Active/Passive Multiple Polarization Sea Ice Detection During Initial Freeze-Up
An algorithm for ice/water detection of ice less than 30 cm in thickness (thin ice) using dual-polarized synthetic aperture radar (SAR) and passive microwave data has been developed based on insights from previous work. The frequency chosen from those available was in the C-band. For the radiometer...
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| Veröffentlicht in: | IEEE transactions on geoscience and remote sensing 2021-07, Vol.59 (7), p.5434-5448 |
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| creator | Keller, Mary R. Gifford, Christopher M. Winstead, Nathaniel S. Walton, William C. Dietz, Jerrold E. |
| description | An algorithm for ice/water detection of ice less than 30 cm in thickness (thin ice) using dual-polarized synthetic aperture radar (SAR) and passive microwave data has been developed based on insights from previous work. The frequency chosen from those available was in the C-band. For the radiometer layer ice concentrations, land contaminated pixels were removed. For the SAR layers, a novel approach to their use in ice detection was developed using the coefficient of variation (COV), defined as the ratio of the standard deviation of the normalized radar cross section, \sigma _{0} , to the mean \sigma _{0} . The COV reduced the complicated signatures of breaking waves and thin ice to bright ice pixels on a dark water background. The co-pol and cross-pol COV layers and the radiometer layer were merged according to physics-based rules, except in regions adjacent to land or the ice edge where only the SAR layers were valid. The detection algorithm was applied to 233 Sentinel 1a and 1b dual-polarization images of the freeze-up from 2015, 2016, 2018, and 2019 in the Beaufort and Chukchi Seas. The synergistic ice retrievals showed improved agreement with manual operational analyses in the marginal ice zone over other automated operational products. |
| doi_str_mv | 10.1109/TGRS.2020.3013512 |
| format | Article |
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The frequency chosen from those available was in the C-band. For the radiometer layer ice concentrations, land contaminated pixels were removed. For the SAR layers, a novel approach to their use in ice detection was developed using the coefficient of variation (COV), defined as the ratio of the standard deviation of the normalized radar cross section, <inline-formula> <tex-math notation="LaTeX">\sigma _{0} </tex-math></inline-formula>, to the mean <inline-formula> <tex-math notation="LaTeX">\sigma _{0} </tex-math></inline-formula>. The COV reduced the complicated signatures of breaking waves and thin ice to bright ice pixels on a dark water background. The co-pol and cross-pol COV layers and the radiometer layer were merged according to physics-based rules, except in regions adjacent to land or the ice edge where only the SAR layers were valid. The detection algorithm was applied to 233 Sentinel 1a and 1b dual-polarization images of the freeze-up from 2015, 2016, 2018, and 2019 in the Beaufort and Chukchi Seas. The synergistic ice retrievals showed improved agreement with manual operational analyses in the marginal ice zone over other automated operational products.]]></description><identifier>ISSN: 0196-2892</identifier><identifier>EISSN: 1558-0644</identifier><identifier>DOI: 10.1109/TGRS.2020.3013512</identifier><identifier>CODEN: IGRSD2</identifier><language>eng</language><publisher>New York: IEEE</publisher><subject>Algorithms ; Breaking waves ; C band ; Coefficient of variation ; Detection ; Dual polarization radar ; Ice cover ; Ice edge ; Land pollution ; Microwave FET integrated circuits ; Microwave integrated circuits ; Microwave radiometry ; Microwave theory and techniques ; passive microwave remote sensing ; Physics ; Pixels ; Polarization ; Radar ; Radar cross sections ; radar remote sensing ; Radiometers ; SAR (radar) ; Sea ice ; Sentinel-1 ; Synthetic aperture radar ; synthetic aperture radar (SAR)</subject><ispartof>IEEE transactions on geoscience and remote sensing, 2021-07, Vol.59 (7), p.5434-5448</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c293t-91de56121d6350d3572dbae15b9a749cd4628289cf32d419c4106228cf8107483</citedby><cites>FETCH-LOGICAL-c293t-91de56121d6350d3572dbae15b9a749cd4628289cf32d419c4106228cf8107483</cites><orcidid>0000-0003-0669-1298 ; 0000-0001-8060-3300 ; 0000-0002-7323-6538 ; 0000-0002-3848-6267</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9166518$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,796,27924,27925,54758</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/9166518$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Keller, Mary R.</creatorcontrib><creatorcontrib>Gifford, Christopher M.</creatorcontrib><creatorcontrib>Winstead, Nathaniel S.</creatorcontrib><creatorcontrib>Walton, William C.</creatorcontrib><creatorcontrib>Dietz, Jerrold E.</creatorcontrib><title>Active/Passive Multiple Polarization Sea Ice Detection During Initial Freeze-Up</title><title>IEEE transactions on geoscience and remote sensing</title><addtitle>TGRS</addtitle><description><![CDATA[An algorithm for ice/water detection of ice less than 30 cm in thickness (thin ice) using dual-polarized synthetic aperture radar (SAR) and passive microwave data has been developed based on insights from previous work. The frequency chosen from those available was in the C-band. For the radiometer layer ice concentrations, land contaminated pixels were removed. For the SAR layers, a novel approach to their use in ice detection was developed using the coefficient of variation (COV), defined as the ratio of the standard deviation of the normalized radar cross section, <inline-formula> <tex-math notation="LaTeX">\sigma _{0} </tex-math></inline-formula>, to the mean <inline-formula> <tex-math notation="LaTeX">\sigma _{0} </tex-math></inline-formula>. The COV reduced the complicated signatures of breaking waves and thin ice to bright ice pixels on a dark water background. The co-pol and cross-pol COV layers and the radiometer layer were merged according to physics-based rules, except in regions adjacent to land or the ice edge where only the SAR layers were valid. The detection algorithm was applied to 233 Sentinel 1a and 1b dual-polarization images of the freeze-up from 2015, 2016, 2018, and 2019 in the Beaufort and Chukchi Seas. The synergistic ice retrievals showed improved agreement with manual operational analyses in the marginal ice zone over other automated operational products.]]></description><subject>Algorithms</subject><subject>Breaking waves</subject><subject>C band</subject><subject>Coefficient of variation</subject><subject>Detection</subject><subject>Dual polarization radar</subject><subject>Ice cover</subject><subject>Ice edge</subject><subject>Land pollution</subject><subject>Microwave FET integrated circuits</subject><subject>Microwave integrated circuits</subject><subject>Microwave radiometry</subject><subject>Microwave theory and techniques</subject><subject>passive microwave remote sensing</subject><subject>Physics</subject><subject>Pixels</subject><subject>Polarization</subject><subject>Radar</subject><subject>Radar cross sections</subject><subject>radar remote sensing</subject><subject>Radiometers</subject><subject>SAR (radar)</subject><subject>Sea ice</subject><subject>Sentinel-1</subject><subject>Synthetic aperture radar</subject><subject>synthetic aperture radar (SAR)</subject><issn>0196-2892</issn><issn>1558-0644</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><recordid>eNo9kE1PwkAQhjdGExH9AcZLE8-Fnf1q90hAkAQDEThvlu3ULKlt3RYT-fUWIZ7eZPK8M5OHkEegAwCqh5vZ-3rAKKMDToFLYFekB1KmMVVCXJMeBa1ilmp2S-6aZk8pCAlJjyxHrvXfOFzZpukyejsUra8LjFZVYYM_2tZXZbRGG80dRhNs0f1NJofgy49oXvrW2yKaBsQjxtv6ntzktmjw4ZJ9sp2-bMav8WI5m49Hi9gxzdtYQ4ZSAYNMcUkzLhOW7SyC3GmbCO0yoVjavetyzjIB2gmgirHU5SnQRKS8T57Pe-tQfR2wac2-OoSyO2mYFILphDPVUXCmXKiaJmBu6uA_bfgxQM3Jmzl5Mydv5uKt6zydOx4R_3kNSklI-S-PPWdz</recordid><startdate>20210701</startdate><enddate>20210701</enddate><creator>Keller, Mary R.</creator><creator>Gifford, Christopher M.</creator><creator>Winstead, Nathaniel S.</creator><creator>Walton, William C.</creator><creator>Dietz, Jerrold E.</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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The frequency chosen from those available was in the C-band. For the radiometer layer ice concentrations, land contaminated pixels were removed. For the SAR layers, a novel approach to their use in ice detection was developed using the coefficient of variation (COV), defined as the ratio of the standard deviation of the normalized radar cross section, <inline-formula> <tex-math notation="LaTeX">\sigma _{0} </tex-math></inline-formula>, to the mean <inline-formula> <tex-math notation="LaTeX">\sigma _{0} </tex-math></inline-formula>. The COV reduced the complicated signatures of breaking waves and thin ice to bright ice pixels on a dark water background. The co-pol and cross-pol COV layers and the radiometer layer were merged according to physics-based rules, except in regions adjacent to land or the ice edge where only the SAR layers were valid. The detection algorithm was applied to 233 Sentinel 1a and 1b dual-polarization images of the freeze-up from 2015, 2016, 2018, and 2019 in the Beaufort and Chukchi Seas. The synergistic ice retrievals showed improved agreement with manual operational analyses in the marginal ice zone over other automated operational products.]]></abstract><cop>New York</cop><pub>IEEE</pub><doi>10.1109/TGRS.2020.3013512</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0003-0669-1298</orcidid><orcidid>https://orcid.org/0000-0001-8060-3300</orcidid><orcidid>https://orcid.org/0000-0002-7323-6538</orcidid><orcidid>https://orcid.org/0000-0002-3848-6267</orcidid></addata></record> |
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| subjects | Algorithms Breaking waves C band Coefficient of variation Detection Dual polarization radar Ice cover Ice edge Land pollution Microwave FET integrated circuits Microwave integrated circuits Microwave radiometry Microwave theory and techniques passive microwave remote sensing Physics Pixels Polarization Radar Radar cross sections radar remote sensing Radiometers SAR (radar) Sea ice Sentinel-1 Synthetic aperture radar synthetic aperture radar (SAR) |
| title | Active/Passive Multiple Polarization Sea Ice Detection During Initial Freeze-Up |
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