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Cold Regions Science and Technology
Volume 52, Issue 2, April 2008, Pages 207-223
Research in Cryospheric Science and Engineering
 
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doi:10.1016/j.coldregions.2007.06.006    
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Copyright © 2007 Elsevier B.V. All rights reserved.

High resolution (400 m) motion characterization of sea ice using ERS-1 SAR imagery

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M. Thomasa, E-mail The Corresponding Author,C.A. Geigerb, Corresponding Author Contact Information, E-mail The Corresponding Author and C. Kambhamettua, E-mail The Corresponding Author

aVideo/Image Modeling and Synthesis (VIMS) Lab, Computer and Information Science, University of Delaware, Newark, DE, USA

bCenter for Climatic Research, Department of Geography, University of Delaware, Newark, DE, USA


Received 16 November 2006; 
accepted 14 June 2007. 
Available online 30 June 2007.

Abstract

Using Synthetic Aperture Radar (SAR) images from ERS-1, we render high resolution motion fields of sea ice using a multi-resolution processing system. The results are provided at a 400 m resolution, which is an order of magnitude greater than the standard SAR motion products (5–10 km). An error propagation experiment shows a standard deviation of 1.3% day− 1 for the noise in invariant shear resulting from position uncertainties and processing techniques. We use this noise level to determine a significant lower threshold when identifying shear zone discontinuities. As example, a 24-day sequence of images is processed using this system to examine the development and evolution of a shear zone. This evolution is in response to the topographic steering caused by ocean circulation and wind forcing along a continental shelf break. In addition, we adapt the Line Integral Convolution (LIC) to depict flow patterns present in the motion field. Collectively, these motion products provide valuable descriptions of the non-rigid dynamics taking place within the sea ice. Our goal is to complement the existing RADARSAT Geophysical Processing System (RGPS) motion products and aid in the validation and further development of the most progressive “lead-resolving” sea ice models currently available. This form of sea ice visualization is important for understanding air–ice–sea momentum transfer processes that transcend through small-scale to large-scale fracture events with application to ship navigation.

Keywords: Sea ice; ERS-1 SAR; Buoys; Motion estimation; Discontinuity identification; Line integral convolution; Computer vision

Article Outline

1. Introduction
2. Data selection
3. Background: non-rigid motion analysis
3.1. Motion estimation theory
4. Implementation details
4.1. Preprocessing
4.2. Creation of a scaled hierarchy
4.3. Global motion estimation
4.4. Piece-wise local motion estimation
4.5. Local linear motion
5. Example illustration of non-rigid motion
5.1. Data uncertainty
6. Geophysical example
7. Visualization tools
8. Concluding remarks
Acknowledgements
References









Corresponding Author Contact InformationCorresponding author.

Cold Regions Science and Technology
Volume 52, Issue 2, April 2008, Pages 207-223
Research in Cryospheric Science and Engineering
 
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