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

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

doi:10.1016/j.tust.2022.104931

Cited by 92 publications

(14 citation statements)

References 54 publications

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“…Population density and distance from downtown have an enhanced impact on ridership during peak hours, which is similar to the finding of Yang et al(2023) and Zhao et al(2014) . This is attributed primarily to an increasing trend in ridership within a certain travel distance in the stations with high population density during the peak periods due to the necessary commuting activities like going to work, attending school and seeking medical treatment (Ren et al2021).…”

Section: 21importance Of Shap Variablessupporting

confidence: 81%

Nonlinear relationships between built environmental characteristics and ridership in Xi'an metrostation

Hou

Duan

et al. 2023

Preprint

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In recent years, Xi'an metro construction has been progressing rapidly, becoming the primary mode of urban green public transportation. Since the ridership of the metro is closely linked to the characteristics of its surrounding built environment, a key problem in promoting the benign development between the two is to explore the spatiotemporal distributional difference in ridership and its influencing factors. In this study, the "5D" characteristics of built environment are described by density, diversity, design, destination and distance variables. The spatiotemporal distribution characteristics of ridership are analyzed via Arc GIS and Python, while the nonlinear relationships between ridership and built environment of 106 metro stations of downtown Xi'an, as well as relevant threshold effects are revealed via Shapley additive explanations with gradient boosted decision tree (GBDT-SHAP). The results show that: (1) Xi'an metro travel presents a medium-short spatiotemporal distribution, and the ridership network is characterized by strong center-spillover. (2) The nonlinear relationship between built environment and ridership is ubiquitous and presents a threshold effect. The impact threshold of bus stop density on ridership is 4-6 pcs/km2, the impact threshold of road network density is roughly 4-5 km/km2, and the effective threshold of building density does not exceed 20%. (3) The positive impact of POI facility density on peak ridership is stronger than that at flat hours. Variables like land use mixture, population density and distance from downtown have a time-driven effect on the ridership, whose importance and influence change with time. This study provides a better understanding of the spatiotemporal impact of Xi'an's built environment on metro travel, which is of profound significance for the coordinated development between the city and metro construction.

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Section: 21importance Of Shap Variablessupporting

confidence: 81%

Nonlinear relationships between built environmental characteristics and ridership in Xi'an metrostation

Hou

Duan

et al. 2023

Preprint

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“…SHAP can more intuitively represent the local positive or negative effect of all samples of a variable on the model compared with the previous variable importance ranking model and further decompose it into the interaction between the main local effect of the variable and other variables. Meanwhile, PDP can describe the degree of correlation change of variables in different value ranges without assuming a linear correlation ( Yang et al, 2023 ), which helps in improving the interpretability of the model.…”

Section: Methodsmentioning

confidence: 99%

Exploring the non-linear relationship and synergistic effect between urban built environment and public sentiment integrating macro- and micro-level perspective: a case study in San Francisco

He,

Yu,

et al. 2024

Front. Psychol.

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Public sentiment can effectively evaluate the public’s feelings of well-being in the urban environment and reflect the quality of the spatial environment to a certain extent. Previous studies on the relationship between public sentiment and urban built environmental factors have yielded meaningful results. However, few studies have focused on the effect of micro-built environment on public sentiment at the street level, which directly shapes people’s perceptions. In addition, the nonlinear relationship and synergistic effect among urban built environmental factors have been commonly disregarded in previous studies, resulting in an incomplete understanding of the impact of urban built environment on public emotions. Therefore, this paper takes San Francisco as a study case to explore the complex relationship between urban built environmental factors and public emotions. Specifically, this paper measures the polarity of public emotions through sentiment analysis on Twitter data, establishes a comprehensive built environment index system from both macro- and micro- perspectives, and subsequently explores the complex relationship between the urban built environment and public sentiment through the OLS model and Shapley Additive Explanation algorithm. Results show that: (1) micro-built environmental factors have a significant influence on public emotion, although they have been frequently ignored. (2) Public sentiment tends to be more positive in areas with recreation facilities, mixed land use, rich street view visual environment, suitable thermal and acoustic environment, balanced income, and a suitable degree of high population density. (3) A nonlinear relationship and threshold effect exist between the built environmental variables and the semantic orientations of public emotion. Environment improvement strategies based on the synergic effect between variables can effectively promote the generation of positive emotions. Our empirical findings can offer valuable insights to promote feelings of well-being and foster an urban development approach through strategic interventions within the urban built environment.

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“…Future studies should consider children's evacuation behavior in a different context and focus on the commonly observed emergency behaviors among children at different ages. The other point of the spectrum of the vulnerable population during emergencies and evacuation is elderlies due to their physical limitations [105][106][107]. Therefore, elderlies' emergency decision-making and evacuation behavior can be a subject to be studied by future researchers.…”

Section: Recommendation For Future Studymentioning

confidence: 99%

Students' evacuation behavior during an emergency at schools: A systematic literature review

Bahmani

Yang

et al. 2023

International Journal of Disaster Risk Reduction

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

Cited by 92 publications

References 54 publications

Nonlinear relationships between built environmental characteristics and ridership in Xi'an metrostation

Nonlinear relationships between built environmental characteristics and ridership in Xi'an metrostation

Exploring the non-linear relationship and synergistic effect between urban built environment and public sentiment integrating macro- and micro-level perspective: a case study in San Francisco

Students' evacuation behavior during an emergency at schools: A systematic literature review

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