Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/81733
Title: Interactions between bus, metro, and taxi use before and after the Chinese spring festival
Authors: Huang, JW 
Liu, XT 
Zhao, PX
Zhang, JW 
Kwan, MP
Keywords: Smart card data
Taxi gPS trajectories
Public transport modes
Travel behavior
Built environment
Issue Date: 2019
Publisher: Molecular Diversity Preservation International (MDPI)
Source: ISPRS international journal of geo-information, 10 Oct. 2019, v. 8, no. 10, 445, p. 1-18 How to cite?
Journal: ISPRS international journal of geo-information 
Abstract: Public transport plays an important role in developing sustainable cities. A better understanding of how different public transit modes (bus, metro, and taxi) interact with each other will provide better sustainable strategies to transport and urban planners. However, most existing studies are either limited to small-scale surveys or focused on the identification of general interaction patterns during times of regular traffic. Transient demographic changes in a city (i.e., many people moving out and in) can lead to significant changes in such interaction patterns and provide a useful context for better investigating the changes in these patterns. Despite that, little has been done to explore how such interaction patterns change and how they are linked to the built environment from the perspective of transient demographic changes using urban big data. In this paper, the tap-in-tap-out smart card data of bus/metro and taxi GPS trajectory data before and after the Chinese Spring Festival in Shenzhen, China, are used to explore such interaction patterns. A time-series clustering method and an elasticity change index (ECI) are adopted to detect the changing transit mode patterns and the underlying dynamics. The findings indicate that the interactions between different transit modes vary over space and time and are competitive or complementary in different parts of the city. Both ordinary least-squares (OLS) and geographically weighted regression (GWR) models with built environment variables are used to reveal the impact of changes in different transit modes on ECIs and their linkage with the built environment. The results of this study will contribute to the planning and design of multi-modal transport services.
URI: http://hdl.handle.net/10397/81733
EISSN: 2220-9964
DOI: 10.3390/ijgi8100445
Rights: © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
The following publication Huang, J.; Liu, X.; Zhao, P.; Zhang, J.; Kwan, M.-P. Interactions between Bus, Metro, and Taxi Use before and after the Chinese Spring Festival. ISPRS Int. J. Geo-Inf. 2019, 8, 445, 1-18 is available at https://dx.doi.org/10.3390/ijgi8100445
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