Abstract #301685

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JSM 2002 Abstract #301685
Activity Number: 241
Type: Topic Contributed
Date/Time: Tuesday, August 13, 2002 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Computing*
Abstract - #301685
Title: A Comparison of Classification Methods for Large Imagery Data Sets
Author(s): James Shine*+ and Daniel Carr
Affiliation(s): George Mason University and George Mason University
Address: 4218 Alcott Street, Alexandria, Virginia, 22309, USA
Keywords: classification ; imagery ; multivariate
Abstract:

Classification is an important field with many applications. In particular, the classification of digital imagery has important applications in the mapping community. In this paper, the authors compare five different classification methods on multispectral imagery of south-central Virginia: support vector machines, neural networks, nearest-neighbor, discriminant analysis, and classification trees. Results will be shown and discussed.

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Revised March 2002