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Promoting sustainable human mobility for income segregation mitigation.
Yong Chen1, Chenlei Liao2, Zeen Cai2
1School of Information Technology and Artificial Intelligence, Zhejiang University of Finance and Economics, Hangzhou 310018, China.
Patterns (New York, N.Y.)
|April 24, 2026
Summary
Urban income segregation influences human mobility patterns, with people tending to visit areas of lower segregation. This bias, linked to city size and accessibility, impacts urban sustainability and equitable resource distribution.
Area of Science:
- Urban studies
- Sociology
- Environmental science
Background:
- Urban income segregation affects social cohesion and access to resources.
- Understanding mobility patterns is crucial for urban planning and sustainability.
Purpose of the Study:
- To investigate the relationship between urban income segregation and human mobility patterns.
- To quantify the tendency of biased visitation based on segregation levels.
Main Methods:
- Utilized 1.4 million human mobility data points across 10 large US cities.
- Introduced the segregation visitation index to measure mobility bias.
- Developed a human mobility model with segregation constraints and transfer ensemble optimization.
Main Results:
- Locations with varying segregation levels show biased collective mobility.
- Mobility bias increases with city size and infrastructure accessibility.
- Observed mobility patterns are not solely explained by distance and population.
Conclusions:
- Human mobility is intricately linked to urban income segregation and environmental exposure.
- Accounting for location-specific mobility differences is vital for sustainable segregation mitigation strategies.
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