Spatial-spatial analysis of the inland urban crash using spatial GIS and Fuzzy Model (Case study: Kerman city)

The city of Kerman has seen many developments over the past decades. These developments include: physical development, urban population growth, inertial migration, marginalization and horizontal expansion of the city while maintaining the administrative, economic and cultural center of the South East, but building infrastructure, especially in the urban transport sector, in proportion to this developments have not been made. The present study, with the understanding of the importance of the subject and considering the position of Kerman city and the lack of coherent studies in this regard, it has been tried to investigate and analyze the dispersion of accidents in the city of Kerman by using GIS technology and fuzzy model and prioritize the accidental areas using the strategic planning to organize incidental urban areas.

The type of research is operational and considering the nature of the subject, the research method is analytical-expository. The data assessment process is a combination of documentary and survey. Experts opinions  and studies survey, show that in addition to cultural issues, the top ten factors affecting the rate of accidents, population density, density of accidents, density of service centers and passageways play the most role in the amount of accidents.

Based on the combination of effective factors and fuzzy method, three areas of Azadi Square, Khoyane Motahari and jihad are the most susceptible to intractable accidents, respectively. According to traffic flow projects in Azadi Square, Motahari Avenue (Motahari Park) has three ways Taleghani was designed to organize using strategic planning.

The main purpose of this study was to emphasize the total number of accidents in order to describe accident locations and create a model based on the severity and variety of accidents. Conclusions show that central areas of the city, especially Azadi Square, Motahari Street, and Jihad Boulevard, were the most at risk of urban accidents.