Urban Growth Modelling based on PSO & CA A Case Study of Qazvin Metropolitan Area, Iran

The cellular automata (CA) as a powerful spatial dynamic modelling tool are designed as a function of parameters whose calibration plays a crucial role for obtaining a suitable set of parameters in order for precise and reliable modelling. This paper presents an improved cellular automata model optimised using PSO to simulate the spatiotemporal processes of urban growth. In this study the PSO based CA model was applied in Qazvin metropolitan area, west of Iran, to simulate the spatio-temporal process of urban growth from 2004 to 2010 by using cellular automata setting the logistic regression functions as transition functions. Furthermore, the weighting coefficients of parameters affecting the urban growth, i.e. distance from urban centers, distance from roads, distance from agricultural centers, and neighborhood effects were selected using PSO. The simulation outcomes, evaluated with kappa statistic of 75.2 % demonstrate that the integration of PSO and CA could be suitable for dynamic urban growth modeling

کلیدواژه ها:

Urban Growing ، Cellular Automata ، PSO ، CA with PSO ، Urban Growing with CA PSO