Application of Different Methods of Decision Tree Algorithm for Mapping Rangeland Using Satellite Imagery (Case Study: Doviraj Catchment in Ilam Province)

Using satellite imagery for the study of Earth's resources is attended by manyresearchers. In fact, the various phenomena have different spectral response inelectromagnetic radiation. One major application of satellite data is the classification ofland cover. In recent years, a number of classification algorithms have been developed forclassification of remote sensing data. One of the most notable is the decision tree. The aimof this study was to compare three types of decision trees split algorithm for land coverclassification in Doviraj catchment in Ilam province, Iran. For this, propose, first, thegeometric and radiometric corrections were performed on the 2007 ETM+ data. Field dataas training sites were collected in the various classes of land use. The results of imageclassification accuracy assessment showed that the Gini split classification. With kappavalue 89.98 and the entire accuracy 91.17% was significantly higher, then categorization ofbranching and the branching ratio and Entropy with kappa values of 88.45 and 90.65 andthe entire accuracy of 86.21 and 86.15%, respectively.