How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds

To inform the station-area planning, previous studies use direct ridership models to examine the relationship between the built environment around stations and transit ridership. Based on this framework, this study innovatively applies gradient boosting decision trees to investigate the non-linear e...

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Bibliographic Details
Published in:Journal of transport geography Vol. 77; pp. 70 - 78
Main Authors: Ding, Chuan, Cao, Xinyu, Liu, Chao
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 01.05.2019
Elsevier BV
Subjects:
Built environment
Bus stops
Decision trees
Demographic variables
Demography
Direct ridership model
Land use
Land use management
Land use planning
Metropolitan areas
Public transportation
Ridership
Transit ridership
Transit-oriented development
Travel demand
Urban environments
Travel demand
Transit ridership
Direct ridership model
Transit-oriented development
Land use
ISSN:0966-6923, 1873-1236
Online Access:Get full text
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Summary:To inform the station-area planning, previous studies use direct ridership models to examine the relationship between the built environment around stations and transit ridership. Based on this framework, this study innovatively applies gradient boosting decision trees to investigate the non-linear effects of built environment variables on station boarding. Using the Metrorail data in the Washington metropolitan area, we found that station-area built environment characteristics collectively contribute to 34% of the predictive power for Metrorail ridership, after controlling for transit service factors and demographics. Built environment variables show threshold effects on Metrorail ridership. We further identified their effective ranges, guiding land use planning around stations. This study highlights the roles of compact and mixed land use development, the number of bus stops, and car ownership in determining the station-level ridership.
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ISSN:0966-6923
1873-1236
DOI:10.1016/j.jtrangeo.2019.04.011