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作者

Yanxiu Jin;Peiran Li;Zhiheng Chen;Shreyas Bharule;Ning Jia;Jinyu Chen;Xuan Song;Ryosuke Shibasaki;Haoran Zhang

来源

CITIES,Vol.134,Issue1,Article 104117

语言

英文

关键字

作者单位

Center for Spatial Information Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba 277-8568, Japan;LocationMind Inc., 3-5-2 Iwamotocho, Chiyoda-ku, Tokyo 101-0032, Japan;SUSTech-UTokyo Joint Research Center on Super Smart City, Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China;College of Management and Economics, Tianjin University, Tianjin, China;School of Urban Planning & Design, Peking University, Shenzhen, China;Center for Spatial Information Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba 277-8568, Japan;LocationMind Inc., 3-5-2 Iwamotocho, Chiyoda-ku, Tokyo 101-0032, Japan;SUSTech-UTokyo Joint Research Center on Super Smart City, Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech), Shenzhen, China;College of Management and Economics, Tianjin University, Tianjin, China;School of Urban Planning & Design, Peking University, Shenzhen, China;Institut d'Estudis Regionals i Metropolitans de Barcelona (IERMB), Autonomous University of Barcelona, Plaça del Coneixement, Edifici MRA, Planta 2, Campus UAB, 08193 Bellaterra, Spain;TURBA Lab, Internet Interdisciplinary Institute (IN3), Universitat Oberta de Catalunya, Barcelona, Spain;School of Economics, Peking University, 5 Summer Palace Road Street, Beijing 100871, China;College of Earth Sciences, Jilin University, Changchun 130061, China;The Bartlett School of Planning, University College London, Central House, 14 Upper Woburn Place, London WC1H 0NN, UK;School of Urban Design, Wuhan University, No. 299 Bayi Road, Wuchang District, Wuhan 430072, China;Hubei Habitat Environment Research Centre of Engineering and Technology, Wuhan, China;Virginia Center for Housing Research (VCHR) at Virginia Tech, United States of America;École supérieure d'aménagement du territoire et de développement régional (ÉSAD) Laval University Quebec City (QC), Canada

摘要

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.