Gendered Mobility Patterns in Île-de-France: Insights from High-Resolution GNSS Traces

Daniela Perrotta , Max Planck Institute for Demographic Research
Egor Kotov, Max Planck Institute for Demographic Research
Tom Theile, Max Planck Institute for Demographic Research
Emilio Zagheni, Max Planck Institute for Demographic Research

Mobility patterns reflect deep social inequalities, with gender shaping how people move through cities. Leveraging high-resolution GPS data from over 3,000 participants in the Île-de-France region, we analyze gendered differences in daily mobility at fine spatial and temporal scales. The dataset provides seven consecutive days of GNSS traces recorded every 2–3 seconds, linked to demographic and socioeconomic attributes and calibrated with population weights to ensure representativeness. We compute five mobility indicators—unique and core locations, radius of gyration, Shannon entropy, and immobility rate—disaggregated by gender and age group. Results show consistent gender gaps: women visit fewer unique (-20%) and core (-25%) locations, travel over smaller areas (-668 m radius), display lower mobility diversity (-0.22 entropy), and exhibit higher immobility rates (+0.25) compared to men. Differences peak among adults aged 25–44, corresponding to caregiving and work–life balance constraints. Income-stratified analyses reveal that gender disparities are largest in low-income communes, where men travel 1.4 km farther on average, while gaps narrow in higher-income areas. These findings demonstrate that socioeconomic context both structures overall mobility and amplifies gender inequality. By leveraging high-resolution, representative GNSS data, this study provides a detailed assessment of gendered mobility in Île-de-France, showing how structural and contextual factors jointly shape everyday movement patterns.

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 Presented in Session 26. Flash Session Emerging Data Sources in Demography: Digital Traces, AI and Mobile Phone Data