Time-space dynamics of income segregation in the city of Milan

Traditional approaches to urban income segregation focus on static residential patterns, often failing to capture the dynamic nature of social mixing at the neighborhood level. We leverage high-resolution location-based data from mobile phones to capture the interplay of three different income groups (high, medium, and low) based on their daily routines. The three income groups define a novel 3D space embedded in the temporal dynamics of urban activities, which we propose as a framework to analyze social mixing. This framework offers a more detailed perspective on social interactions, closely linked to the geographical features of each neighborhood. While nighttime residential patterns show high segregation, the working hours foster inclusion, with the city center showing heightened levels of interaction. As evening sets in, leisure areas emerge as potential facilitators for social interactions, depending on urban features such as public transport and various Points Of Interest. These characteristics significantly modulate the magnitude and type of social stratification involved in social mixing, underscoring the significance of urban design in bridging or widening socio-economic divides.

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Publication Details

Journal
PNAS Nexus
Published
2025-08-30
DOI
https://doi.org/10.1093/pnasnexus/pgaf283
Citations
1
Primary Topic
Urban Planning and Valuation
Type
article
Field-Weighted Citation Impact
2.42
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article

Time-space dynamics of income segregation in the city of Milan

Lavinia Rossi Mori, Vittorio Loreto, Riccardo Di Clemente
1 citations
PNAS Nexus
Urban Planning and Valuation
2.42
article

Time-space dynamics of income segregation in the city of Milan

Lavinia Rossi Mori, Vittorio Loreto, Riccardo Di Clemente
article en
1 citations

Abstract

Traditional approaches to urban income segregation focus on static residential patterns, often failing to capture the dynamic nature of social mixing at the neighborhood level. We leverage high-resolution location-based data from mobile phones to capture the interplay of three different income groups (high, medium, and low) based on their daily routines. The three income groups define a novel 3D space embedded in the temporal dynamics of urban activities, which we propose as a framework to analyze social mixing. This framework offers a more detailed perspective on social interactions, closely linked to the geographical features of each neighborhood. While nighttime residential patterns show high segregation, the working hours foster inclusion, with the city center showing heightened levels of interaction. As evening sets in, leisure areas emerge as potential facilitators for social interactions, depending on urban features such as public transport and various Points Of Interest. These characteristics significantly modulate the magnitude and type of social stratification involved in social mixing, underscoring the significance of urban design in bridging or widening socio-economic divides.

PNAS NexusVol. 4(9)
University of Rome Tor Vergata (IT), Institute for Scientific Interchange (IT), Centro Ricerche Enrico Fermi (IT), Complexity Science Hub (AT), Eastern University (BD), Sapienza University of Rome (IT)
Openalex Percentile: Top 9%
Urban Planning and Valuation
2.42
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Time-space dynamics of income segregation in the city of Milan — Lavinia Rossi Mori, Vittorio Loreto, et al. · PNAS Nexus (2025) | TGRS Research Map | TGRS