详情

原文传递 Identifying Urban Functional Areas and Their Dynamic Changes in Beijing: Using Multiyear Transit Smart Card Data

题名：	Identifying Urban Functional Areas and Their Dynamic Changes in Beijing: Using Multiyear Transit Smart Card Data
正文语种：	eng
作者：	Wang, Zijia;Liu, Haixu;Zhu, Yadi;Zhang, Yuerong;Basiri, Anahid;Buettner, Benjamin;Gao, Xing;Cao, Mengqiu
作者单位：	Beijing Jiaotong Univ Sch Civil & Architectual Engn Dept Highway & Railway Engn 3 Shangyuan Village Beijing 100089 Peoples R China;Beijing Urban Construct Design & Dev Grp Co Ltd Transportat Res Ctr 5 Fuchengmen Beidajie Beijing 100032 Peoples R China;Beijing Jiaotong Univ Sch Civil & Architectual Engn Dept Highway & Railway Engn 3 Shangyuan Village Beijing 100089 Peoples R China;UCL Bartlett Sch Planning Cent House 14 Upper Woburn Pl London WC1H 0NN England\|UCL Bartlett Ctr Adv Spatial Anal 90 Tottenham Court Rd London W1T 4TJ England;Univ Glasgow Sch Geog & Earth Sci Glasgow G12 8QQ Lanark Scotland;Tech Univ Munich Dept Civil Geo & Environm Engn Res Grp Accessibil Planning Arcisstr 21 D-80333 Munich Germany;UCL Bartlett Sch Planning Cent House 14 Upper Woburn Pl London WC1H 0NN England;Univ Westminster Sch Architecture & Cities 35 Marylebone Rd London NW1 5LS England
关键词：	Urban functional areas;Dynamic changes;Urban planning;Travel pattern;Smart card data;Beijing
摘要：	A growing number of megacities have been experiencing changes to their landscape due to rapid urbanization trajectories and travel behavior dynamics. Therefore, it is of great significance to investigate the distribution and evolution of a city's urban functional areas over different periods of time. Although the smart card automated fare collection system is already widely used, few studies have used smart card data to infer information about changes in urban functional areas, particularly in developing countries. Thus, this research aims to delineate the dynamic changes that have occurred in urban functional areas based on passengers' travel patterns, using Beijing as a case study. We established a Bayesian framework and applied a Gaussian mixture model derived from transit smart card data in order to gain insight into passengers' travel patterns at station level and then identify the dynamic changes in their corresponding urban functional areas. Our results show that Beijing can be clustered into five different functional areas based on the analysis of corresponding transit station functions: multimodal interchange hub and leisure area; residential area; employment area; mixed but mainly residential area; and mixed residential and employment area. In addition, we found that urban functional areas have experienced slight changes between 2014 and 2017. The findings can be used to inform urban planning strategies designed to tackle urban spatial structure issues, as well as guiding future policy evaluation of urban landscape pattern use.
出版年：	2021
期刊名称：	Journal of Urban Planning and Development
卷：	147
期：	2