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Unsupervised classification of scattering behavior using radar polarimetry dataThe use of an imaging radar polarimeter data for unsupervised classification of scattering behavior is described by comparing the polarization properties of each pixel in a image to that of simple classes of scattering such as even number of reflections, odd number of reflections, and diffuse scattering. For example, when this algorithm is applied to data acquired over the San Francisco Bay area in California, it classifies scattering by the ocean as being similar to that predicted by the class of odd number of reflections, scattering by the urban area as being similar to that predicted by the class of even number of reflections, and scattering by the Golden Gate Park as being similar to that predicted by the diffuse scattering class. It also classifies the scattering by a lighthouse in the ocean and boats on the ocean surface as being similar to that predicted by the even number of reflections class, making it easy to identify these objects against the background of the surrounding ocean. The algorithm is also applied to forested areas and shows that scattering from clear-cut areas and agricultural fields is mostly similar to that predicted by the odd number of reflections class, while the scattering from tree-covered areas generally is classified as being a mixture of pixels exhibiting the characteristics of all three classes, although each pixel is identified with only a single class.
Document ID
19890039472
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Van Zyl, Jakob J.
(California Institute of Technology Jet Propulsion Laboratory, Pasadena, United States)
Date Acquired
August 14, 2013
Publication Date
January 1, 1989
Publication Information
Publication: IEEE Transactions on Geoscience and Remote Sensing
Volume: 27
ISSN: 0196-2892
Subject Category
Communications And Radar
Accession Number
89A26843
Distribution Limits
Public
Copyright
Other

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