Incorporating Smart Card Data in Spatio-Temporal Analysis of Metro Travel Distances

Enhui Chen, Zhirui Ye and Hui Bi
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Enhui Chen: School of Transportation, Southeast University, 2 Sipailou, Nanjing 210096, China
Zhirui Ye: School of Transportation, Southeast University, 2 Sipailou, Nanjing 210096, China
Hui Bi: School of Transportation, Southeast University, 2 Sipailou, Nanjing 210096, China

Sustainability, 2019, vol. 11, issue 24, 1-22

Abstract: The primary objective of this study is to explore spatio-temporal effects of the built environment on station-based travel distances through large-scale data processing. Previous studies mainly used global models in the causal analysis, but spatial and temporal autocorrelation and heterogeneity issues among research zones have not been sufficiently addressed. A framework integrating geographically and temporally weighted regression (GTWR) and the Shannon entropy index (SEI) was thus proposed to investigate the spatio-temporal relationship between travel behaviors and built environment. An empirical study was conducted in Nanjing, China, by incorporating smart card data with metro route data and built environment data. Comparative results show GTWR had a better performance of goodness-of-fit and achieved more accurate predictions, compared to traditional ordinary least squares (OLS) regression and geographically weighted regression (GWR). The spatio-temporal relationship between travel distances and built environment was further analyzed by visualizing the average variation of local coefficients distributions. Effects of built environment variables on metro travel distances were heterogeneous over space and time. Non-commuting activity and exurban area generally had more influences on the heterogeneity of travel distances. The proposed framework can address the issue of spatio-temporal autocorrelation and enhance our understanding of impacts of built environment on travel behaviors, which provides useful guidance for transit agencies and planning departments to implement targeted investment policies and enhance public transit services.

Keywords: metro; travel distance; smart card data; built environment; spatio-temporal analysis; heterogeneity (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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