Multispectral Satellite Imagery Classification Using a Fuzzy Decision Tree

Abstract

A land cover classification system is very important nowadays for various remote sensing applications and many sectors of economy. Therefore, development of algorithms for multi- and hyperspectral imagery classification is an urgent task. In this paper we present a new efficient algorithm for multi- and hyperspectral imagery classification based on a fuzzy decision tree approach. Multispectral imagery spectral bands are used as fuzzy data source attributes and cumulative mutual information between them and the resulting fuzzy classification as a decision tree inducing criterion. The proposed algorithm ensures good classification accuracy.