New application of fuzzy logic algorithm in GIS for land classification
Abstract: Population growth and disorganization of urban planning have led to unsuitable city development in the center of Iran. Suitable region recognition for urban land develop-ment is an important step towards future planning. In the present study, fuzzy logic algorithms (OR, And, Sum, Prod-uct and Gamma) were used within GIS in order to identify valuable land for appropriate residential development. Moreover, effective factors of urban land development (elevation, slope, aspect, geology, land use, drainage net-work, main and bypass roads, distribution of urban and rural areas, and fault line layer) were examined on fuzzy analyses to find the most effective ones. The results showed that, by considering the regional priorities and constraints, the best operator was Gamma, with a power of 0.9. According to this, 74 percent of the total regions are located between less and the least valuable lands and the remaining surfaces (i.e. 26% of the region) were classified from valuable to the most valuable lands. The sensitivity measurement of the layers used in the study showed that fault and distribution of urban and rural layers were the most and the least effective layers on region recognition (i.e. by 25.83% and 3.29%, respectively).