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%. © 2008 Springer Berlin Heidelberg.
CITATION STYLE
Li, H., Hu, G., & Li, J. F. (2008). Multi-Classifier Systems (MCSs) of remote sensing imagery classification based on texture analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5370 LNCS, pp. 740–749). https://doi.org/10.1007/978-3-540-92137-0_81
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