Ressel, Rudolf und Singha, Suman und Lehner, Susanne (2016) Neural Network based automatic Sea Ice Classification for CL-pol RISAT-1 Imagery. In: Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International, Seiten 4835-4838. IEEE Xplore. IGARSS 2016, 2016-07-10 - 2016-07-15, Peking, China. doi: 10.1109/IGARSS.2016.7730261. ISBN 978-1-5090-3332-4. ISSN 2153-7003.
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Offizielle URL: http://dx.doi.org/10.1109/IGARSS.2016.7730261
Kurzfassung
SAR Polarimetry has become a valuable tool in spaceborne SAR based sea ice analysis. The two major objectives in SAR based remote sensing of sea ice is on the one hand to have a large coverage of the imaged ground area, and on the other hand to obtain a radar response that carries as much Information as possible. Whereas single-polarimetric acquisitions of existing sensors offer a wide coverage on the ground, dual polarimetric, or even better fully polarimetric data offer a higher information content which allows for a more reliable automated sea ice analysis. In order to reconcile the advantages of fully polarimetric acquisitions with the higher ground coverage of acquisitions with fewer polarimetric channels, hybrid polarimetric acquisitions offer a trade-off between the mentioned objectives. With the advent of the RISAT-1 satellite platform, we are able to explore the potential of hybrid dual pol acquisitions for sea ice analysis and classification. Our algorithmic approach for an automated sea ice classificationconsists of two steps. In the first step, we perform a Feature etraction procedure. The resulting feature vectors are then ingested into a trained neural network classifier to arrive at a pixelwise supervised classification. We present first results on a dataset acquired off the eastern Greenland coast.
elib-URL des Eintrags: | https://elib.dlr.de/102298/ | ||||||||||||||||
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Dokumentart: | Konferenzbeitrag (Poster) | ||||||||||||||||
Titel: | Neural Network based automatic Sea Ice Classification for CL-pol RISAT-1 Imagery | ||||||||||||||||
Autoren: |
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Datum: | 3 November 2016 | ||||||||||||||||
Erschienen in: | Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International | ||||||||||||||||
Referierte Publikation: | Nein | ||||||||||||||||
Open Access: | Ja | ||||||||||||||||
Gold Open Access: | Nein | ||||||||||||||||
In SCOPUS: | Nein | ||||||||||||||||
In ISI Web of Science: | Nein | ||||||||||||||||
DOI: | 10.1109/IGARSS.2016.7730261 | ||||||||||||||||
Seitenbereich: | Seiten 4835-4838 | ||||||||||||||||
Herausgeber: |
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Verlag: | IEEE Xplore | ||||||||||||||||
ISSN: | 2153-7003 | ||||||||||||||||
ISBN: | 978-1-5090-3332-4 | ||||||||||||||||
Status: | veröffentlicht | ||||||||||||||||
Stichwörter: | Sea Ice; Feature Extraction; SAR, Compact Pol; RISAT | ||||||||||||||||
Veranstaltungstitel: | IGARSS 2016 | ||||||||||||||||
Veranstaltungsort: | Peking, China | ||||||||||||||||
Veranstaltungsart: | internationale Konferenz | ||||||||||||||||
Veranstaltungsbeginn: | 10 Juli 2016 | ||||||||||||||||
Veranstaltungsende: | 15 Juli 2016 | ||||||||||||||||
Veranstalter : | IEEE | ||||||||||||||||
HGF - Forschungsbereich: | Luftfahrt, Raumfahrt und Verkehr | ||||||||||||||||
HGF - Programm: | Raumfahrt | ||||||||||||||||
HGF - Programmthema: | Erdbeobachtung | ||||||||||||||||
DLR - Schwerpunkt: | Raumfahrt | ||||||||||||||||
DLR - Forschungsgebiet: | R EO - Erdbeobachtung | ||||||||||||||||
DLR - Teilgebiet (Projekt, Vorhaben): | R - Vorhaben Entwicklung und Erprobung von Verfahren zur Gewässerfernerkundung (alt) | ||||||||||||||||
Standort: | Bremen , Oberpfaffenhofen | ||||||||||||||||
Institute & Einrichtungen: | Institut für Methodik der Fernerkundung Institut für Methodik der Fernerkundung > SAR-Signalverarbeitung | ||||||||||||||||
Hinterlegt von: | Kaps, Ruth | ||||||||||||||||
Hinterlegt am: | 22 Jan 2016 14:04 | ||||||||||||||||
Letzte Änderung: | 24 Apr 2024 20:08 |
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