Land-use scenario modelling based on human decisions - Combining system dynamics and cellular automata

Our paper introduces a combined model approach using systemdynamics simulating regional drivers and cellular automaton representing localland-use dynamics. The model benefits from conclusive causal interrelations ofdetailed population dynamics, real household decision parameters, residentialdemand on prevailing residential land use types and residential supply as a resultof dynamic housing parameters. Consequently, we can simulate growth andshrinkage processes to occur concurrently within an urban region. In this process,human decisions are covered in two ways, firstly, by bottom-up individualresidential choice-making over different residential types and secondly by top-downdecision making by planning authorities. The model is applied to the metropolitanregion of Berlin. It provides more plausible results compared to cellular automataapproaches using conventional trend based regional input models. Humandecisions on land-use are displayed in six scenarios representing possible futurepaths of Berlin´s urban development from 2008 to 2030. The findings indicate thatthe effect on residential patterns due to different planning approaches is equal tothe effect introduced by the likely maximum deviation of economic anddemographic trends as proved by kappa values. A quality assessment confirms thebenefit of the combined approach and affirms that the model functionality is sound.