Extensions of linear discriminant analysis for statistical classification of remotely sensed satellite imagery
作者： Paul Switzer
DOI: 10.1007/BF01029421
关键词:
摘要: Linear discriminant analysis is a commonly used statistical tool for the classification of surface features using satellite reflectance data. Extensions this basic promise substantial improvements. In particular, we examine added effectiveness integration spatial autocorrelation into model, resolution nonhomogeneous pixels, and data based prior probability estimates class membership.
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