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Transit Travel Community Detection and Evolutionary Analysis: A Case Study of Shenzhen
12 references·0 citing·53 second hopsampled
Transit Travel Community Detection and Evolutionary Analysis: A Case Study of Shenzhen (2023)Transit Travel Community Detection and Ev…Spatiotemporal Evolution of Travel Pattern Using Smart Card Data (2022)Spatiotemporal Evolution of T…Exploring Spatial Network Structure of the Metropolitan Circle Based on Multi-Source Big Data: A Case Study of Hangzhou Metropolitan Circle (2022)Exploring Spatial Network Str…Revealing spatiotemporal travel demand and community structure characteristics with taxi trip data: A case study of New York City (2021)Revealing spatiotemporal trav…Geographically Explicit Network Analysis of Urban Living and Working Interaction Pattern in Shenzhen City, South China (2021)Geographically Explicit Netwo…A Method for Bus OD Matrix Estimation Using Multisource Data (2020)A Method for Bus OD Matrix Es…Exploring changes in the spatial distribution of the low-to-moderate income group using transit smart card data (2018)Exploring changes in the spat…Portraying Temporal Dynamics of Urban Spatial Divisions with Mobile Phone Positioning Data: A Complex Network Approach (2016)Portraying Temporal Dynamics …Revealing travel patterns and city structure with taxi trip data (2015)Revealing travel patterns and…Quantifying long-term evolution of intra-urban spatial interactions (2014)Quantifying long-term evoluti…Small-world phenomenon of keywords network based on complex network (2013)Small-world phenomenon of key…Redrawing the Map of Great Britain from a Network of Human Interactions (2010)Redrawing the Map of Great Br…Does Urban Mobility Have a Daily Routine? Learning from the Aggregate Data of Mobile Networks (2010)Does Urban Mobility Have a Da…Six Degrees of Separation: A Play (1990)The impact of small world on innovation: An empirical study of 16 countries (2009)A Small World of Citations? 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Evidence from Changxing County, China (2022)Alighting location estimation from public transit data: a case study of Shenzhen (2024)Local Indicators of Spatial Association—LISA (1995)Estimation of a disaggregate multimodal public transport Origin–Destination matrix from passive smartcard data from Santiago, Chile (2012)Detecting the dynamics of urban structure through spatial network analysis (2014)The effect of traffic status on dockless bicycle-sharing: Evidence from Shanghai, China (2022)Voting with one's feet: Unraveling urban centers attraction using visiting frequency (2022)Carbon emission characteristics of urban trip based on multi-layer network modeling (2023)Combining smart card data and household travel survey to analyze jobs–housing relationships in Beijing (2015)Spatial variations in urban public ridership derived from GPS trajectories and smart card data (2018)Increasing the precision of public transit user activity location detection from smart card data analysis via spatial–temporal DBSCAN (2024)Spatial-temporal identification of commuters using trip chain data from non-motorized mode incentive program and public transportation (2024)Understanding metro station areas’ functional characteristics via embedding representation: A case study of shanghai (2025)
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References

  • 2010Redrawing the Map of Great Britain from a Network of Human Interactions424 cited
  • 2015Revealing travel patterns and city structure with taxi trip data408 cited
  • 2010Does Urban Mobility Have a Daily Routine? Learning from the Aggregate Data of Mobile Networks266 cited
  • 2018Exploring changes in the spatial distribution of the low-to-moderate income group using transit smart card data53 cited
  • 2016Portraying Temporal Dynamics of Urban Spatial Divisions with Mobile Phone Positioning Data: A Complex Network Approach36 cited
  • 2020A Method for Bus OD Matrix Estimation Using Multisource Data36 cited
  • 2014Quantifying long-term evolution of intra-urban spatial interactions35 cited
  • 2013Small-world phenomenon of keywords network based on complex network35 cited
  • 2021Revealing spatiotemporal travel demand and community structure characteristics with taxi trip data: A case study of New York City28 cited
  • 2022Spatiotemporal Evolution of Travel Pattern Using Smart Card Data13 cited
  • 2022Exploring Spatial Network Structure of the Metropolitan Circle Based on Multi-Source Big Data: A Case Study of Hangzhou Metropolitan Circle10 cited
  • 2021Geographically Explicit Network Analysis of Urban Living and Working Interaction Pattern in Shenzhen City, South China5 cited

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