Types of land use classification on the TM imagery—As Shenyang TM images of 2004 for an example

The object of this paper is the classification of land coverage types of the Shenyang TM images of 2004. After introducing the brightness values of TM images and the methods of the classification of land coverage types, we classified the land types of the Shenyang TM images of 2004 in the methods of Supervised and decision tree using ENVI software. The results shows that the method of decision tree is more effective to distinguish classes some types whose reflective luminance are so similar that easy confused than Supervised. Decision tree will be further developed and applied.