Boucherie Louis, Maier Benjamin F, Lehmann Sune
DTU Compute, Technical University of Denmark, Kongens Lyngby, Denmark.
Center for Social Data Science, University of Copenhagen, Copenhagen, Denmark.
Nat Hum Behav. 2025 Sep 1. doi: 10.1038/s41562-025-02282-7.
Driven by access to large volumes of movement data, the study of human mobility has grown rapidly over the past few decades. The field has shown that human mobility is scale-free, proposed models to generate scale-free moving distance distributions and explained how the scale-free distribution arises. It has not, however, explicitly addressed how mobility is structured by geographical constraints, such as how mobility relates to the outlines of landmasses, lakes and rivers and the placement of buildings, roadways and cities. On the basis of millions of moves, we show how separating the effect of geography from mobility choices reveals a power law spanning five orders of magnitude. To do so, we incorporate geography via the pair distribution function, which encapsulates the structure of locations on which mobility occurs. By showing how the spatial distribution of human settlements shapes human mobility, our approach bridges the gap between distance- and opportunity-based models of human mobility.
在获取大量移动数据的推动下，人类流动性研究在过去几十年中迅速发展。该领域已表明人类流动性是无标度的，提出了生成无标度移动距离分布的模型，并解释了无标度分布是如何产生的。然而，它尚未明确解决流动性是如何由地理限制构建的，例如流动性如何与陆地、湖泊和河流的轮廓以及建筑物、道路和城市的布局相关。基于数百万次移动，我们展示了如何将地理因素的影响与移动选择分开，从而揭示出跨越五个数量级的幂律。为此，我们通过对分布函数纳入地理因素，该函数封装了发生移动的地点的结构。通过展示人类住区的空间分布如何塑造人类流动性，我们的方法弥合了基于距离和基于机会的人类流动性模型之间的差距。
