Application of Decision Tree in Land Use Classification

In this paper, Landsat ETM+ image of Huainan city in Anhui were classified with a decision tree, which was established based on the analysis of the spectrum characteristics, the texture characteristics and other auxiliary information, such as NDVI, NDBI and topography characteristics. Then the author compared decision tree classification technology with maximum likelihood classification method. The result indicated that the accuracy of decision tree classification was 4.06% higher than that of the maximum likelihood classification and Kappa coefficient was increased by 5.61%. These show that decision tree classification technology is flexible and can improve the classification accuracy efficiently.