land use mapping using fuzzy classification: case study in three catchment areas in hamedan province

land cover mapping is important for many planning and management activities. today, satellite images and remote sensing techniques are extensively used in all sectors including agriculture and natural resources because they provide updated data and high analyzing abilities. in this study, in order to produce land cover map for the northern part of hamedan province , digital satellite data irsp6 ( awifs time series data) were used. first, satellite image geometric correction with a mean square error of less than 0.48 pixels was applied. for image classification, the method of fuzzy classification was used. finally, the land cover map of the study region was classified into thirteen classes. to assess the classified land cover map precision it was controlled for ground truths with a gps. kappa coefficient and overall classification accuracy of fuzzy classificotion were estimated 86 and 88 percent respectively. the results confirmed that the fuzzy clofifier was capable to generate land cover maps and cultivation‎ pattern‎ with high accuracy.