Urban sprawl modeling using statistical approach in Mashhad, northeastern Iran

Urban sprawl is a key subject of interest among urban planners and policy-makers, which needs to measure and monitor in order to overcome its impacts. The present study aims to generate an urban sprawl model using two statistical approaches by the integration of GIS in Mashhad city, northeastern Iran. For this purpose, a modified relative Shannon’s entropy together with hierarchical clustering analysis was considered as sprawl model. Five geo-statistical variables were considered as input measurement variables in sprawl model. Statistical approaches of relative entropy measurement and hierarchical clustering analysis revealed an analogous result through the sprawl model. On this basis, three districts were categorized as crucial zones of the study area in regard of sprawl expansion. The sprawl expansion in these districts depended on the growth of informal settlements and increase of crimes. This phenomenon could trigger negative environmental and socio-economical impacts in the study area. Hence, the urban management in the study area should control the sprawl expansion in the crucial districts by environmental prevention of land use change and land degradation.