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《Areal Research and Development》 2003-01
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The Decision Tree Classification and Its Application in Land Cover

LI Shuang 1,2 , ZHANG Re-xun 1 (1.College of Environment and Planning, Henan University, Kaifeng 475001, China; 2.Department of Geography, Liaocheng Teachers' University, Liaocheng 252059, China)  
Decision tree classification algorithms have significant potential for remote sensing data classification. In this research, three different types decision tree classification (UDT, MDT and HDT) are present. First, the paper discussed the algorithms structure and the algorithms theory of decision tree. Second, decision tree algorithms have been used to play land cover classification from remotely sensed data, and compare the result with conventional statistics classification. The results of this research showed that decision trees have several advantages for remote sensing applications by virtue of their relatively simple, explicit, and intuitive classification structure.
【Fund】: 河南省杰出青年科学基金资助项目 ( 0 0 0 3 992 0 )
【CateGory Index】: TP79
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