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Dynamic community detection considering daily rhythms of human mobility
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References

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  • 2018Portraying Urban Functional Zones by Coupling Remote Sensing Imagery and Human Sensing Data133 cited
  • 2011Reliable shortest path finding in stochastic networks with spatial correlated link travel times120 cited
  • 2018Urban form, demographic and socio-economic correlates of walking, cycling, and e-biking: Evidence from eight neighborhoods in Beijing94 cited
  • 2018Understanding the Impacts of Human Mobility on Accessibility Using Massive Mobile Phone Tracking Data90 cited
  • 2012Discovering the Geographical Borders of Human Mobility79 cited
  • 2019

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Understanding travel time uncertainty impacts on the equity of individual accessibility
73 cited
  • 2016Exploring Spatial-Temporal Patterns of Urban Human Mobility Hotspots63 cited
  • Cited by

    • 2023Predicting mobile users' next location using the semantically enriched geo-embedding model and the multilayer attention mechanism25 cited
    • 2024How to build vibrant communities by utilizing functional zones? A community-detection-based approach for revealing the association between land use and community vibrancy18 cited
    • 2025Optimal location of free-floating bike-sharing dispatching hubs: A multi-scale perspective9 cited
    • 2024Understanding multimodal travel mobilities of dockless bike-sharing and metro: A multilayer network analysis7 cited
    • 2023Identification of homogenous zones using riding speed time-series to reveal the spatial structure of the urban pace6 cited
    • 2024Understanding user equilibrium states of road networks: Evidence from two Chinese mega-cities using taxi trajectory mining6 cited
    • 2025Revealing Urban Spatial Interaction Characteristics and Crowd Travel Patterns from Trajectory Data6 cited
    • 2023Comprehensive Analysis of Key Spatial Parameters for Characterizing Human Mobility Patterns4 cited