Site Selection of Urban Services in New Cities using Geographic Information System (GIS) and Fuzzy Logic (Case Study: Landfill in Pardis New City)

One of the main goals of planning and constructing satellite towns around metropolitan areas is to attract population overflow, which can reduce the heavy burden of environmental threats in metropolitan areas to some extent. On the other hand, not paying attention to locating the urban services and planning without environmental considerations in these new cities will impose calamities on the region. In fact, these disasters are sometimes so great that they cannot be comparable to the positive consequences of constructing such settlements and will cause predetermined goals fade away. Due to the importance of this issue, the purpose of this study was to locate the municipal landfill in Pardis New City. This city is one of the satellite towns on the outskirts of Tehran and is located 18 km east of Tehran, on both sides of the Tehran-Mazandaran road. The research methods in this study include using multi-criteria decision making method and applying the capabilities of Geographic Information Systems (GIS) and Analytic Hierarchy Process (AHP). The intended criteria in this study are distance from deep-water wells, land slope, distance from Pardis New City, distance from surface water, distance from population centers, distance from gardens, distance from agricultural lands and distance from roads access. In this study, after determining the coefficient of importance of the criteria, the analyses were performed according to Boolean and fuzzy logics in Arcgis10.5 software environment, and the optimal lands for municipal waste disposal were identified in the southeast of Pardis New City. The results of this study showed that the fewest fields created in terms of the number of parts and their area were in Boolean method, while most of them were in the fuzzy method. This is due to the fact that the selection of criteria is absolute and definite in Boolean method, whereas various results can be modified to give more acceptable answers in the fuzzy method.