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Intelligent Development Research on Job-Housing Space in Chinese Metropolitan Areaud under the Background of Rapid Urbanization

机译:中国大都市区就业空间智能化发展研究 在快速城市化的背景下

摘要

Under the impact of regional integration and rapid urbanization, Chinese metropolitan area is confronted with the pressure brought by further massiveness, high density and continuous development. The existing layout of job-housing space balance in cities has been further spread and aggravated, which leads to a series of problems including traffic jams and air pollution, etc. This thesis excavates, analyzes and integrates the city residents’ action trajectory data in various heterogeneous cities through the intelligent transportation data platform of metropolitan area. Furthermore, the research also extracts the intelligent knowledge on the aspect of urban job-housing space, identifies and analyzes its characteristics effectively. udThis thesis takes Beijing-Tianjin-Hebei metropolitan area as the research object to carry out intelligent analysis on working and residential space in main cities. We can identify residents' commuting behaviors with multi-source location perception data. Firstly, the GPS trajectory data of large-scale taxi will be utilized, and the transportation behaviors and characteristics of taxi will be assumed as the urban residents’ trip behaviors. Then the research of urban space-time structure and residents’ activities hot spots will be carried out from the macro perspective. Secondly, a residents’ trip survey method combining mobile phone location and internet feedback will be put forward. Aiming at the location Microblog data, the characteristics of residents’ workplaces and residences could be identified with fuzzy mathematical method. During the identification process, the individual behavior patterns obtained from the resident trip survey data will be used as the recognition feature. udThrough the analysis, We discovered that the data mining method of the residents’ action trajectory is feasible for the study of job-housing space. The study shows that the key factor influencing the job-housing balance in metropolitan area is the improvement of disperse urbanization life-style which takes family as a single unit. It also puts forwards the future ternary development mode of “employment-residence-public service” of job-housing balance in Chinese metropolitan area. The research also discovers a measurement method of excess commuting to develop the commuting efficiency in job-housing space. Furthermore, through the research on excess commuting degree of main cities in Beijing-Tianjin-Hebei metropolitan area by utilizing the commuting behaviors extraction result of Microsoft data, the correlation factor of characteristic attributes and job-housing separation phenomenon in urban community could be found. Finally, the intelligent development characteristics of job-housing space in metropolitan area will be discussed by combining the geographical visualization method and taxi trajectory mining result.
机译:在区域一体化和快速城市化的影响下,中国大都市地区面临着更大的规模,更高的密度和持续发展所带来的压力。城市现有的就业空间平衡布局进一步扩大和加剧,导致交通拥堵,空气污染等一系列问题。本文对城市居民的行动轨迹数据进行了挖掘,分析和整合。通过大城市地区的智能交通数据平台实现异构城市。此外,研究还从城市就业空间方面提取了智能知识,有效地识别和分析了其特征。 ud本文以京津冀都市圈为研究对象,对主要城市的工作和居住空间进行了智能分析。我们可以通过多源位置感知数据来识别居民的通勤行为。首先,利用大型出租车的GPS轨迹数据,将出租车的交通行为和特征作为城市居民的出行行为。然后从宏观的角度对城市时空结构和居民活动热点进行研究。其次,将提出结合手机位置和互联网反馈的居民出行调查方法。针对位置微博数据,可以通过模糊数学方法识别居民的工作场所和住所特征。在识别过程中,将从居民出行调查数据中获得的个人行为模式用作识别特征。 ud通过分析,我们发现居民行动轨迹的数据挖掘方法对于研究工作居住空间是可行的。研究表明,影响大都市地区工作与住房平衡的关键因素是以家庭为单位的分散城市化生活方式的改善。提出了中国大都市就业平衡的“就业-居住-公共服务”三元发展模式。研究还发现了一种过量通勤的测量方法,以提高工作空间中的通勤效率。此外,通过利用微软数据的通勤行为提取结果,对京津冀都市圈主要城市的过剩通勤程度进行研究,可以发现城市社区特征属性与工作-住房分离现象的相关因素。最后,结合地理可视化方法和滑行轨迹挖掘结果,讨论了大都市地区工作空间的智能发展特征。

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