Investigating the potential of different polarimetric features based on dual polarimetric TerraSAR-X data for automated sea ice classification
In this work, we examine the performance of an automated sea ice classification algorithm based on dual polarimetric TerraSAR-X data. Polarimetric features are extracted from HHVV dualpol stripmap images. In a second step, the feature vectors are fed into an artificial neural network to classify eac...
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ftdlr:oai:elib.dlr.de:95395 2024-05-19T07:48:19+00:00 Investigating the potential of different polarimetric features based on dual polarimetric TerraSAR-X data for automated sea ice classification Ressel, Rudolf Frost, Anja Lehner, Susanne Ouwehand, L. 2015-04 https://elib.dlr.de/95395/ http://www.spacebooks-online.com/product_info.php?cPath=104&products_id=17603 unknown ESA Communications Ressel, Rudolf und Frost, Anja und Lehner, Susanne (2015) Investigating the potential of different polarimetric features based on dual polarimetric TerraSAR-X data for automated sea ice classification. In: Proceedings of the POLINSAR 2015, SP-729, Seiten 1-6. ESA Communications. ESA POLinSAR 2015, 2015-01-26 - 2015-01-30, Frascati, Italien. ISBN 978-92-9221-293-3. ISSN 1609-042X. SAR-Signalverarbeitung Institut für Methodik der Fernerkundung Konferenzbeitrag NonPeerReviewed 2015 ftdlr 2024-04-25T00:33:07Z In this work, we examine the performance of an automated sea ice classification algorithm based on dual polarimetric TerraSAR-X data. Polarimetric features are extracted from HHVV dualpol stripmap images. In a second step, the feature vectors are fed into an artificial neural network to classify each pixel into an ice type. The first part of our analysis addresses the predictive value of different subsets of features for our classification process (by means of measuring mutual information). Different neural network configurations are then explored for optimal classification performance. The results on a TerraSAR-X dataset indicate a high reliability of a trained dual polarimetric classifier. Performance speed and accuracy promise applicability for near real time operational use. Conference Object Sea ice German Aerospace Center: elib - DLR electronic library |
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German Aerospace Center: elib - DLR electronic library |
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unknown |
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SAR-Signalverarbeitung Institut für Methodik der Fernerkundung |
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SAR-Signalverarbeitung Institut für Methodik der Fernerkundung Ressel, Rudolf Frost, Anja Lehner, Susanne Investigating the potential of different polarimetric features based on dual polarimetric TerraSAR-X data for automated sea ice classification |
topic_facet |
SAR-Signalverarbeitung Institut für Methodik der Fernerkundung |
description |
In this work, we examine the performance of an automated sea ice classification algorithm based on dual polarimetric TerraSAR-X data. Polarimetric features are extracted from HHVV dualpol stripmap images. In a second step, the feature vectors are fed into an artificial neural network to classify each pixel into an ice type. The first part of our analysis addresses the predictive value of different subsets of features for our classification process (by means of measuring mutual information). Different neural network configurations are then explored for optimal classification performance. The results on a TerraSAR-X dataset indicate a high reliability of a trained dual polarimetric classifier. Performance speed and accuracy promise applicability for near real time operational use. |
author2 |
Ouwehand, L. |
format |
Conference Object |
author |
Ressel, Rudolf Frost, Anja Lehner, Susanne |
author_facet |
Ressel, Rudolf Frost, Anja Lehner, Susanne |
author_sort |
Ressel, Rudolf |
title |
Investigating the potential of different polarimetric features based on dual polarimetric TerraSAR-X data for automated sea ice classification |
title_short |
Investigating the potential of different polarimetric features based on dual polarimetric TerraSAR-X data for automated sea ice classification |
title_full |
Investigating the potential of different polarimetric features based on dual polarimetric TerraSAR-X data for automated sea ice classification |
title_fullStr |
Investigating the potential of different polarimetric features based on dual polarimetric TerraSAR-X data for automated sea ice classification |
title_full_unstemmed |
Investigating the potential of different polarimetric features based on dual polarimetric TerraSAR-X data for automated sea ice classification |
title_sort |
investigating the potential of different polarimetric features based on dual polarimetric terrasar-x data for automated sea ice classification |
publisher |
ESA Communications |
publishDate |
2015 |
url |
https://elib.dlr.de/95395/ http://www.spacebooks-online.com/product_info.php?cPath=104&products_id=17603 |
genre |
Sea ice |
genre_facet |
Sea ice |
op_relation |
Ressel, Rudolf und Frost, Anja und Lehner, Susanne (2015) Investigating the potential of different polarimetric features based on dual polarimetric TerraSAR-X data for automated sea ice classification. In: Proceedings of the POLINSAR 2015, SP-729, Seiten 1-6. ESA Communications. ESA POLinSAR 2015, 2015-01-26 - 2015-01-30, Frascati, Italien. ISBN 978-92-9221-293-3. ISSN 1609-042X. |
_version_ |
1799488860677210112 |