Understanding railway usage behavior with ten million GPS records

Jin，Yanxiu1; Li，Peiran1; Chen，Zhiheng1; Bharule，Shreyas2; Jia，Ning4; Chen，Jinyu1; Song，Xuan1,3; Shibasaki，Ryosuke1; Zhang，Haoran5

2023-02-01

10.1016/j.cities.2022.104117

Cities   影响因子和分区

0264-2751

1873-6084

Considering the essential role of public railway transport in urban planning and development, it is crucial to understand railway travel behavior. With data and survey cost limitations, the railway travel behavior considered in previous studies suffers from a lack of comprehensiveness. Based on millions of GPS records, we analyzed railway usage behavior and then classified 36 stations on the JR Yamanote and JR Chuo lines in Tokyo based on railway usage behavior. To explore the built environment characteristics of each classification and the relationship between railway usage behavior and the built environment, we generated a series of built environment indicators based on the functional attributes around stations. The results show that railway usage behavior in non-secondary catchment areas correlates strongly with the commercial and functional attributes of stations. For non-core catchment areas around stations, consumption level, housing price, and passenger load are the main influencing indicators. Beyond these analysis results, we also present a policy discussion on railway station construction. We found that GPS records constitute valuable information for assessing station usage and neighborhood construction. These fundings can assist urban planners in performing better land use planning and development assessments for future cities.

Big data Built environment Public transit Railway usage behavior Tokyo

SSCI

英语

其他

Urban Studies

Urban Studies

WOS:000907119600001

ELSEVIER SCI LTD

SOCIAL SCIENCES, GENERAL

2-s2.0-85144829335

Scopus

1.Center for Spatial Information Science,The University of Tokyo,Kashiwa-shi,5-1-5 Kashiwanoha, Chiba,277-8568,Japan
2.LocationMind Inc.,Tokyo,3-5-2 Iwamotocho, Chiyoda-ku,101-0032,Japan
3.SUSTech-UTokyo Joint Research Center on Super Smart City,Department of Computer Science and Engineering,Southern University of Science and Technology (SUSTech),Shenzhen,China
4.College of Management and Economics,Tianjin University,Tianjin,China
5.School of Urban Planning & Design,Peking University,Shenzhen,China

Jin，Yanxiu,Li，Peiran,Chen，Zhiheng,et al. Understanding railway usage behavior with ten million GPS records[J]. Cities,2023,133.

Jin，Yanxiu.,Li，Peiran.,Chen，Zhiheng.,Bharule，Shreyas.,Jia，Ning.,...&Zhang，Haoran.(2023).Understanding railway usage behavior with ten million GPS records.Cities,133.

Jin，Yanxiu,et al."Understanding railway usage behavior with ten million GPS records".Cities 133(2023).