Research on an Evaluation Method for the Job-Housing Spaces of Megacities Using Different Scales Based on Multisource Data Integration: A Case Study from Shenzhen

2018 3rd International Conference on Environmental Engineering and Sustainable Development

生态环境科学

Yue, Jun^1^2 ; Chen, Xiaoxiang^1 ; Zhang, Wenhui^1

Urban Planning and Design Institute of Shenzhen, Guangdong

518028, China^1

Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Land and Resources, Shenzhen Guangdong

518000, China^2

关键词: Environmental pollutions;    Evaluation results;    Multi-source data integrations;    Public facilities;    Spatial complexity;    Spatial structure;    Statistical datas;    Urban development;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/264/1/012016/pdf
DOI  :  10.1088/1755-1315/264/1/012016

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Urbanization is proceeding rapidly in several developing countries, such as China. The accelerating urbanization causes not only the expansion of the city scale and space but also creates changes to the internal spatial structure, especially the separation of job-housing spaces and increased commuting time. Reasonable urban space organization is necessary because it can both optimize the structure of urban multicenter groups and reduce residents' need to drive, which lessens traffic congestion, improves the accessibility of public facilities, reduces environmental pollution and promotes the sustainable development of the city. Based on the spatial complexity and development uncertainty of megacities, this paper establishes an evaluation method for the job-housing spaces of megacities on different scales by using traditional statistical data, survey data and big data from multisource data integration to guide urban development and formulate urban policy on the macro level and to understand the relationship of urban space and the relationship between humans and land on the micro level, which may provide the basis for intelligent and refined management of the city. The comparison of multisource data integration and evaluation results from different scales provide a more comprehensive and reasonable reference for the management of megacities.