Tan Xingye, Huang Bo, Batty Michael, Li Weiyu, Wang Qi Ryan, Zhou Yulun, Gong Peng
Department of Geography, The University of Hong Kong, Hong Kong SAR, China.
Computational Social Science Laboratory, Faculty of Social Science, The University of Hong Kong, Hong Kong SAR, China.
Nat Commun. 2025 Mar 24;16(1):2881. doi: 10.1038/s41467-025-58286-4.
Human mobility is becoming increasingly complex in urban environments. However, our fundamental understanding of urban population dynamics, particularly the pulsating fluctuations occurring across different locations and timescales, remains limited. Here, we use mobile device data from large cities and regions worldwide combined with a detrended fractal analysis to uncover a universal spatiotemporal scaling law that governs urban population fluctuations. This law reveals the scale invariance of these fluctuations, spanning from city centers to peripheries over both time and space. Moreover, we show that at any given location, fluctuations obey a time-based scaling law characterized by a spatially decaying exponent, which quantifies their relationship with urban structure. These interconnected discoveries culminate in a robust allometric equation that links population dynamics with urban densities, providing a powerful framework for predicting and managing the complexities of urban human activities. Collectively, this study paves the way for more effective urban planning, transportation strategies, and policies grounded in population dynamics, thereby fostering the development of resilient and sustainable cities.
在城市环境中，人类流动正变得日益复杂。然而，我们对城市人口动态的基本理解，尤其是在不同地点和时间尺度上出现的脉动式波动，仍然有限。在此，我们使用来自全球大城市和地区的移动设备数据，并结合去趋势分形分析，以揭示支配城市人口波动的通用时空标度律。该定律揭示了这些波动的尺度不变性，在时间和空间上从城市中心到周边地区均适用。此外，我们表明，在任何给定位置，波动都遵循基于时间的标度律，其特征是空间衰减指数，该指数量化了它们与城市结构的关系。这些相互关联的发现最终形成了一个强大的异速生长方程，将人口动态与城市密度联系起来，为预测和管理城市人类活动的复杂性提供了一个有力的框架。总体而言，这项研究为基于人口动态的更有效的城市规划、交通战略和政策铺平了道路，从而促进了具有韧性和可持续性城市的发展。
