Next Article in Journal
Modelling and Simulation of Selected Real Estate Market Spatial Phenomena
Previous Article in Journal
Ensemble Neural Networks for Modeling DEM Error
Previous Article in Special Issue
A Multi-Dimensional Analysis of El Niño on Twitter: Spatial, Social, Temporal, and Semantic Perspectives
Open AccessArticle

Interactions between Bus, Metro, and Taxi Use before and after the Chinese Spring Festival

1
Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong, China
2
Institute of Cartography and Geoinformation, ETH Zurich, 8093 Zurich, Switzerland
3
Department of Geography and Resource Management, and Institute of Space and Earth Information Science, The Chinese University of Hong Kong, Hong Kong, China
4
Department of Human Geography and Spatial Planning, Utrecht University, 3584 CB Utrecht, The Netherlands
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(10), 445; https://doi.org/10.3390/ijgi8100445
Received: 28 August 2019 / Revised: 4 October 2019 / Accepted: 7 October 2019 / Published: 10 October 2019
(This article belongs to the Special Issue Geospatial Methods in Social and Behavioral Sciences)
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. View Full-Text
Keywords: smart card data; taxi GPS trajectories; public transport modes; travel behavior; built environment smart card data; taxi GPS trajectories; public transport modes; travel behavior; built environment
Show Figures

Figure 1

MDPI and ACS Style

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.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop