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

机译:通过将重力场模型与元胞自动机相结合,对大城市群区域中的城市景观动力学进行建模。

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摘要

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.
机译:在大都市区(MCA)中有效建模城市景观动力学对于理解其空间演变过程至关重要。但是,现有的基于元胞自动机(CA)的城市景观动态模型的局限性在于,它们没有考虑MCA中不同城市/城镇之间的城市流量(例如,人,物质和信息的流量)。本文提出了一种新的都市景观动态模型(MLDM),该模型通过将重力场模型(GFM)与CA模型相结合,更适合于在MCA中模拟城市景观。 GFM用于建模城市间城市流动的影响并完善CA模型的转换规则。 MLDM被用于模拟北京-天津-唐山的MCA中的城市景观,并且比不考虑城市流量的CA模型产生了更准确的模拟结果。基于MLDM的未来景观预测表明,该地区的城市化将持续到2020年,尤其是在一些“热点”地区。在中国这个心脏地区,应密切注意这些领域的战略性区域规划和环境保护。

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