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Extensions of linear discriminant analysis for statistical classification of remotely sensed satellite imagery. Technical report No. 30 [electronic resource].

Published
Oak Ridge, Tenn. : Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 1979.
Physical Description
Pages: 20 : digital, PDF file
Additional Creators
United States. Department of Energy. Office of Scientific and Technical Information
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Summary
Linear discriminant analysis is a commonly used statistical tool for classification of surface features using satellite surface reflectance data. Extensions of this basic tool promise substantial improvements. In particular, the added effectiveness of integration of spatial autocorrelation into the discriminant model, resolution of nonhomogeneous pixels, and data based prior probability estimates of class membership, and the use of unclassified pixels as part of the discriminant function training set are examined.
Report Numbers
E 1.99:doe/ey/22874-64
doe/ey/22874-64
Subject(s)
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Note
Published through SciTech Connect.
11/01/1979.
"doe/ey/22874-64"
Switzer, P.
Stanford Univ., CA (USA)
Funding Information
EY-76-S-02-2874
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