Keywords
urban region, land use modelling, system dynamics, cellular automaton, scenario simulations, berlin
Start Date
1-7-2012 12:00 AM
Abstract
Our paper introduces a combined model approach using system dynamics simulating regional drivers and cellular automaton representing local land-use dynamics. The model benefits from conclusive causal interrelations of detailed population dynamics, real household decision parameters, residential demand on prevailing residential land use types and residential supply as a result of dynamic housing parameters. Consequently, we can simulate growth and shrinkage processes to occur concurrently within an urban region. In this process, human decisions are covered in two ways, firstly, by bottom-up individual residential choice-making over different residential types and secondly by top-down decision making by planning authorities. The model is applied to the metropolitan region of Berlin. It provides more plausible results compared to cellular automata approaches using conventional trend based regional input models. Human decisions on land-use are displayed in six scenarios representing possible future paths of Berlin´s urban development from 2008 to 2030. The findings indicate that the effect on residential patterns due to different planning approaches is equal to the effect introduced by the likely maximum deviation of economic and demographic trends as proved by kappa values. A quality assessment confirms the benefit of the combined approach and affirms that the model functionality is sound.
Land-use scenario modelling based on human decisions – Combining system dynamics and cellular automata
Our paper introduces a combined model approach using system dynamics simulating regional drivers and cellular automaton representing local land-use dynamics. The model benefits from conclusive causal interrelations of detailed population dynamics, real household decision parameters, residential demand on prevailing residential land use types and residential supply as a result of dynamic housing parameters. Consequently, we can simulate growth and shrinkage processes to occur concurrently within an urban region. In this process, human decisions are covered in two ways, firstly, by bottom-up individual residential choice-making over different residential types and secondly by top-down decision making by planning authorities. The model is applied to the metropolitan region of Berlin. It provides more plausible results compared to cellular automata approaches using conventional trend based regional input models. Human decisions on land-use are displayed in six scenarios representing possible future paths of Berlin´s urban development from 2008 to 2030. The findings indicate that the effect on residential patterns due to different planning approaches is equal to the effect introduced by the likely maximum deviation of economic and demographic trends as proved by kappa values. A quality assessment confirms the benefit of the combined approach and affirms that the model functionality is sound.
