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Analyzing lead information from SAR images
Van Dyne, Michele M. Tsatsoulis, Costas Fetterer, Florence
Van Dyne, Michele M.
Tsatsoulis, Costas
Fetterer, Florence
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Abstract
Leads are relatively linear features in the sea ice cover, which are composed of open water or new, thin ice, Because of their composition, leads impact the ocean/air heat exchange, Automated analysis of leads from sea ice imagery may provide a means of gathering important information about the sea ice cover and its climatic influence, This paper describes: 1) a method for extracting and analyzing leads from ERS-1 synthetic aperture radar (SAR) images classified by ice type and 2) the results of using this method on images of the Beaufort Sea, The methodology consists of identifying potential lead features in the image and measuring their characteristics both before and after using a thinning or skeletonization technique on the features. The measurements obtained using this method include lead area, average width, number of leads in an area, amount of branching, and linearity of the lead, These measurements were analyzed with respect to the time of year and the latitude of the images. Results indicate that the measurements produced by the methodology are consistent with lead measurement distributions that others have found, The results of the study suggest that the methodology is appropriate to study lead characteristics on a large scale.
Description
©1998 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Date
1998-03
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IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
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Keywords
Beaufort sea, Image analysis, Image processing, Leads, Lead statistics, SAR, Sea ice
Citation
Van Dyne, MM; Tsatsoulis, C; Fetterer, F. Analyzing lead information from SAR images. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING. March 1998. 36(2) : 647-660.