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Quantifying long-term evolution of intra-urban spatial interactions.

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    New metro lines can reshape urban mobility, even if standard metrics show little change. Analyzing community structures reveals how infrastructure like Singapore's Circle Line (CCL) alters spatial interactions and travel patterns over time.

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    Area of Science:

    • Urban planning and transportation science
    • Spatial analysis and network theory
    • Mobility data analytics

    Background:

    • Assessing the long-term effects of urban transportation infrastructure changes on spatial interactions is challenging.
    • Static or aggregated mobility measures often fail to capture the subtle impacts of infrastructure development.
    • A lack of longitudinal data limits understanding of urban mobility evolution and infrastructure sensitivity.

    Purpose of the Study:

    • To quantify the impact of the Circle Line (CCL) metro extension in Singapore on urban spatial interactions.
    • To investigate how infrastructure changes affect mobility patterns beyond conventional metrics.
    • To explore dynamic changes in urban community structure following transportation enhancements.

    Main Methods:

    • Utilized large-scale mobility records spanning over three years.
    • Compared temporal community structures before and after the Circle Line completion.
    • Analyzed spatial reorganization and changes in locality dynamics.

    Main Results:

    • Commonly used movement indicators showed minimal change post-CCL completion.
    • Significant differences in temporal community structure and spatial reorganization were observed.
    • The CCL facilitated more consistent community structures by reducing travel costs to desired destinations.

    Conclusions:

    • Infrastructure projects like the CCL can induce significant, yet subtle, changes in urban spatial organization.
    • Analyzing dynamic community structures offers a novel approach to evaluating long-term infrastructure impacts.
    • Understanding these dynamics is crucial for analyzing urban evolution and optimizing future transportation developments.