首页|Quantifying local mobility patterns in urban human mobility data
Quantifying local mobility patterns in urban human mobility data
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NETL
NSTL
Taylor & Francis
Abstract Understanding fine-scale dynamics of human mobility patterns is pivotal for effective urban planning, public health strategies, and retail analysis. This study introduces a novel mobility measure – the Local Mobility Index (LMI) – combining geometry-based mobility metrics and accessibility measures. The LMI can be considered a measure of ‘relative localness’ by integrating preferences into the assessment of local mobility patterns, offering a novel measure for understanding mobility behavior in urban contexts. The LMI improves upon existing measures as it captures individual choice for local destinations through measuring whether individuals select nearby destinations; accounting for the unequal spatial distribution of urban amenities. Our contribution is mainly methodological, advancing the field by introducing a metric that captures different aspects of mobility compared to conventional mobility metrics. Leveraging mobile-phone-based GPS data, we examine the LMI using 759 individuals across three cities in England. We found that the LMI captures a new and distinct dimension of urban mobility, as evidenced by its weak correlation with established metrics. Therefore, LMI's capacity to highlight previously undetected aspects of mobility behavior, underscores its importance for advancing research and urban planning.
Local mobility indexlocalized travel behaviorurban accessibility optimizationspatial mobility patterns
Milad Malekzadeh、Darja Reuschke、Jed A. Long
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Department of Geography and Environment, Western University
City-Region Economic Development Institute, Birmingham Business School, University of Birmingham
NETL
NSTL
Taylor & Francis
