分形
标度律
渗透(认知心理学)
城市形态
经济地理学
比例(比率)
地理
缩放比例
计算机科学
统计物理学
城市规划
数学
心理学
地图学
工程类
土木工程
几何学
数学分析
神经科学
物理
作者
Fengli Xu,Yong Li,Depeng Jin,Jianhua Lü,Song Ci
标识
DOI:10.1038/s43588-021-00160-6
摘要
Cities grow in a bottom-up manner, leading to fractal-like urban morphologies characterized by scaling laws. The correlated percolation model has succeeded in modeling urban geometries by imposing strong spatial correlations; however, the origin of the underlying mechanisms behind spatially correlated urban growth remains largely unknown. Our understanding of human movements has recently been revolutionized thanks to the increasing availability of large-scale human mobility data. This paper introduces a computational urban growth model that captures spatially correlated urban growth with a micro-foundation in human mobility behavior. We compare the proposed model with three empirical datasets, discovering that strong social interactions and long-term memory effects in human movements are two fundamental principles responsible for fractal-like urban morphology, along with the three important laws of urban growth. Our model connects the empirical findings in urban growth patterns and human mobility behavior.
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