalgae blooms</subject><subject>High resolution early detection</subject><subject>Marine and brackish environment</subject><subject>Radar</subject><subject>Remote Sensing Technology</subject><subject>Satellite Imagery</subject><subject>Sea water ecosystems</subject><subject>Seaweed - growth & development</subject><subject>Spacecraft</subject><subject>Synecology</subject><subject>Synthetic aperture radar (SAR)</subject><subject>Unsupervised SAR index factor</subject><issn>0025-326X</issn><issn>1879-3363</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkctKAzEUhoMotlZfQWcjuJma6ySzLPUKBcELuAuZzJkyJdPUpBX79qa01mVXB3K-k5z_C0JXBA8JJsXtbNiZsPCuWrkhxYSl0yHm_Aj1iZJlzljBjlEfYypyRovPHjqLcYYxllSSU9SjnLKSYdVH4g6WYJetn2e-yTpjgzduaiCrnPddzKp1Zn23cPCTvY1es7YzUwjrc3TSGBfhYlcH6OPh_n38lE9eHp_Ho0luOePLnDIAQa0SDAtVcMwVE4QTVTcVLplSUJccpGSEGN4QWZS4sSVRzMiCQ1XVbIButvcugv9aQVzqro0WnDNz8KuoSVEoKrik9DDKSywlV2KDyi2awsYYoNGLkIKFtSZYb_Tqmd7r1Ru9m0bSmyYvd4-sqg7q_dyfzwRc7wATrXFNMHPbxn9O0TKxInGjLQfJ3ncLQUfbwtxC3Yb0Hbr27cFlfgGyrZof</recordid><startdate>20140115</startdate><enddate>20140115</enddate><creator>Shen, Hui</creator><creator>Perrie, William</creator><creator>Liu, Qingrong</creator><creator>He, Yijun</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7ST</scope><scope>7TN</scope><scope>7TV</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H97</scope><scope>L.G</scope><scope>M7N</scope><scope>SOI</scope></search><sort><creationdate>20140115</creationdate><title>Detection of macroalgae blooms by complex SAR imagery</title><author>Shen, Hui ; Perrie, William ; Liu, Qingrong ; He, Yijun</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c434t-23ee52c85305864048351418dfb09388ed94e77311a4f17690fc9183a764ebbd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Animal and plant ecology</topic><topic>Animal, plant and microbial ecology</topic><topic>Applied ecology</topic><topic>Biological and medical sciences</topic><topic>Ecotoxicology, biological effects of pollution</topic><topic>Environmental Monitoring - methods</topic><topic>Eutrophication</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Green macroalgae blooms</topic><topic>High resolution early detection</topic><topic>Marine and brackish environment</topic><topic>Radar</topic><topic>Remote Sensing Technology</topic><topic>Satellite Imagery</topic><topic>Sea water ecosystems</topic><topic>Seaweed - growth & development</topic><topic>Spacecraft</topic><topic>Synecology</topic><topic>Synthetic aperture radar (SAR)</topic><topic>Unsupervised SAR index factor</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Shen, Hui</creatorcontrib><creatorcontrib>Perrie, William</creatorcontrib><creatorcontrib>Liu, Qingrong</creatorcontrib><creatorcontrib>He, Yijun</creatorcontrib><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Environment Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Pollution Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Environment Abstracts</collection><jtitle>Marine pollution bulletin</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Shen, Hui</au><au>Perrie, William</au><au>Liu, Qingrong</au><au>He, Yijun</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Detection of macroalgae blooms by complex SAR imagery</atitle><jtitle>Marine pollution bulletin</jtitle><addtitle>Mar Pollut Bull</addtitle><date>2014-01-15</date><risdate>2014</risdate><volume>78</volume><issue>1-2</issue><spage>190</spage><epage>195</epage><pages>190-195</pages><issn>0025-326X</issn><eissn>1879-3363</eissn><coden>MPNBAZ</coden><abstract>•Complex SAR imagery enables better recognition of macroalgae patches.•Combination of different information in SAR matrix forms new index factors.•Proposed index factors contribute to unsupervised recognition of macroalgae.
Increased frequency and enhanced damage to the marine environment and to human society caused by green macroalgae blooms demand improved high-resolution early detection methods. Conventional satellite remote sensing methods via spectra radiometers do not work in cloud-covered areas, and therefore cannot meet these demands for operational applications. We present a methodology for green macroalgae bloom detection based on RADARSAT-2 synthetic aperture radar (SAR) images. Green macroalgae patches exhibit different polarimetric characteristics compared to the open ocean surface, in both the amplitude and phase domains of SAR-measured complex radar backscatter returns. In this study, new index factors are defined which have opposite signs in green macroalgae-covered areas, compared to the open water surface. These index factors enable unsupervised detection from SAR images, providing a high-resolution new tool for detection of green macroalgae blooms, which can potentially contribute to a better understanding of the mechanisms related to outbreaks of green macroalgae blooms in coastal areas throughout the world ocean.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><pmid>24239308</pmid><doi>10.1016/j.marpolbul.2013.10.044</doi><tpages>6</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0025-326X |
| ispartof | Marine pollution bulletin, 2014-01, Vol.78 (1-2), p.190-195 |
| issn | 0025-326X 1879-3363 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1668254722 |
| source | MEDLINE; Elsevier ScienceDirect Journals Complete |
| subjects | Animal and plant ecology Animal, plant and microbial ecology Applied ecology Biological and medical sciences Ecotoxicology, biological effects of pollution Environmental Monitoring - methods Eutrophication Fundamental and applied biological sciences. Psychology Green macroalgae blooms High resolution early detection Marine and brackish environment Radar Remote Sensing Technology Satellite Imagery Sea water ecosystems Seaweed - growth & development Spacecraft Synecology Synthetic aperture radar (SAR) Unsupervised SAR index factor |
| title | Detection of macroalgae blooms by complex SAR imagery |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-29T03%3A27%3A07IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Detection%20of%20macroalgae%20blooms%20by%20complex%20SAR%20imagery&rft.jtitle=Marine%20pollution%20bulletin&rft.au=Shen,%20Hui&rft.date=2014-01-15&rft.volume=78&rft.issue=1-2&rft.spage=190&rft.epage=195&rft.pages=190-195&rft.issn=0025-326X&rft.eissn=1879-3363&rft.coden=MPNBAZ&rft_id=info:doi/10.1016/j.marpolbul.2013.10.044&rft_dat=%3Cproquest_cross%3E1668254722%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1490774852&rft_id=info:pmid/24239308&rft_els_id=S0025326X13006656&rfr_iscdi=true |