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A comparison of texture measures for the per-field classification of Mediterranean land cover

By C.D. Lloyd, S. Berberoglu, P.J. Curran and P.M. Atkinson

Abstract

Land cover of a Mediterranean region was classified within an artificial neural network (ANN) on a per-field basis using Landsat Thematic Mapper (TM) imagery. In addition to spectral information, the classifier used geostatistical structure functions and texture measures extracted from the co-occurrence matrix. Geostatistical measures of texture resulted in a more accurate classification of Mediterranean land cover than statistics derived from the co-occurrence matrix. The primary advantage of geostatistical measures was their robustness over a wide range of land cover types, field sizes and forms of class mixing. Spectral information and the variogram (geostatistical texture measure) resulted in the highest overall classification accuracies

Topics: G1
Year: 2004
OAI identifier: oai:eprints.soton.ac.uk:15449
Provided by: e-Prints Soton
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