Abstract JSSP

Urban Sprawl Modelling. The Case of Sanandaj City, Iran

Sassan MOHAMMADY1, Mahmoud Reza DELAVAR1
1 University of Tehran, College of Engineering, Department of Surveying and Geomatics Engineering, GIS Division, Tehran, IRAN
E-mail: Sassanmohammady@ut.ac.ir, mdelavar@ut.ac.ir
Pages: 83-90

Abstract. World urban population has dramatically increased from 22.9% in 1985 to 53% in 2013 fact that has caused unprecedented urban environmental destruction and shortage of infrastructure needed to support the population. In terms of the pressure on the built environment, urban sprawl increases the financial and environmental costs associated with infrastructure, waste disposal, energy consumption and the use of natural resources. Urban sprawl causes much damage to the natural environment by creating and furthering the spread of pollution. Thus, it becomes necessary to monitor, analyze and model the city growth. Efforts have been made to predict potential urban development in accordance with the existing and/or planned infrastructure based on smart city development plans. A number of models have been employed to detect urban land use/cover changes considering the various known drivers of land use change. The case study area is the city of Sanandaj in the west of Iran. In this study, we used Particle Swarm Optimization algorithm for modelling the urban sprawl during 1987-2000, and we employed the Landsat imageries acquired in 1987 and 2000 for modelling urban sprawl in this area for the period 1987-2000. We also considered a number of influencing factors to predict the potential urban growth modelling including the following: distance to street, distance to district centre, distance to developed area, distance to green space, slope and the number of urban cell in a 3*3 neighbourhood. We used Kappa statistics for an accurate assessment in order to compare the simulated map in 2000 with the real one.

K e y w o r d s: urban sprawl, modelling, Shannon Entropy, Particle Swarm Optimization (PSO)








			Urban Sprawl Modelling. The Case of Sanandaj City, Iran Sassan MOHAMMADY1, Mahmoud Reza DELAVAR1 1 University of Tehran, College of Engineering, Department of Surveying and Geomatics Engineering, GIS Division, Tehran, IRAN E-mail: Sassanmohammady@ut.ac.ir, mdelavar@ut.ac.ir Pages: 83-90 Abstract. World urban population has dramatically increased from 22.9% in 1985 to 53% in 2013 fact that has caused unprecedented urban environmental destruction and shortage of infrastructure needed to support the population. In terms of the pressure on the built environment, urban sprawl increases the financial and environmental costs associated with infrastructure, waste disposal, energy consumption and the use of natural resources. Urban sprawl causes much damage to the natural environment by creating and furthering the spread of pollution. Thus, it becomes necessary to monitor, analyze and model the city growth. Efforts have been made to predict potential urban development in accordance with the existing and/or planned infrastructure based on smart city development plans. A number of models have been employed to detect urban land use/cover changes considering the various known drivers of land use change. The case study area is the city of Sanandaj in the west of Iran. In this study, we used Particle Swarm Optimization algorithm for modelling the urban sprawl during 1987-2000, and we employed the Landsat imageries acquired in 1987 and 2000 for modelling urban sprawl in this area for the period 1987-2000. We also considered a number of influencing factors to predict the potential urban growth modelling including the following: distance to street, distance to district centre, distance to developed area, distance to green space, slope and the number of urban cell in a 33 neighbourhood. We used Kappa statistics for an accurate assessment in order to compare the simulated map in 2000 with the real one. K e y w o r d s:* urban sprawl, modelling, Shannon Entropy, Particle Swarm Optimization (PSO)