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Revealing Spatial-Temporal Characteristics and Patterns of Urban Travel: A Large-Scale Analysis and Visualization Study with Taxi GPS Data

1
School of Environment, Beijing Normal University, Beijing 100875, China
2
Institute of Public Safety Research, Department of Engineering Physics, Tsinghua University, Beijing 100084, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(6), 257; https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi8060257
Received: 16 April 2019 / Revised: 26 May 2019 / Accepted: 28 May 2019 / Published: 30 May 2019
Mobility and spatial interaction data have become increasingly available due to the widespread adoption of location-aware technologies. Examples of mobile data include human daily activities, vehicle trajectories, and animal movements. In this study we focus on a special type of mobility data, i.e., origin–destination (OD) pairs, and propose a new adapted chord diagram plot to reveal the urban human travel spatial-temporal characteristics and patterns of a seven-day taxi trajectory data set collected in Beijing; this large scale data set includes approximately 88.5 million trips of anonymous customers. The spatial distribution patterns of the pick-up points (PUPs) and the drop-off points (DOPs) on weekdays and weekends are analyzed first. The maximum of the morning and the evening peaks are at 8:00–10:00 and 17:00–19:00. The morning peaks of taxis are delayed by 0.5–1 h compared with the commuting morning peaks. Second, travel demand, intensity, time, and distance on weekdays and weekends are analyzed to explore human mobility. The travel demand and high-intensity travel of residents in Beijing is mainly concentrated within the 6th Ring Road. The residents who travel long distances (>10 km) and for a long time (>60 min) mainly from outside the 6th Ring Road and the surrounding new towns of Beijing. The circular structure of the travel distance distribution also confirms the single-center urban structure of Beijing. Finally, a new adapted chord diagram plot is proposed to achieve the spatial-temporal scale visualization of taxi trajectory origin–destination (OD) flows. The method can characterize the volume, direction, and properties of OD flows in multiple spatial-temporal scales; it is implemented using a circular visualization package in R (circlize). Through the visualization experiment of taxi GPS trajectory data in Beijing, the results show that the proposed visualization technology is able to characterize the spatial-temporal patterns of trajectory OD flows in multiple spatial-temporal scales. These results are expected to enhance current urban mobility research and suggest some interesting avenues for future research. View Full-Text
Keywords: human travel; travel pattern; OD flow; the chord diagram plot; taxi data human travel; travel pattern; OD flow; the chord diagram plot; taxi data
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MDPI and ACS Style

Wang, H.; Huang, H.; Ni, X.; Zeng, W. Revealing Spatial-Temporal Characteristics and Patterns of Urban Travel: A Large-Scale Analysis and Visualization Study with Taxi GPS Data. ISPRS Int. J. Geo-Inf. 2019, 8, 257. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi8060257

AMA Style

Wang H, Huang H, Ni X, Zeng W. Revealing Spatial-Temporal Characteristics and Patterns of Urban Travel: A Large-Scale Analysis and Visualization Study with Taxi GPS Data. ISPRS International Journal of Geo-Information. 2019; 8(6):257. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi8060257

Chicago/Turabian Style

Wang, Huihui, Hong Huang, Xiaoyong Ni, and Weihua Zeng. 2019. "Revealing Spatial-Temporal Characteristics and Patterns of Urban Travel: A Large-Scale Analysis and Visualization Study with Taxi GPS Data" ISPRS International Journal of Geo-Information 8, no. 6: 257. https://0-doi-org.brum.beds.ac.uk/10.3390/ijgi8060257

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