Mobility Behavior Evolution During Extended Emergencies: Returners, Explorers, and the 15-Minute City

TL;DR

This study addresses how mobility patterns in a dense urban region evolve during extended emergencies by examining the returner/explorer dichotomy using high-resolution 500 m grid data. It leverages radius of gyration metrics $r_g$ and $r_g^{(k)}$ with a fixed $k=4$ to classify individuals, and analyzes distributions, transitions, and entropy over a 15-day emergency window, comparing against 15 normal days. Key findings include the requirement of at least two weeks to detect shifts, a crisis-driven contraction of long-distance travel among explorers, pronounced weekend returner-like patterns, and persistent spatial disparities linked to POI density; nearly half of explorers shift to returners under crisis. The work offers actionable insights for urban resilience, emphasizing extended monitoring, enhanced local accessibility, temporally adaptive policies, and fine-grained neighborhood planning aligned with the 15-minute city concept. These results underscore the value of granular spatiotemporal data for designing context-aware emergency interventions and sustainable urban strategies.

Abstract

Understanding human mobility during emergencies is critical for strengthening urban resilience and guiding emergency management. This study examines transitions between returners, who repeatedly visit a limited set of locations, and explorers, who travel across broader destinations, over a 15-day emergency period in a densely populated metropolitan region using the YJMob100K dataset. High-resolution spatial data reveal intra-urban behavioral dynamics often masked at coarser scales. Beyond static comparisons, we analyze how mobility evolves over time, with varying emergency durations, across weekdays and weekends, and relative to neighborhood boundaries, linking the analysis to the 15-minute city framework. Results show that at least two weeks of data are required to detect meaningful behavioral shifts. During prolonged emergencies, individuals resume visits to non-essential locations more slowly than under normal conditions. Explorers markedly reduce long distance travel, while weekends and holidays consistently exhibit returner-like, short distance patterns. Residents of low Points of Interest (POI) density neighborhoods often travel to POI rich areas, highlighting spatial disparities. Strengthening local accessibility may improve urban resilience during crises. Full reproducibility is supported through the project website: https://github.com/wissamkontar

Figures (10)

• Figure 1: Distribution of the $S_k$ ratio ($r_g^{(k)} / r_g$), highlighting k-explorers ($S_k \approx 0$) and k-returners ($S_k \approx 1$) during normal (a–d) and emergency (e–h) periods.
• Figure 2: Proportion of k-returners and k-explorers across normal (a) and emergency (b) periods.
• Figure 3: Percentage of k-returners and k-explorers over the first 1, 3, 5, 7, and 14 days of the normal (a, c, e, g, i) and emergency (b, d, f, h, j) periods.
• Figure 4: Maximum distance from home (a, c) and non-home dwelling time (b, d) during the normal and emergency periods. The vertical axis represents the relative share of the total population.
• Figure 5: Maximum distance from home for each day of the normal (a–h) and the emergency periods (i–r).