Evaluating suitability of Pol-SAR (TerraSAR-X, Radarsat-2) for automated sea ice classification
Ressel R, Singha S, Lehner S (2016)
Publication Type: Conference contribution
Publication year: 2016
Publisher: SPIE
Book Volume: 9877
Conference Proceedings Title: Proceedings of SPIE - The International Society for Optical Engineering
Event location: New Delhi, IND
ISBN: 9781510601185
DOI: 10.1117/12.2223435
Abstract
Satellite borne SAR imagery has become an invaluable tool in the field of sea ice monitoring. Previously, single polarimetric imagery were employed in supervised and unsupervised classification schemes for sea ice investigation, which was preceded by image processing techniques such as segmentation and textural features. Recently, through the advent of polarimetric SAR sensors, investigation of polarimetric features in sea ice has attracted increased attention. While dual-polarimetric data has already been investigated in a number of works, full-polarimetric data has so far not been a major scientific focus. To explore the possibilities of full-polarimetric data and compare the differences in C-and X-bands, we endeavor to analyze in detail an array of datasets, simultaneously acquired, in C-band (RADARSAT-2) and X-band (TerraSAR-X) over ice infested areas. First, we propose an array of polarimetric features (Pauli and lexicographic based). Ancillary data from national ice services, SMOS data and expert judgement were utilized to identify the governing ice regimes. Based on these observations, we then extracted mentioned features. The subsequent supervised classification approach was based on an Artificial Neural Network (ANN). To gain quantitative insight into the quality of the features themselves (and reduce a possible impact of the Hughes phenomenon), we employed mutual information to unearth the relevance and redundancy of features. The results of this information theoretic analysis guided a pruning process regarding the optimal subset of features. In the last step we compared the classified results of all sensors and images, stated respective accuracies and discussed output discrepancies in the cases of simultaneous acquisitions.
Involved external institutions
Germany (DE)How to cite
APA:
Ressel, R., Singha, S., & Lehner, S. (2016). Evaluating suitability of Pol-SAR (TerraSAR-X, Radarsat-2) for automated sea ice classification. In Jing M. Chen, Ashwagosh Ganju, A. S. Rajawat, Reza Khanbilvardi (Eds.), Proceedings of SPIE - The International Society for Optical Engineering. New Delhi, IND: SPIE.
MLA:
Ressel, Rudolf, Suman Singha, and Susanne Lehner. "Evaluating suitability of Pol-SAR (TerraSAR-X, Radarsat-2) for automated sea ice classification." Proceedings of the Land Surface and Cryosphere Remote Sensing III, New Delhi, IND Ed. Jing M. Chen, Ashwagosh Ganju, A. S. Rajawat, Reza Khanbilvardi, SPIE, 2016.
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