"流体城市"视角下职住空间格局及变化机理研究——基于城市计算方法

The research use of urban multi-source sensing technology to extract jobs-housing features combined with socio-economic attribute data and Internet big data. The research explore the evaluation of urban jobs-housing balance and the relationship between jobs-housing and planning, transportation, housing prices, economic, environmental, industrial layout and their impact on the level of generated jobs-housing, which to clarify the process of urbanization on multi-source factors affecting changes in the urban structure response mechanism, and to provide a scientific basis for urban development plans for the construction of city managers in the wisdom of the city carried out the decision to Research by various types of complex phenomena of human activities in space and time-driven traffic, move, commute to provide a solid theoretical and technical basis...This research covering three areas: (1) big data oriented multi-view jobs-housing balance evaluation models; (2) jobs-housing characteristics extraction based on multi-source heterogeneous city data; (3) the pattern and the mechanism of change of the jobs-housing features...Research on this subject is to carry out analysis of urban function zoning, infrastructure, urban transport planning and urban land use planning studies, and to guide the sustainable urban construction of theoretical significance and application value. Applicants for further projects and research location of City team-building methods in an efficient use of resources and improve the quality of life of residents as the goal of wisdom, understanding scientific rationality urban function zoning, road network, infrastructure layout, a better understanding of urbanization and the impact on the lifestyle of the residents living environment to provide a theoretical basis and technical support.

本课题利用城市多源感知技术提取职住特征，结合社会经济属性数据、互联网大数据，探讨城市职住平衡的评价指标，以及规划、交通、房价、经济、环境、产业布局等多种关系要素对职住性产生的影响，阐明城市化进程中城市结构对多源影响要素的变化响应机制，为城市管理者在为构建智慧城市而进行的城市发展规划中的决策提供科学的理论依据。 本课题研究内容涉及三个方面：（1）面向大数据的多视角职住平衡测度模型；（2）基于多源异构城市数据的职住特征提取；（3）流体城市视角下的职住特征格局形成与变化机理。 本课题的研究是开展城市功能区划分析、城市交通规划和城市土地利用规划等研究的基础，对指导我国的可持续城市建设具有十分重要的理论意义和应用价值。

本课题利用城市多源感知技术提取职住特征，结合社会经济属性数据、互联网大数据，探讨城市职住平衡的评价指标，以及规划、交通、房价、经济、环境、产业布局等多种关系要素对职住性产生的影响，阐明城市化进程中城市结构对多源影响要素的变化响应机制，为城市管理者在为构建智慧城市而进行的城市发展规划中的决策提供科学的理论依据。 .本课题研究内容涉及三个方面：（1）面向大数据的多视角职住平衡测度模型；（2）基于多源异构城市数据的职住特征提取；（3）流体城市视角下的职住特征格局形成与变化机理。.本课题研究结果如下：（1）分别从个体、企业、城市三个角度考查测度职住平衡指标构建了面向大数据的多视角职住平衡测度模型；（2）基于机器学习的多元异构城市数据职住特征提取，包括开发了基于中国高分系列卫星的城市用地信息提取人工智能算法和基于出租车轨迹数据的职住平衡指数预测模型；（3）“流空间”视角下基于MGWR模型的职住特征格局形成与变化机理。研究以杭州市作为示范区，重点研究了该市的职住平衡性，同时发现区位因素、交通可达性、居民受教育水平、居住成本是影响职住平衡性的首要因素。.本课题的研究是开展城市功能区划分析、城市交通规划和城市土地利用规划等研究的基础，对指导我国的可持续城市建设具有十分重要的理论意义和应用价值。