For landscapes and natural phenomena, the face of the earth has always been subject to change. The increase in population and the excessive use of land has increased the pressure on the environment.Therefore, in order to optimize the management of natural areas, awareness of land use is considered as an urgent requirement In this study, a pixel-based classification approach based on ENVI 5.3 software and an object-oriented approach using eCognition software was used to prepare the land use map of Susangerd County with Landsat 8 satellite OLI sensor. In order to compare the results, both methods used the same educational data for classification. Then, the most important methods for assessing accuracy including precision and kappa coefficient of classification were extracted and it was determined that the maximum optimal algorithm in the base pixel classification method compared with other algorithms, 9% show better results. But in contrast to the object-oriented classification method, about 1% (in particular, precise and precise classification) results in higher accuracy in the classification of images. The amount of accuracy in the object-oriented classification-based method depends largely on choosing the appropriate parameters for classification, defining the rules, and applying the appropriate algorithm to obtain the degree of membership.