Multispectral Satellite Imagery Classification Using a Fuzzy Decision Tree
Multispectral Satellite Imagery Classification Using a Fuzzy Decision Tree
Author(s): Sergey Stankevich, Vitaly Levashenko, Elena ZaitsevaSubject(s): Economy, ICT Information and Communications Technologies
Published by: Žilinská univerzita v Žilině
Keywords: Remote sensing; multispectral imagery classification; fuzzy decision trees; classification accuracy; spectral band selection;
Summary/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.
Journal: Komunikácie - vedecké listy Žilinskej univerzity v Žiline
- Issue Year: 16/2014
- Issue No: 1
- Page Range: 109-113
- Page Count: 5
- Language: English