A Study of Urban Living and Employment Compactness Based on Multi-source Spatio-temporal Data

Department: Urban Planning and Design
Research Centre: Centre of Urban Studies and Urban Planning;
Active Dates: August 2014 – July 2017

Project Team: Anthony G.O. YEH (PI), Dr. Weifeng Li (Co-I), Dr. Zhixin Qi (Co-I)

Funding body: National Science Foundation China (NSFC) General Program


Rapid urbanization in China has led to a set of urban problems such as traffic congestion, energy consumption, which may affect sustainable development. One of the problems is mismatch between activities and spatial structures. Urban planning in China has been promoting compact city characterized as high-density and mixed land use development for many years. However, compact urban form, compact land use and facilities are not real goals of fulfilling a compact city. Achieving high quality and compactness of urban living and employment are the key issues of sustainable development. The availability of big data from mobile phones and smart cards enable us to have better knowledge of travel pattern and behaviours. To recognize and extract residents’ living and commuting activity pattern from big data is one key scientific question. The other scientific question is how to demonstrate the evolving dynamics of urban systems by integrating the big data with the traditional land use and transportation data. This project examines the analysis of big data for the investigating the compactness of urban living and employment and to find the relationships between the measurement of compactness from traditional land use analysis and actual people’s activity space from big data. The project will further advance the theory of compact city, filling in the research gap that traditional urban planning practice cannot match spatial structure and urban micro-economic activities. It will develop the bottom-up activity based urban planning theoretical framework by the use of big data which is of great significance to sustainable urban spatial development and smart urban planning.

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