This video paper presents an improved cellular automata (CA) model of urban growth.
An innovative feature of this cellular model is the incorporation stochastically optimize the transition rules to reduce the simulation
uncertainties and improve its locational accuracy in urban modeling. The CA
parameters retrieved by the PSO technique. This algorithm based CA model was applied in disctrict Presov, Slovakia, to simulate the spatio-temporal process of urban growth from 2006 to 2018.
