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Time-varying and non-linear associations between metro ridership and the built environment · Study

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Time-varying and non-linear associations between metro ridership and the built environment

Linchuan Yang, Bingjie Yu, Yuan Liang, Yi Lü, Wenxiang Li

2022-12-28articleTunnelling and Underground Space Technology185 citationsclosed

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Urban Transport and Accessibility Transportation Planning and Optimization Urban Design and Spatial Analysis

Abstract

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Citations in this library

Stored only when both papers are in the corpus — 185 citations exist upstream.

References

1997Travel demand and the 3Ds: Density, diversity, and design

1959How Accessibility Shapes Land Use

2009Influences of Built Environments on Walking and Cycling: Lessons from Bogotá

2021To walk or not to walk? Examining non-linear effects of streetscape greenery on walking propensity of older adults

2011Transit ridership forecasting at station level: an approach based on distance-decay weighted regression

2010Rail-based transit-oriented development: Lessons from New York City and Hong Kong

2020Examining non-linear built environment effects on elderly’s walking: A random forest approach

2018A geographically and temporally weighted regression model to explore the spatiotemporal influence of built environment on transit ridership

Cited by

2023Exploring nonlinear effects of built environment on jogging behavior using random forest

2023Nonlinear, threshold and synergistic effects of first/last-mile facilities on metro ridership

2023Nonlinear effects of built environment features on metro ridership: An integrated exploration with machine learning considering spatial heterogeneity

2023The nonlinear relationship between the active travel behavior of older adults and built environments: A comparison between an inner-city area and a suburban area

2022Multiscale spatial analysis of metro usage and its determinants for sustainable urban development in Shenzhen, China

2023Effects of buffer size on associations between the built environment and metro ridership: A machine learning-based sensitive analysis

2024How does visual environment affect outdoor jogging behavior? Insights from large-scale city images and GPS trajectories

2022Understanding Post-Pandemic Metro Commuting Ridership by Considering the Built Environment: A Quasi-Natural Experiment in Wuhan, China

Details

Year2022

Typearticle

VenueTunnelling and Underground Space Technology

Languageen

Files0 public / 0

Identifiers

doi10.1016/j.tust.2022.104931

openalex_workW4313435862

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