General type-2 fuzzy classifiers to land cover classification

Abstract

This paper proposes a fuzzy classifier based on type-2 fuzzy sets to be applied in land cover classification. The classifier is built from the available data and considers the merging of information acquired from different experts. The data regards a thematic mapper representing the land cover of a real plain cultivated area. The experts are represented by different bands which discretize the spectral sensor information. The new method proposed to design the classifier as well as the use of general type-2 fuzzy sets allows the modeling of input-output relations and minimize the effects of uncertainties in the usual fuzzy rule-based classifiers. The experiments carried out attest the efficiency of the proposed general type-2 fuzzy classifier.