Simulating Urban Economic Development via S-Curve & CA

Title: Simulating Urban Economic Development in Metropolitan Areas Using Coupled S-Curve and Cellular Automata

urban-economic-scurve-cellular-automata-pic1

Abstract

Urban economic forecasting is crucial for the formulation of a macroeconomic development strategy for a region toward harmonious socio-economic and ecological progress. Cellular Automata (CA) enables fine-grained urban economic modeling, but its conventional discrete-state structure performs poorly when handling continuous economic variables like GDP density, and furthermore often lacks the ability to integrate with general economic growth patterns. These shortcomings ultimately compromise the simulation accuracy of urban economic dynamics. This paper innovatively proposes a continuous-state Density Cellular Automata (DCA) framework integrated with S-shaped economic growth responses, aiming to enhance GDP density simulation accuracy. Taking the Wuhan metropolitan area as a case, we simulated the 2010–2020 GDP density evolution and compared the performance with two baseline models. The results indicate that all cities in the metropolitan area follow S-shaped growth but with significant inter-city differences. The DCA demonstrates a 58.21% reduction in MAE compared to the discrete-state PLUS model and a 29.78% decrease in RMSE relative to the conventional continuous-state Gray-Cells CA model. The scale effect analysis shows that smaller zoning scales improve the accuracy of economic simulations. DCA can provide references of economic trends and support urban planners and managers in balancing urbanization with the ecological environment.