Nowadays, urban land use and land cover information at the micro and macro levels of planning have a particular importance. So many researches have not been done in land use information extraction. Remote sensing as an inexpensive and fast method, and particular with appearance of object-based analysis, has an appropriate potential for this. In this paper, the aim is land use information extraction on a dense and complicated urban area. For this purpose, a hierarchical system inclusive land cover and land use levels has been used. After the implementation of a step by step land cover classification approach, land use unites extraction are done. In the next stage, feature space inclusive more than 50 conceptual features based on land cover information is designed and extracted. After this stage, optimized features among these features with high separability using SFFS are extracted. Finally a fuzzy nearest neighbor classification for land use classification based on optimized is implemented. Land use classification is performed on two combined and uncombined class system that combined class is recognized as most appropriate class system. In the present approach without considering area criteria of land use object, 82% overall accuracy and with this criteria 85% overall accuracy is achieved.
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