了解人口和移徙模式是一个巨大的挑战。数以百万计的个人决定，由经济，政治，人口，理性和/或情感的原因，构成了人口动态的高度复杂性。近年来，在定量地理解这种复杂性方面已经取得了重大进展，因为涉及城市增长的那些[Bettencourt LMA，Lobo J，Helbing D，Kuehnert C，West GB（2007）Growth，. Innovation，Scaling，and the Pace of Life in Cities，Proc Natl Acad Sci USA 104（17）7301-7306]，但许多基本问题仍然难以理解。在这里，我们提出了令人信服的经验证据，高度的规律性，在城市蔓延的时间和空间的相关性，解开模式的惯性在城市的增长和它们之间的相互作用。通过使用世界上现存最详尽的人口数据基础之一--西班牙政府研究所INE的数据，记录涵盖111年和（2011年）4500万人，分布在8000多个人口核心中--我们表明城市增长的惯性具有15年的特征时间，它与其他城市的增长之间的相互作用具有70公里的特征距离。距离被证明是纠缠两个城市的主要因素（占总相关性的60%）。我们提出了一个人口流动的数学模型，i）再现了所有这些假设，ii）可以用来预测城市的人口演变。因此，我们当前社会理论的力量得到了加强。
英文摘要：
Understanding demographic and migrational patterns constitutes a great challenge. Millions of individual decisions, motivated by economic, political, demographic, rational, and/or emotional reasons underlie the high complexity of demographic dynamics. Significant advances in quantitatively understanding such complexity have been registered in recent years, as those involving the growth of cities [Bettencourt LMA, Lobo J, Helbing D, Kuehnert C, West GB (2007) Growth,. Innovation, Scaling, and the Pace of Life in Cities, Proc Natl Acad Sci USA 104 (17) 7301-7306] but many fundamental issues still defy comprehension. We present here compelling empirical evidence of a high level of regularity regarding time and spatial correlations in urban sprawl, unraveling patterns about the inertia in the growth of cities and their interaction with each other. By using one of the world's most exhaustive extant demographic data basis ---that of the Spanish Government's Institute INE, with records covering 111 years and (in 2011) 45 million people, distributed amongst more than 8000 population nuclei--- we show that the inertia of city growth has a characteristic time of 15 years, and its interaction with the growth of other cities has a characteristic distance of 70 km. Distance is shown to be the main factor that entangles two cities (a 60% of total correlations). We present a mathematical model for population flows that i) reproduces all these regularities and ii) can be used to predict the population-evolution of cities. The power of our current social theories is thereby enhanced.
The development of public transportation networks and associated transit oriented development policies are efficient tools to mitigate urban sprawl and its negative environmental impacts, especially in terms of commuting emissions. We study in this paper the trajectories in terms of sprawl and public transport accessibility of the nine largest Chinese megacities, from 2000 to 2030 with projected transportation networks and populations. Using the radial profile methodology, we compare the evolution of population distribution with the evolution of accessibility profiles. We show a rebalancing of…
Université Paris-Saclay（巴黎萨克雷大学）；CNRS（法国国家科学研究中心）；CEA（法国原子能和替代能源委员会）；Institut de Physique Théorique（理论物理研究所）；Centre d’Analyse et de Mathématique Sociales（社会分析与数学中心）；EHESS（高等社会科学研究院）；Fondazione Bruno Kessler（布鲁诺·凯斯勒基金会）；University of Trento（特伦托大学）
We study a stochastic model of urban growth generating spatial distributions of population densities at an intermediate mesoscopic scale. The model is based on the antagonist interplay between the two opposite abstract processes of aggregation (preferential attachment) and diffusion (urban sprawl). Introducing indicators to quantify precisely urban form, the model is first statistically validated and intensively explored to understand its complex behavior across the parameter space. We then compute real morphological measures on local areas of size 50km covering all European Union, and show th…
Seen from a satellite, observing land use in the daytime or at night, most cities have circular shapes, organised around a city centre. A radial analysis of artificial land use growth is conducted in order to understand what the recent changes in urbanisation are across Europe and how it relates to city size. We focus on the most fundamental differentiation regarding urban land use: has it been artificialised for human uses (residence or roads for instance) or is it natural, or at least undeveloped? Using spatially detailed data from the EU Copernicus Urban Atlas, profiles of artificial land u…
A large proportion of Africa's infrastructure is yet to be built. Where and how these new buildings are constructed matters since today's decisions will last for decades. The resulting morphology of cities has lasting implications for a city's energy needs. Estimating and projecting these needs has always been challenging in Africa due to the lack of data. Yet, given the sweeping urbanisation expected in Africa over the next three decades, this obstacle must be overcome to guide cities towards a trajectory of sustainability and resilience. Based on the location and surface of nearly 200 millio…
Urban systems are composed by complex couplings of several components, and more particularly between the built environment and transportation networks. Their interaction is involved in the emergence of the urban form. We propose in this chapter to introduce an approach to urban morphology grasping both aspects and their interaction. We first define complementary measures, study their empirical values and their spatial correlations on European territorial systems. The behavior of indicators and correlations suggest underlying non-stationary and multi-scalar processes. We then introduce a genera…
The ongoing SARS-CoV-2 pandemic has been holding the world hostage for more than a year now. Mobility is key to viral spreading and its restriction is the main non-pharmaceutical interventions to fight the virus expansion. Previous works have shown a connection between the structural organization of cities and the movement patterns of their residents. This puts urban centers in the focus of epidemic surveillance and interventions. Here we show that the organization of urban flows has a tremendous impact on disease spreading and on the amenability of different mitigation strategies. By studying…
Urban dynamics in large metropolitan areas result from complex interactions across social, economic, and political factors, including population distribution, flows of wealth, and infrastructure requirements. We develop a Census-calibrated model of urban dynamics for the Greater Sydney and Melbourne areas for 2011 and 2016, highlighting the evolution of population distributions and the housing market structure in these two cities in terms of their mortgage and rent distributions. We show that there is a tendency to homophily between renters and mortgage holders: renters tend to cluster nearer …
Entropy relates the fast, microscopic behaviour of the elements in a system to its slow, macroscopic state. We propose to use it to explain how, as complexity theory suggests, small scale decisions of individuals form cities. For this, we offer the first interpretation of entropy for cities that reflects interactions between different places through interdependently linked states in a multiscale approach. With simulated patterns we show that structural complexity in spatial systems can be the most probable configuration if the elements of a system interact across multiple scales. In the case s…
Lyles School of Civil Engineering, Purdue University（普渡大学莱尔斯土木工程学院）；Agronomy Department, Purdue University（普渡大学农学系）；Institut de Physique Théorique, CEA, CNRS-URA 2306（法国原子能和替代能源委员会/法国国家科学研究中心理论物理研究所）；Centre d’Analyse et de Mathématique Sociales, CNRS/EHESS（法国国家科学研究中心/高等社会科学学院社会分析与数学中心）
Urban form has been empirically demonstrated to be of scaling invariance and can be described with fractal geometry. However, the rational range of fractal dimension value and the relationships between various fractal indicators of cities are not yet revealed in theory. By mathematical deduction and transformation (e.g. Fourier transform), I find that scaling analysis, spectral analysis, and spatial correlation analysis are all associated with fractal concepts and can be integrated into a new approach to fractal analysis of cities. This method can be termed 3S analyses of urban form. Using the…
This paper proposes a new method to analyze the spatial structure of urban systems using ideas from fractals. Regarding a system of cities as a set of "particles" distributed randomly on a triangular lattice, we construct a spatial correlation function of cities. Suppose that the spatial correlation follows the power law. It can be proved that the correlation exponent is the second order generalized dimension. The spatial correlation model is applied to the system of cities in China. The results show that the Chinese urban system can be described by the correlation dimension ranging from 1.3 t…
Univ Lyon（里昂大学）；Inria（法国国家信息与自动化研究所）；CNRS（法国国家科学研究中心）；ENS de Lyon（里昂高等师范学院）；Université Claude Bernard Lyon 1（里昂第一大学克洛德·贝尔纳大学）；Central European University（中欧大学）
Urbanisation is a great challenge for modern societies, promising better access to economic opportunities while widening socioeconomic inequalities. Accurately tracking how this process unfolds has been challenging for traditional data collection methods, while remote sensing information offers an alternative to gather a more complete view on these societal changes. By feeding a neural network with satellite images one may recover the socioeconomic information associated to that area, however these models lack to explain how visual features contained in a sample, trigger a given prediction. He…
Bidirectional yet asymmetric causality between urban systems and traffic dynamics in 30 cities worldwide
ETH Zurich（苏黎世联邦理工学院）；University College London（伦敦大学学院）；Singapore-ETH Centre, ETH Zurich（新加坡-苏黎世联邦理工学院中心，苏黎世联邦理工学院）；Department of Geography, University of Wisconsin-Madison（威斯康星大学麦迪逊分校地理系）
Classifying Urban Regions by Aggregated Pollutant Weather Correlation Strength: A Spatiotemporal Study
Maulana Abul Kalam Azad University of Technology, West Bengal（西孟加拉马乌拉纳·阿卜杜勒·卡兰·阿扎德理工大学）；S. N. Bose National Centre for Basic Sciences（S.N.玻色基础科学国家中心）；Indian Statistical Institute（印度统计研究所）
The urban networks of London and New York City are investigated as directed graphs within the paradigm of graph percolation. It has been recently observed that urban networks show a critical percolation transition when a fraction of edges are removed. The resulting strongly connected components form a cluster structure whose size distribution follows a power law with critical exponent $τ$. We start by analyzing how the networks react when subjected to increasingly widespread random edge removal and the effect of spatial correlations with power-law decay. We observe a progressive decrease of $τ…
Decoding street network morphologies and their correlation to travel mode choice
School of Applied Sciences and Engineering, Universidad EAFIT（应用科学与工程学院，埃法伊特大学）；Department of Civil and Environmental Engineering, University of Idaho（土木与环境工程系，爱达荷大学）；Nature and Cities Research Group, Universidad EAFIT（自然与城市研究组，埃法伊特大学）；Math Applications in Science and Engineering Research Group, Universidad EAFIT（科学与工程数学应用研究组，埃法伊特大学）
Urban population density always follows the exponential distribution and can be described with Clark's model. Because of this, the spatial distribution of urban population used to be regarded as non-fractal pattern. However, Clark's model differs from the exponential function in mathematics because that urban population is distributed on the fractal support of landform and land-use form. By using mathematical transform and empirical evidence, we argue that there are self-affine scaling relations and local power laws behind the exponential distribution of urban density. The scale parameter of C…
Urban form and growth can be described with fractal dimension, which is a measurement of space filling of urban evolution. Based on empirical analyses, a discovery is made that the time series of fractal dimension of urban form can be treated as a sigmoid function of time. Among various sigmoid functions, the logistic function is the most probable selection. However, how to use the model of fractal dimension growth to explain and predict urban growth is a pending problem remaining to be solved. This paper is devoted to modeling fractal dimension evolution of different types of cities. A intere…
The question of whether urbanization contributes to increasing carbon dioxide emissions has been mainly investigated via scaling relationships with population or population density. However, these approaches overlook the correlations between population and area, and ignore possible interactions between these quantities. Here, we propose a generalized framework that simultaneously considers the effects of population and area along with possible interactions between these urban metrics. Our results significantly improve the description of emissions and reveal the coupled role between population …
Spatial patterns and processes of cities can be described with various entropy functions. However, spatial entropy always depends on the scale of measurement, and it is difficult to find a characteristic value for it. In contrast, fractal parameters can be employed to characterize scale-free phenomena. This paper is devoted to exploring the similarities and differences between spatial entropy and fractal dimension in urban description. Drawing an analogy between cities and growing fractals, we illustrate the definitions of fractal dimension based on different entropy concepts. Three representa…
Nowadays, travel surveys provide rich information about urban mobility and commuting patterns. But, at the same time, they have drawbacks: they are static pictures of a dynamic phenomena, are expensive to make, and take prolonged periods of time to finish. However, the availability of mobile usage data (Call Detail Records) makes the study of urban mobility possible at levels not known before. This has been done in the past with good results--mobile data makes possible to find and understand aggregated mobility patterns. In this paper, we propose to analyze mobile data at individual level by e…
We investigate the behavior of extended urban traffic networks within the framework of percolation theory by using real and synthetic traffic data. Our main focus shifts from the statistical properties of the cluster size distribution studied recently, to the spatial analysis of the clusters at criticality and to the definition of a similarity measure between whole urban configurations. We discover that the breakup patterns of the complete network, formed by the connected functional road clusters at criticality, show remarkable stability from one hour to the next, and predictability for differ…
Urban infrastructure networks play a major role in providing reliable flows of multitude critical services demanded by citizens in modern cities. We analyzed here a database of 125 infrastructure networks, roads (RN); urban drainage networks (UDN); water distribution networks (WDN), in 52 global cities, serving populations ranging from 1,000 to 9,000,000. For all infrastructure networks, the node-degree distributions, p(k), derived using undirected, dual-mapped graphs, fit Pareto distributions. Variance around mean gamma reduces substantially as network size increases. Convergence of functiona…
Evolving spatiotemporal patterns and urban scaling of deaths from external causes
Universidade Federal do Ceará（塞阿拉联邦大学）；Escola de Saúde Pública do Ceará（塞阿拉公共卫生学院）；Universidade de Fortaleza（福塔莱萨大学）；Secretaria Executiva de Vigilância em Saúde, Secretaria da Saúde do Ceará（塞阿拉州卫生厅健康监督执行秘书处）；Universidade Estadual de Maringá（马林加州立大学）；Department of Global Health and Population, Harvard T. H. Chan School of Public Health（哈佛大学陈曾熙公共卫生学院全球健康与人口系）
In recent decades the world has experienced rates of urban growth unparalleled in any other period of history and this growth is shaping the environment in which an increasing proportion of us live. In this paper we use a longitudinal dataset from Foursquare, a location-based social network, to analyse urban growth across 100 major cities worldwide. Initially we explore how urban growth differs in cities across the world. We show that there exists a strong spatial correlation, with nearby pairs of cities more likely to share similar growth profiles than remote pairs of cities. Subsequently we …
The COVID-19 pandemic has evolved over time through multiple spatial and temporal dynamics. The varying extent of interactions among different geographical areas can result to a complex pattern of spreading so that influences between these areas can be hard to discern. Here, we use cross-correlation analysis to detect synchronous evolution and potential inter-influences in the time evolution of new COVID-19 cases at the county level in the USA. Our analysis identified two main time periods with distinguishable features in the behavior of correlations. In the first phase, there were few strong …
Using machine learning to understand causal relationships between urban form and travel CO2 emissions across continents
Mercator Research Institute of Global Commons and Climate Change（墨卡托全球公域与气候变化研究所）；Technical University Berlin（柏林工业大学）；The University of Edinburgh（爱丁堡大学）；Institute for Applied Economic Research（应用经济研究所）；German Aerospace Center（德国航空航天中心）；UC Berkeley（加州大学伯克利分校）
