Soft Computing

, Volume 15, Issue 12, pp 2355–2374 | Cite as

A multistage genetic fuzzy classifier for land cover classification from satellite imagery

  • D. G. Stavrakoudis
  • J. B. Theocharis
  • G. C. Zalidis
Focus

Abstract

A linguistic boosted genetic fuzzy classifier (LiBGFC) is proposed in this paper for land cover classification from multispectral images. The LiBGFC is a three-stage process, aiming at effectively tackling the interpretability versus accuracy tradeoff problem. The first stage iteratively generates fuzzy rules, as directed by a boosting algorithm that localizes new rules in uncovered subspaces of the feature space, implicitly preserving the cooperation with previously derived ones. Each rule is able to select the required features, further improving the interpretability of the obtained model. Special provision is taken in the formulation of the fitness function to avoid the creation of redundant rules. A simplification stage follows the first one aiming at further improving the interpretability of the initial rule base, providing a more compact and interpretable solution. Finally, a genetic tuning stage fine tunes the fuzzy sets database improving the classification performance of the obtained model. The LiBGFC is tested using an IKONOS multispectral VHR image, in a lake-wetland ecosystem of international importance. The results indicate the effectiveness of the proposed system in handling multidimensional feature spaces, producing easily understandable fuzzy models.

Keywords

AdaBoost Genetic fuzzy rule-based classification systems (GFRBCS) Local feature selection Genetic tuning Evolutionary algorithms Textural and spatial features Multispectral image classification 

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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  • D. G. Stavrakoudis
    • 1
  • J. B. Theocharis
    • 1
  • G. C. Zalidis
    • 2
  1. 1.Division of Electronics and Computer Engineering, Department of Electrical and Computer EngineeringAristotle University of ThessalonikiThessalonikiGreece
  2. 2.Laboratory of Applied Soil Science, Faculty of AgronomyAristotle University of ThessalonikiThessalonikiGreece

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