利用公交刷卡数据分析北京职住关系和通勤出行

基于位置服务(Location Based Service,LBS)技术为研究城市系统的时空动态规律提供了新的视角,已往多基于移动通讯(GSM)、全球定位系统(GPS)、社会化网络(SNS)和无线宽带热点(Wi-Fi)数据开展研究,但少有研究利用公交IC卡刷卡数据进行城市系统分析.普遍存在的LBS数据虽然具有丰富的时间和空间信息,但缺乏社会维度信息,使其应用范围受到一定限制.本文基于2008年北京市连续一周的公交IC卡(Smart Card Data,SCD)刷卡数据,结合2005年居民出行调查、地块级别的土地利用图,识别公交持卡人的居住地、就业地和通勤出行,并将识别结果在公交站点和交通分析小区(TAZ)尺度上汇总:①将识别的通勤出行分别从通勤时间和距离角度,与居民出行调查数据和其他已有北京相关研究进行对比,显示较好的吻合性；②对来自3大典型居住区和去往6大典型办公区的通勤出行进行可视化并对比分析；③对全市基于公交的通勤出行进行可视化,并识别主要交通流方向.本研究初步提出了从传统的居民出行调查和城市GIS数据建立规则,用于SCD数据挖掘的方法,具有较好的可靠性.

Identifying Commuting Pattern of Beijing Using Bus Smart Card Data

This paper combines the one-week bus smart card data (SCD) and one-day household travel survey as well as the parcel-level land use map for identifying jobs-housing places and commuting trips in the Beijing Metropolitan Area with an area of 16,410 square kilometers. The identification result is aggregated in the bus stop and traffic analysis zone (TAZ) levels, respectively. In particular, commuting trips with commuting time and distance attached from three typical residence communities and those to five typical business zones are mapped and compared with each other to analyze commuting patterns of Beijing. The identified commuting trips are compared with those in the household travel survey in terms of commuting time and distance, indicating that our results are coincident with the survey significantly. Our approach is proved to have its potential in identifying more solid identification result based on rules extracted from existing surveys or censuses.