Multi-Classifier Systems (MCSs) of Remote Sensing Imagery Classification Based on Texture Analysis

  • Hongfen Li
  • Guangdao Hu
  • Jiang-feng Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5370)

Abstract

This article concerns methods of improving the accuracy of land cover maps using Very High-resolution Satellites (VHRS).It discusses two methods for increasing the accuracy of classifiers used in land cover mapping. One is texture analysis using GLCM method and the other is multiple classifier system (MCSs) using voting rules. A case study of QuickBird Imagery of an area in Chenggong County of Yunnan Province is conducted based on an analysis of QuickBird imagery. The experiment results show that these two methods can improve the accuracy greatly. The applying of texture bands makes an increase of 2.6816%, and the MCSs make an increase of 3.9512%.

Keywords

multiple classifier system (MCSs) co-occurrence probability texture analysis land-cover classification 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Hongfen Li
    • 1
  • Guangdao Hu
    • 1
  • Jiang-feng Li
    • 1
  1. 1.Institute of Mathematical and Remote Sensing GeologyChina University of GeosciencesWuhanChina

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