Keywords
residential mobility; shrinking city; agent-based model; model complexity; agent heterogeneity
Location
Session C1: Complexity, Sensitivity, and Uncertainty Issues in Integrated Environmental Models
Start Date
16-6-2014 3:40 PM
End Date
16-6-2014 5:20 PM
Abstract
Residential mobility is one of the major drivers of urban land use change. For urban planning it is therefore essential to understand patterns of population distribution and residential mobility in cities. Agent-based modelling has been found to be the most suitable method to investigate the complex interplay of processes, including individual location decisions. While numerous of such models have been developed in recent years, the challenge of adequate model complexity is still a hot topic. In this talk we present an agent-based model on residential mobility in the shrinking town Delitzsch in eastern Germany. The model is parameterized by a detailed data base resulting from an extensive questionnaire survey. Using this data-driven approach, it is possible to systematically explore the role of model complexity for describing relocation patterns, for example by setting agents' decision parameters either equal for all households or different for various groups, defined by household properties (like income, composition, lifestyle). In the most detailed model version, agents' decision characteristics are drawn from empirically observed distributions for the given combination of up to six household properties. Furthermore, the complexity of the demography module can be varied. Preliminary results indicate that at larger spatial scales (e.g. moves within the city) detailed parameterization of the decision process does not provide much additional information, whereas model complexity can potentially help to better understand patterns at the scale of neighborhoods. Moreover, experiments varying structural complexity can provide guidance for further structural refinements in model design und hence help improving model realism.
Included in
Civil Engineering Commons, Data Storage Systems Commons, Environmental Engineering Commons, Hydraulic Engineering Commons, Other Civil and Environmental Engineering Commons
Residential mobility and model complexity - an agent-based modelling experiment on a small shrinking town in Eastern Germany
Session C1: Complexity, Sensitivity, and Uncertainty Issues in Integrated Environmental Models
Residential mobility is one of the major drivers of urban land use change. For urban planning it is therefore essential to understand patterns of population distribution and residential mobility in cities. Agent-based modelling has been found to be the most suitable method to investigate the complex interplay of processes, including individual location decisions. While numerous of such models have been developed in recent years, the challenge of adequate model complexity is still a hot topic. In this talk we present an agent-based model on residential mobility in the shrinking town Delitzsch in eastern Germany. The model is parameterized by a detailed data base resulting from an extensive questionnaire survey. Using this data-driven approach, it is possible to systematically explore the role of model complexity for describing relocation patterns, for example by setting agents' decision parameters either equal for all households or different for various groups, defined by household properties (like income, composition, lifestyle). In the most detailed model version, agents' decision characteristics are drawn from empirically observed distributions for the given combination of up to six household properties. Furthermore, the complexity of the demography module can be varied. Preliminary results indicate that at larger spatial scales (e.g. moves within the city) detailed parameterization of the decision process does not provide much additional information, whereas model complexity can potentially help to better understand patterns at the scale of neighborhoods. Moreover, experiments varying structural complexity can provide guidance for further structural refinements in model design und hence help improving model realism.
