Near Real Time Delivery of Sea Ice Information Retrieved from Spaceborne Synthetic Aperture Radar
Sea ice is subject to constant change. Within just a few hours the wind can turn, shoving sea ice together over kilometres and causing pressure ridges to form – obstacles that are difficult or impossible even for icebreakers to overcome. Synthetic Aperture Radar (SAR) satellites are able to observe...
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ftdlr:oai:elib.dlr.de:198424 2024-05-19T07:48:09+00:00 Near Real Time Delivery of Sea Ice Information Retrieved from Spaceborne Synthetic Aperture Radar Frost, Anja Murashkin, Dmitrii Kortum, Karl Bathmann, Martin Wiehle, Stefan Voinov, Sergey Krause, Detmar Schwarz, Egbert 2023-09-26 application/pdf https://elib.dlr.de/198424/ https://elib.dlr.de/198424/1/IICWG2023-A_Frost__DLR__SAR_derived_sea_ice_information.pdf https://nsidc.org/noaa/iicwg/iicwg-meetings en eng https://elib.dlr.de/198424/1/IICWG2023-A_Frost__DLR__SAR_derived_sea_ice_information.pdf Frost, Anja und Murashkin, Dmitrii und Kortum, Karl und Bathmann, Martin und Wiehle, Stefan und Voinov, Sergey und Krause, Detmar und Schwarz, Egbert (2023) Near Real Time Delivery of Sea Ice Information Retrieved from Spaceborne Synthetic Aperture Radar. IICWG-XXIV: 24th International Ice Charting Working Group Meeting, 2023-09-25 - 2023-09-29, Cambridge, United Kingdom. SAR-Signalverarbeitung Nationales Bodensegment Konferenzbeitrag NonPeerReviewed 2023 ftdlr 2024-04-25T01:09:13Z Sea ice is subject to constant change. Within just a few hours the wind can turn, shoving sea ice together over kilometres and causing pressure ridges to form – obstacles that are difficult or impossible even for icebreakers to overcome. Synthetic Aperture Radar (SAR) satellites are able to observe small- and large-scale structures in sea ice – in any weather, through clouds and darkness. In this contribution, we show new algorithms that aim at retrieving sea ice information from SAR data in particular information on high resolution sea ice drift and sea ice classes. The sea ice drift retrieval is based on the well-known phase correlation technique executed on subsequent, co-located SAR acquisitions. The sea ice classification utilizes a convolutional neural network and - by exploiting the different polarizations - differentiates multiyear ice, first-year ice, new ice, open leads, and rough ice. In a new study, both algorithms are interlinked to perform multi-temporal sea ice classification using a stack of drift-compensated SAR acquisitions (instead of just a single acquisition). The multi-temporal approach is intended to reduce misclassifications and improve reliability of the output. The developed algorithms are foreseen to be integrated into the operational data processing chain at DLR ground station network sites in order to provide sea ice information to maritime users in near real-time (NRT). Conference Object Sea ice German Aerospace Center: elib - DLR electronic library |
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Open Polar |
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German Aerospace Center: elib - DLR electronic library |
op_collection_id |
ftdlr |
language |
English |
topic |
SAR-Signalverarbeitung Nationales Bodensegment |
spellingShingle |
SAR-Signalverarbeitung Nationales Bodensegment Frost, Anja Murashkin, Dmitrii Kortum, Karl Bathmann, Martin Wiehle, Stefan Voinov, Sergey Krause, Detmar Schwarz, Egbert Near Real Time Delivery of Sea Ice Information Retrieved from Spaceborne Synthetic Aperture Radar |
topic_facet |
SAR-Signalverarbeitung Nationales Bodensegment |
description |
Sea ice is subject to constant change. Within just a few hours the wind can turn, shoving sea ice together over kilometres and causing pressure ridges to form – obstacles that are difficult or impossible even for icebreakers to overcome. Synthetic Aperture Radar (SAR) satellites are able to observe small- and large-scale structures in sea ice – in any weather, through clouds and darkness. In this contribution, we show new algorithms that aim at retrieving sea ice information from SAR data in particular information on high resolution sea ice drift and sea ice classes. The sea ice drift retrieval is based on the well-known phase correlation technique executed on subsequent, co-located SAR acquisitions. The sea ice classification utilizes a convolutional neural network and - by exploiting the different polarizations - differentiates multiyear ice, first-year ice, new ice, open leads, and rough ice. In a new study, both algorithms are interlinked to perform multi-temporal sea ice classification using a stack of drift-compensated SAR acquisitions (instead of just a single acquisition). The multi-temporal approach is intended to reduce misclassifications and improve reliability of the output. The developed algorithms are foreseen to be integrated into the operational data processing chain at DLR ground station network sites in order to provide sea ice information to maritime users in near real-time (NRT). |
format |
Conference Object |
author |
Frost, Anja Murashkin, Dmitrii Kortum, Karl Bathmann, Martin Wiehle, Stefan Voinov, Sergey Krause, Detmar Schwarz, Egbert |
author_facet |
Frost, Anja Murashkin, Dmitrii Kortum, Karl Bathmann, Martin Wiehle, Stefan Voinov, Sergey Krause, Detmar Schwarz, Egbert |
author_sort |
Frost, Anja |
title |
Near Real Time Delivery of Sea Ice Information Retrieved from Spaceborne Synthetic Aperture Radar |
title_short |
Near Real Time Delivery of Sea Ice Information Retrieved from Spaceborne Synthetic Aperture Radar |
title_full |
Near Real Time Delivery of Sea Ice Information Retrieved from Spaceborne Synthetic Aperture Radar |
title_fullStr |
Near Real Time Delivery of Sea Ice Information Retrieved from Spaceborne Synthetic Aperture Radar |
title_full_unstemmed |
Near Real Time Delivery of Sea Ice Information Retrieved from Spaceborne Synthetic Aperture Radar |
title_sort |
near real time delivery of sea ice information retrieved from spaceborne synthetic aperture radar |
publishDate |
2023 |
url |
https://elib.dlr.de/198424/ https://elib.dlr.de/198424/1/IICWG2023-A_Frost__DLR__SAR_derived_sea_ice_information.pdf https://nsidc.org/noaa/iicwg/iicwg-meetings |
genre |
Sea ice |
genre_facet |
Sea ice |
op_relation |
https://elib.dlr.de/198424/1/IICWG2023-A_Frost__DLR__SAR_derived_sea_ice_information.pdf Frost, Anja und Murashkin, Dmitrii und Kortum, Karl und Bathmann, Martin und Wiehle, Stefan und Voinov, Sergey und Krause, Detmar und Schwarz, Egbert (2023) Near Real Time Delivery of Sea Ice Information Retrieved from Spaceborne Synthetic Aperture Radar. IICWG-XXIV: 24th International Ice Charting Working Group Meeting, 2023-09-25 - 2023-09-29, Cambridge, United Kingdom. |
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1799488669296361472 |