Uncovering land-use dynamics driven by human decision-making – A combined model approach using cellular automata and system dynamics

Abstract

This paper introduces an enhancement of a cellular automata (CA) model by integrating system dynamics (SD) to incorporate household dynamics and housing decisions as driving forces of residential development. CA macro-models used to simulate the quantitative land-use change (LUC) for urban areas are, thus far, lacking profound dynamics driven by demographic change. The model presented in this paper focuses on household dynamics according to the concept of the second demographic transition (SDT), applying aging and population shrinkage to simulate respective effects on residential choice and the resulting LUC. Such a perspective becomes especially important for urban areas exhibiting growth and shrinkage simultaneously, as currently seen in cities in Europe and in the U.S. To analyze this simultaneity in detail, we implement the residential land use CA model Metronamica and apply it to Berlin’s metropolitan region, which was selected as a typical example that displays contrasting growth and shrinkage processes. The pre-implemented macro-model has been replaced with our new SD model H2DCA (Household Decision Dynamics for Cellular Automata). For the simulation, we used empirical census data, economic data, data on residential satisfaction and numerous types of geo-information representing land-use zoning, accessibility and suitability for the time span 1990‑q2008. A comparison of a null model (NM) and H2DCA provides a very satisfying reproduction of land-use patterns reflected by kappa coefficient values. The causal relation of LUC drivers is considerably improved by sophisticated housing choice-feedback mechanisms. Although specific residential land-use classes exhibit shrinkage, others expand. Due to the detailed residential land-use classification, current re-urbanization processes could also be simulated.