基于多源数据的兰州市主城区城市职住空间关系研究

随着中国经济转轨和社会转型,"职住分离"日趋严重,导致城市出现了一系列问题,急需对新的职住关系进行检视。职住关系研究的难点在于如何有效地锁定居住地、工作地,以及居民如何在居住地—工作地之间位移、居住—就业的空间匹配关系。论文以百度POI大数据和热力图为支撑,辅助问卷调查,结合兰州市土地利用现状图,综合应用职住比模型和最近距离等分析方法,多尺度刻画了兰州市主城区的职住关系。结果表明:在城区尺度上,兰州市职住关系总体处于平衡状态,职住平衡型占99.40%,居住倾向型和就业倾向型分别仅占0.12%和0.48%。从城市核心区到边缘区,职住失衡逐渐加重。职住平衡更多地体现在单位型社区上,失衡主要由商业型社区引致。在街道尺度上,职住关系差异明显,绝大多数街道处于职住平衡状态。城市核心区街道以"就业倾向型"为主;边缘区街道表现为"居住倾向型"。

THE STUDY OF JOB-HOUSING RELATIONSHIP OF CITYBASED ON MULTISOURCE BIG DATA-TAKING CENTRAL URBAN AREA OF LANZHOU AS AN EXAMPLEMAIN CITY AREA

“Job” and “housing” are the most basic functions of the city, and the job-housing relationship reflect the order and efficiency of the city. Car dependence, traffic congestion, long commute are torturing many metropolises. To deal with those, different countermeasures have been proposed. Among them, the jobs-housing balance has been considered as one of the most effective. Existing jobs-housing balance studies have relied heavily if not solely on small data. This article argues that Baidu Heat Map and Baidu POI big data can be used to effectively facilitate the jobs- housing balance studies, making them transcend the constraints such as detection of latency and limited geographic/temporal coverage posed by small data. Via a case study of Lanzhou, it shows how Baidu Heat Map and Baidu POI can be processed to derive useful information to advance the aforementioned studies. The results showed that: 1) Within 1 working days, between workplace and residence, population flow have obvious space-time displacement phenomena. 2) On the urban areascale, the job-housing relationship is in a balance state in Lanzhou, the job-housing balance typeccount for 99.40%, residential leading type and employment oriented type only ccount for 0.12% and 0.48% respectively. 3) On the scale of the subdistrict office, there is a significant difference in job-housing relationship, and most subdistrict offices are the Job-housing Balance type. The ssubdistrict offices in the urban core area are mainly "employment orientedtype", while the subdistrict offices in the middle urban areas show "job-housing balance type"; The subdistrict offices in the urban fringe show "residential leadingtype".