The scaling laws of human travel

By Dirk Brockmann, L. Hufnagel, Theo Geisel. Nature, 2006

2,232 citations recorded by the source corpus.

The dynamic spatial redistribution of individuals is a key driving force of various spatiotemporal phenomena on geographical scales. It can synchronize populations of interacting species, stabilize them, and diversify gene pools. Human travel, for example, is responsible for the geographical spread of human infectious disease. In the light of increasing international trade, intensified human mobility and the imminent threat of an influenza A epidemic, the knowledge of dynamical and statistical properties of human travel is of fundamental importance. Despite its crucial role, a quantitative assessment of these properties on geographical scales remains elusive, and the assumption that humans disperse diffusively still prevails in models. Here we report on a solid and quantitative assessment of human travelling statistics by analysing the circulation of bank notes in the United States. Using a comprehensive data set of over a million individual displacements, we find that dispersal is anomalous in two ways. First, the distribution of travelling distances decays as a power law, indicating that trajectories of bank notes are reminiscent of scale-free random walks known as Lévy flights. Second, the probability of remaining in a small, spatially confined region for a time T is dominated by algebraically long tails that attenuate the superdiffusive spread. We show that human travelling behaviour can be described mathematically on many spatiotemporal scales by a two-parameter continuous-time random walk model to a surprising accuracy, and conclude that human travel on geographical scales is an ambivalent and effectively superdiffusive process.

Subfields: Modeling and Simulation, Molecular Biology, Public Health, Environmental and Occupational Health

View Paper: https://www.semanticscholar.org/paper/f9438655fe509582392dfe70cb5bbe161b550697

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Citations in the corpus

A Tale of Many Cities: Universal Patterns in Human Urban Mobility (2011, methodology): “Our model does not take into account other parameters such as individual heterogeneity patterns [26] or temporal ones [27] that have been studied in the past in the context of human mobility and yet it offers very accurate matching of the human traces of our dataset.”
Understanding individual human mobility patterns (2008, background): “[7] for bank note dispersal, suggesting that the two distributions may capture the same fundamental mechanism driving human mobility patterns.”
Human‐mediated introductions of Australian acacias – a global experiment in biogeography (2011, background): “The human dimensions of invasions are receiving increased attention, drawing interest from researchers in the humanities (e.g. ethicists, historians, philosophers, sociologists) and those studying human behaviour (e.g. movement patterns; Brockmann et al., 2006; González et al., 2008).”
Understanding intra-urban trip patterns from taxi trajectory data (2012, methodology): “This research uses GPS-based floating car data. patterns can be modeled using Lévy flight or truncated Lévy flight (Brockmann et al. 2006; Jiang et al. 2009; Rhee et al. 2008).”
Understanding the Spreading Patterns of Mobile Phone Viruses (2009, background): “Thus to quantitatively study the spreading dynamics of mobile viruses we need to simultaneously model the location (13), the mobility (14-17) and the communication patterns (18-21) of mobile phone users.”
Colloquium: Criticality and dynamical scaling in living systems (2017, background): “For example, physiological and clinical time-series data have typically a spectrum that decays as a power of the frequency (Mandelbrot, 2002) and mobility patterns often exhibit scale-free features (Barabasi, 2005; Brockmann et al., 2006; Proekt et al., 2012).”
An Analysis of Anonymity in the Bitcoin System (2011, neutral): “[13] studied the geographical movement of U.”
Dimension of spatially embedded networks (2011, background): “3 a,b play a fundamental role in physical processes such as diffusio”