Communications - Scientific Letters of the University of Zilina 2014, 16(1):109-113 | DOI: 10.26552/com.C.2014.1.109-113

Multispectral Satellite Imagery Classification Using a Fuzzy Decision Tree

Sergey Stankevich1, Vitaly Levashenko2, Elena Zaitseva2
1 Scientific Centre for Aerospace Research of the Earth, Ukraine
2 University of Zilina, Slovakia

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.

Keywords: remote sensing, multispectral imagery classification, fuzzy decision trees, classification accuracy, spectral band selection

Published: February 28, 2014  Show citation

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Stankevich, S., Levashenko, V., & Zaitseva, E. (2014). Multispectral Satellite Imagery Classification Using a Fuzzy Decision Tree. Communications - Scientific Letters of the University of Zilina, 16(1), 109-113. doi: 10.26552/com.C.2014.1.109-113
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