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理解城市内的介观尺度规模模式。

Understanding the mesoscopic scaling patterns within cities.

机构信息

Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing, 100871, China.

Senseable City Lab, Department of Urban Studies and Planning, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.

出版信息

Sci Rep. 2020 Dec 3;10(1):21201. doi: 10.1038/s41598-020-78135-2.

DOI:10.1038/s41598-020-78135-2
PMID:33273607
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7712915/
Abstract

Understanding quantitative relationships between urban elements is crucial for a wide range of applications. The observation at the macroscopic level demonstrates that the aggregated urban quantities (e.g., gross domestic product) scale systematically with population sizes across cities, also known as urban scaling laws. However, at the mesoscopic level, we lack an understanding of whether the simple scaling relationship holds within cities, which is a fundamental question regarding the spatial origin of scaling in urban systems. Here, by analyzing four extensive datasets covering millions of mobile phone users and urban facilities, we investigate the scaling phenomena within cities. We find that the mesoscopic infrastructure volume and socioeconomic activity scale sub- and super-linearly with the active population, respectively. For a same scaling phenomenon, however, the exponents vary in cities of similar population sizes. To explain these empirical observations, we propose a conceptual framework by considering the heterogeneous distributions of population and facilities, and the spatial interactions between them. Analytical and numerical results suggest that, despite the large number of complexities that influence urban activities, the simple interaction rules can effectively explain the observed regularity and heterogeneity in scaling behaviors within cities.

摘要

理解城市要素之间的定量关系对于广泛的应用至关重要。在宏观层面上的观察表明,聚合的城市数量(例如国内生产总值)与城市人口规模系统地按比例缩放,这被称为城市规模法则。然而,在中观层面上,我们还不了解城市内部是否存在简单的缩放关系,这是关于城市系统中缩放的空间起源的一个基本问题。在这里,通过分析涵盖数百万手机用户和城市设施的四个广泛数据集,我们研究了城市内部的缩放现象。我们发现,微观基础设施数量和社会经济活动分别以亚线性和超线性的方式与活跃人口按比例缩放。然而,对于相同的缩放现象,在人口规模相似的城市中,指数是不同的。为了解释这些经验观察,我们提出了一个概念框架,考虑了人口和设施的异质分布以及它们之间的空间相互作用。分析和数值结果表明,尽管影响城市活动的复杂性因素众多,但简单的相互作用规则可以有效地解释城市内部观察到的缩放行为的规律性和异质性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d49/7712915/0f24284f14ef/41598_2020_78135_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d49/7712915/05f095955ff9/41598_2020_78135_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d49/7712915/82d77b3129be/41598_2020_78135_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d49/7712915/1a5ef2956e21/41598_2020_78135_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d49/7712915/0f24284f14ef/41598_2020_78135_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d49/7712915/05f095955ff9/41598_2020_78135_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d49/7712915/82d77b3129be/41598_2020_78135_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d49/7712915/1a5ef2956e21/41598_2020_78135_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d49/7712915/0f24284f14ef/41598_2020_78135_Fig4_HTML.jpg

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