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

Authors:
Hongfen Li;Guangdao Hu;Jiang-Feng Li
Affiliations:
Institute of Mathematical and Remote Sensing Geology, China University of Geosciences, Wuhan, China 430074;Institute of Mathematical and Remote Sensing Geology, China University of Geosciences, Wuhan, China 430074;Institute of Mathematical and Remote Sensing Geology, China University of Geosciences, Wuhan, China 430074
Venue:
ISICA '08 Proceedings of the 3rd International Symposium on Advances in Computation and Intelligence
Year:
2008

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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%.