Modeling the urban landscape dynamics in a megalopolitan cluster area by incorporating a gravitational field model with cellular automata

The effective modeling of the urban landscape dynamics in a megalopolitan cluster area (MCA) is essential to understanding its spatial evolution process. However, existing urban landscape dynamic models based on cellular automata (CA) are limited in that they do not consider urban flows (e.g., flows of people, material, and information) between the different cities/towns in an MCA. This paper proposes a new megalopolitan landscape dynamic model (MLDM) that is better suited for simulating the urban landscapes in an MCA by combining a gravitational field model (GFM) with a CA model. The GFM was used to model the influence of inter-city urban flows and to refine the transition rules of the CA model. The MLDM was applied to simulate the urban landscape in the MCA of Beijing–Tianjin–Tangshan, and produced more accurate simulation results than the CA model that did not account for urban flows. The MLDM-based prediction of future landscapes suggested that urbanization will continue in the region through 2020, especially in a few ‘hotspot’ areas. Close attention should be paid to these areas for strategic regional planning and environmental protection in this heartland of China.

► This paper proposes a new megalopolis landscape dynamic model by combining a gravitational field model with a CA model.
► The model proposed produced more accurate simulation results than the CA model, which did not account for urban flows.
► The model proposed is of great value for locating ‘hotspots’ of future urbanization in a megalopolis cluster area.
► The model proposed can provide valuable information for regional landscape planning and environmental management in a megalopolis cluster area.