SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Investigating the relationship between built environment and spatiotemporal heterogeneity of metro ridership
16 references·0 citing·39 second hop
Investigating the relationship between built environment and spatiotemporal heterogeneity of metro ridership (2025)Investigating the relationship between bu…Introducing the “15-Minute City”: Sustainability, Resilience and Place Identity in Future Post-Pandemic Cities (2021)Introducing the “15-Minute Ci…15-Minute City: Decomposing the New Urban Planning Eutopia (2021)15-Minute City: Decomposing t…The varying patterns of rail transit ridership and their relationships with fine-scale built environment factors: Big data analytics from Guangzhou (2020)The varying patterns of rail …Relationship between eye-level greenness and cycling frequency around metro stations in Shenzhen, China: A big data approach (2020)Relationship between eye-leve…Understanding the impact of built environment on metro ridership using open source in Shanghai (2019)Understanding the impact of b…How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds (2019)How does the station-area bui…Discovering the spatio-temporal impacts of built environment on metro ridership using smart card data (2019)Discovering the spatio-tempor…Spatial variations in urban public ridership derived from GPS trajectories and smart card data (2018)Spatial variations in urban p…Check-in behaviour and spatio-temporal vibrancy: An exploratory analysis in Shenzhen, China (2018)Check-in behaviour and spatio…A geographically and temporally weighted regression model to explore the spatiotemporal influence of built environment on transit ridership (2018)A geographically and temporal…What determines rail transit passenger volume? Implications for transit oriented development planning (2017)What determines rail transit …Measuring TOD around transit nodes - Towards TOD policy (2017)Measuring TOD around transit …How do metro stations integrate with walking environments? Results from walking access within three types of built environment in Beijing (2016)How do metro stations integra…Revealing centrality in the spatial structure of cities from human activity patterns (2015)Revealing centrality in the s…Land use characteristics of subway catchment areas and their influence on subway ridership in Seoul (2015)Land use characteristics of s…What influences Metro station ridership in China? Insights from Nanjing (2013)What influences Metro station…Impacts of Mixed Use and Density on Utilization of Three Modes of Travel: Single-Occupant Vehicle, Transit, and Walking (1994)A micro-analysis of land use and travel in five neighborhoods in the San Francisco Bay Area (1997)Travel demand and the 3Ds: Density, diversity, and design (1997)Nonlinear and synergistic effects of TOD on urban vibrancy: Applying local explanations for gradient boosting decision tree (2021)Activity-based disaggregate travel demand model system with activity schedules (2001)Factors influencing light-rail station boardings in the United States (2004)The New transit town: best practices in transit-oriented development (2004)Spatially varying impacts of built environment factors on rail transit ridership at station level: A case study in Guangzhou, China (2020)Threshold and moderating effects of land use on metro ridership in Shenzhen: Implications for TOD planning (2020)GIS and Multicriteria Decision Analysis (2000)Travel and the Built Environment (2010)Transit oriented development among metro station areas in Shanghai, China: Variations, typology, optimization and implications for land use planning (2018)Elaborating non-linear associations and synergies of subway access and land uses with urban vitality in Shenzhen (2020)Transit-oriented development (TOD) typologies around metro station areas in urban China: A comparative analysis of five typical megacities for planning implications (2020)Spatial Processes, Models and Applications (1983)Interactive Spatial Data Analysis (1995)Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity (1996)Spatiotemporal distribution characteristics and mechanism analysis of urban population density: A case of Xi'an, Shaanxi, China (2018)Portraying the spatial dynamics of urban vibrancy using multisource urban big data (2019)Geographically Weighted Regression: The Analysis of Spatially Varying Relationships (2002)Multiscale geographically and temporally weighted regression: exploring the spatiotemporal determinants of housing prices (2018)A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data (2020)Transit-Oriented Development in the United States: Experiences, Challenges, and Prospects (2004)Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo (2018)Examining the relationship between built environment and metro ridership at station-to-station level (2020)Non-linear associations between built environment and active travel for working and shopping: An extreme gradient boosting approach (2021)Built environments and mode choice: toward a normative framework (2002)Linking urban transport and land use in developing countries (2013)Time-varying and non-linear associations between metro ridership and the built environment (2022)A Pattern Language (1977)The 15-minute city offers a new framework for sustainability, liveability, and health (2022)The 15-minute city: Urban planning and design efforts toward creating sustainable neighborhoods (2022)The x-minute city: Measuring the 10, 15, 20-minute city and an evaluation of its use for sustainable urban design (2022)Transport and social exclusion in London (2000)The Geography of Transport Systems (2020)The 20-minute city: An equity analysis of Liverpool City Region (2021)Barcelona under the 15-Minute City Lens: Mapping the Accessibility and Proximity Potential Based on Pedestrian Travel Times (2022)Crowding valuation in urban tram and bus transportation based on smart card data (2018)Unravel the landscape and pulses of cycling activities from a dockless bike-sharing system (2019)
this work references cited by second hop

References

  • 2021Introducing the “15-Minute City”: Sustainability, Resilience and Place Identity in Future Post-Pandemic Cities1,971 cited
  • 202115-Minute City: Decomposing the New Urban Planning Eutopia576 cited
  • 2018Check-in behaviour and spatio-temporal vibrancy: An exploratory analysis in Shenzhen, China341 cited
  • 2018A geographically and temporally weighted regression model to explore the spatiotemporal influence of built environment on transit ridership333 cited
  • 2015Land use characteristics of subway catchment areas and their influence on subway ridership in Seoul320 cited
  • 2019How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds311 cited
  • 2013What influences Metro station ridership in China? Insights from Nanjing260 cited
  • 2018Spatial variations in urban public ridership derived from GPS trajectories and smart card data251 cited
  • 2017Measuring TOD around transit nodes - Towards TOD policy219 cited
  • 2019Understanding the impact of built environment on metro ridership using open source in Shanghai214 cited
  • 2019Discovering the spatio-temporal impacts of built environment on metro ridership using smart card data195 cited
  • 2015Revealing centrality in the spatial structure of cities from human activity patterns191 cited
  • 2017What determines rail transit passenger volume? Implications for transit oriented development planning

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

169 cited
  • 2020The varying patterns of rail transit ridership and their relationships with fine-scale built environment factors: Big data analytics from Guangzhou157 cited
  • 2020Relationship between eye-level greenness and cycling frequency around metro stations in Shenzhen, China: A big data approach136 cited
  • 2016How do metro stations integrate with walking environments? Results from walking access within three types of built environment in Beijing115 cited
  • Cited by

    No citing works inside the corpus for this window.