基于地铁刷卡数据的城市通勤与就业中心吸引范围研究

发布时间：2018-05-23 06:38

本文选题：地铁刷卡数据 + 通勤　；参考：《人文地理》2017年03期

【摘要】：地理时空大数据为通勤行为和城市空间结构研究带来了新的机遇。基于一周地铁刷卡数据,采用出行链(trip-chain)数据模型对用户一天的出行进行描述,建立通勤识别规则,识别出上海市域的职住空间和通勤格局。上海市域平均通勤时间为35分钟,通勤主流向是向心流,说明上海市域依旧表现出强单中心结构。市域就业单中心与居住郊区化并存,中心城区多核心就业已经形成。在此基础上进一步分析中心城区13个就业(次)中心的吸引范围、模式以及在整个市域的影响力,讨论多中心发展对职住平衡与通勤消减的意义。结果表明:多中心发展有利于城市通勤的合理分配,虽然次中心的平均通勤时间不一定减少,但是就业(次)中心已经表现出对邻近地区的通勤吸引和对主中心的通勤分流。
[Abstract]:Geo-temporal big data brings new opportunities for the study of commuting behavior and urban spatial structure. Based on the weekly subway card swipe data, the trip chain trip-chain data model is used to describe the daily trip of the user, and the commuting identification rules are established to identify the occupation and residence space and commuting pattern in Shanghai. The average commuting time in Shanghai is 35 minutes. City employment single center and residential suburbanization coexist, the central city area multi-core employment has been formed. On this basis, the attraction scope, mode and influence in the whole city of 13 employment centers in central urban area are analyzed, and the significance of multi-center development to the balance of occupation and housing and the decrease of commuting is discussed. The results show that the multi-center development is beneficial to the rational distribution of urban commuting. Although the average commuting time of the secondary center is not necessarily reduced, the employment (secondary) center has shown the attraction of commuting to the adjacent area and the commuting diversion to the main center.
【作者单位】：华东师范大学地理科学学院;
【基金】：国家自然科学基金项目(41271441,41401173)
【分类号】：C912.81

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