上海市职住关系和通勤特征分析研究 ——基于轨道交通客流数据视角

Study on Job-Housing Relationship and Characteristic of Commuting in Shanghai: Based on the Perspective of Rail Transit Passenger Flow Data

许志榕
上海市城市规划设计研究院 助理工程师，硕士

摘要: 交通卡刷卡数据、手机信令数据、空间定位信息（GPS）等大数据的出现为城市与人的行为研究提供了数据支撑。基于2015年4月上海市公共交通卡刷卡数据，创建一般出行及虚拟换乘规则，建立上海轨道交通出行数据模型，并结合轨道交通网络空间数据模型，识别基于地铁出行的城市居民居住地、就业地和包括通勤时间、距离、空间分布等在内的通勤特征信息，并对典型就业中心和大型居住社区周边站点进行应用分析。研究表明，基于地铁的通勤出行者有130多万持卡人，平均通勤时间34.82 min，平均通勤距离为12.4 km；居住地在内环内、内外环间及外环外各站的持卡人相差不多，但就业地则有近2/3分布于内环内；通勤出行方向呈现明显的向心性；典型就业中心辐射范围广泛，平均通勤时间越往市中心越低；各大型居住社区的地铁通勤量相差很大，通勤去向并不集中于内环内。

Abstract: Big Data such as transportation card data, cell phone data, Global Position System provides data support for the study on the behavior of city and people. Using Shanghai public transportation card data in April 2015, and creating general travel rules and virtual transfer rules, this study establishes Shanghai rail transit trip data model. Combined with the spatial data of rail transit network, the study identifies jobs-housing relationship and characteristics of commuting such as time, distance and spatial distribution in Shanghai. Then the study makes an application of analyzing typical employment centers and large-sized residential communities. The research identifies more than 1.3 million commuters, with average commuting time of 34.82 minutes and average commuting distance of 12.4 kilometers. The number of residences is about the same in the inner ring, outside the outer ring and between the two rings. But the percentage of employment in the inner ring makes up 2/3. The direction of commuter travel is obviously centripetal. The typical employment center has a wide range of radiation, and the average commuting time is lower in the center. The amount of commuting in large-sized residential communities is different, and the commuter direction is not concentrated in the inner ring.

关键词：交通卡刷卡数据、职住关系、通勤特征、上海

Keyword: Transportation card data，Job-housing relationship，Characteristics of commuting，Shanghai

中图分类号：中图分类号TU981

文献标识码: 文献标识码A

[1]龙瀛，孙立君，陶遂. 基于公共交通智能卡数据的城市研究综述[J]. 城市规划学刊，2015（3）：70-77.
LONG Ying, SUN Lijun, TAO Sui. A review of urban studies based on transit smart card data[J]. Urban Planning Forum, 2015 (3): 70-77.
[2]Roth C, Kang S M, Batty M, et al. Structure of urban movements: polycentric activity and entangled hierarchical flows[J]. Plos One, 2011, 6(1): e15923.
[3]龙瀛，张宇，崔承印. 利用公交刷卡数据分析北京职住关系和通勤出行[J]. 地理学报，2012,67（10）：1339-1352.
LONG Ying, ZHANG Yu, CUI Chengyin. Identifying commuting pattern of Beijing using bus smart card data[J]. Acta Geographica Sinica, 2012, 67 (10): 1339-1352.
[4]Zhou J, Long Y. Jobs-housing balance of bus commuters in Beijing exploration with large-scale synthesized smart card data[C]//Transportation Research Board 92nd Annual Meeting. Washington, DC. 2014.
[5]钮心毅，丁亮. 利用手机数据分析上海市域的职住空间关系：若干结论和讨论[J]. 上海城市规划，2015（2）：39-43.
NIU Xinyi, DING Liang. Analyzing job-housing spatial relationship in Shanghai using mobile phone data: Some conclusions and discussions[J]. Shanghai Urban Planning, 2015 (2): 39-43.
[6]上海市第五次综合交通调查联席会议办公室. 上海市第五次综合交通调查成果报告[R]. 2015.
Office of the Joint Conference of the 5th Shanghai Comprehensive Transport Survey. 5th Shanghai comprehensive transport survey[R]. 2015.
[7]上海市规划和国土资源管理局，上海市城市规划设计研究院. 大型居住社区规划评估[R]. 2014.
Shanghai Urban Planning and Land Resources Administration Bureau, Shanghai Urban Planning and Design Research Institute. Planning and evaluation of large-sized residential communities[R]. 2014.