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A Depolarization Ratio Anomaly Detector to identify icebergs in sea ice using dual-polarization SAR images

Marino, Armando; Dierking, Wolfgang and Christine, Wesche (2016). A Depolarization Ratio Anomaly Detector to identify icebergs in sea ice using dual-polarization SAR images. IEEE Transactions on Geoscience and Remote Sensing, 54(9) pp. 5602–5615.

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DOI (Digital Object Identifier) Link: https://doi.org/10.1109/TGRS.2016.2569450
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Abstract

Icebergs represent hazards to maritime traffic and offshore operations. Satellite Synthetic Aperture Radar (SAR) is very valuable for the observation of polar regions and extensive work was already carried out on detection and tracking of large icebergs. However, the identification of small icebergs is still challenging especially when these are embedded in sea ice. In this work, a new detector is proposed based on incoherent dual-polarization SAR images. The algorithm considers the limited extension of small icebergs, which are supposed to have a stronger cross polarization and higher cross- over co-polarization ratio compared to the surrounding sea or sea ice background.

The new detector is tested with two satellite systems. Firstly, RADARSAT-2 quad-polarimetric images are analyzed to evaluate the effects of high resolution data. Subsequently a more exhaustive analysis is carried out using dual-polarization ground detected Sentinel-1a Extra Wide swath images acquired over the time span of two months. The test areas are on the East Coast of Greenland, where several icebergs have been observed. A quantitative analysis and a comparison with a detector using only the cross polarization channel is carried out exploiting grounded icebergs as test targets. The proposed methodology improves the contrast between icebergs and sea ice clutter by up to 75 times. This returns an improved probability of detection.

Item Type: Journal Item
Copyright Holders: 2016 IEEE
ISSN: 0196-2892
Keywords: Arctic; iceberg detection; polarimetry; synthetic aperture radar (SAR)
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Engineering and Innovation
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Item ID: 46729
Depositing User: Armando Marino
Date Deposited: 28 Jun 2016 12:28
Last Modified: 28 Apr 2017 20:12
URI: http://oro.open.ac.uk/id/eprint/46729
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