Rapid Urban Growth in the Qazvin Region and Its Environmental Hazards: Implementing an Agent-Based Model
Farhad Hosseinali1, Ali A. Alesheikh1, Farshad Nourian2
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1Faculty of Geodesy and Geomatics Engineering,
K.N. Toosi University of Technology, ValiAsr Street., Mirdamad Cross, 19967-15433, Tehran, Iran
2School of Urban Planning, University of Tehran, Enghelab Avenue, 14155-6135,Tehran, Iran
Pol. J. Environ. Stud. 2014;23(3):727–735
Urban growth is a prevalent challenge in many countries as it causes unexpected changes in land-uses of surrounding areas of cities and endangers the environment and natural resources. Thus, spatial planners and environmental managers always look for the models that simulate the expansion of urban land-use, and enable them to prevent unbalanced expansion of cities, and guide the developments to the desired areas.
Several methods have been devised to simulate the dynamics of land-use development. However, the complexity of urban growth is recognized as a major barrier for such simulation methods. Agent-based models as a dynamic bottom-up approach use the real actors of land-use development as their basic components. Thus, such models have found popularity in simulating land-use development and urban sprawl modeling.
This paper introduces a new agent-based model used for simulating urban land-use development in our study area located in Qazvin province, Iran. The orchards that encompass the western, eastern, and southern sides of Qazvin city are the most sensitive zones in the study area. The model uses 2005 data for the purpose of calibration and 2010 data for the goal of evaluation. A Kappa accuracy of 82.78% was finally achieved for the predication of the observed developments. Also, three zones of residential developments around Qazvin city were found to be endangered. Orchards located on the eastern side of Qazvin city are exposed to destruction and conversion into urban areas. The calibrated model can also be used as a useful tool for predicting future land-use developments and for recognizing endangered environmental zones.