Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds
https://orcid.org/0000-0001-9560-8585
https://orcid.org/0000-0002-4403-9762
Abstract 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.
How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds
https://orcid.org/0000-0001-9560-8585
https://orcid.org/0000-0002-4403-9762
Abstract 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.
How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds
https://orcid.org/0000-0001-9560-8585
https://orcid.org/0000-0002-4403-9762
Abstract 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.
How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds
Ding, Chuan (Autor:in) / Cao, Xinyu (Autor:in) / Liu, Chao (Autor:in)
Journal of Transport Geography ; 77 ; 70-78
22.04.2019
9 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Metrorail Trends and Markets: Synopsis of Recent Ridership Growth
| British Library Online Contents | 2009
| British Library Online Contents | 2015
| IuD Bahn | 1997