FINE-SCALE URBAN MODELING AND ITS OPPORTUNITIES IN THE "BIG DATA" ERA: METHODS, DATA AND EMPIRICAL STUDIES

Fine-scale simulation, in which the parcel is the basic spatial unit and urban activity body is the simulation object, is an important research direction for the urban modeling in the future, and the arrival of big data era also provides an important development opportunity for it. In the paper, the mainstream modeling methods for fine-scale urban modeling are introduced mainly, including cellular automata(CA), agentbased modeling(ABM) and traditional Microsimulation(MSM), all of which are microscopic simulation from the bottom up. Then, according with the high-standard data requirements for the fine-scale urban modeling, the paper sums up the internationally acceptable methods for the fine-scale simulation data synthesis(population synthesis), and also gives a number of practical cases about the fine-scale urban modeling in recent years. Finally, the paper puts forward the framework and key technology, based on GIS platform and combined with CA/ABM/MSM method, to construct fine-scale urban modeling, to support the development and assessment of spatial policy in the metropolitan area.

[1]  W. Deming,et al.  On a Least Squares Adjustment of a Sampled Frequency Table When the Expected Marginal Totals are Known , 1940 .

[2]  Hugh Kelley,et al.  Multi-scale analysis of a household level agent-based model of landcover change. , 2004, Journal of environmental management.

[3]  Kay W. Axhausen,et al.  Population synthesis for microsimulation: State of the art , 2010 .

[4]  Zhenjiang Shen,et al.  Urban Form, Transportation Energy Consumption, and Environment Impact Integrated Simulation: A Multi-agent Model , 2013 .

[5]  Graham Clarke,et al.  GIS and microsimulation for local labour market analysis , 2000 .

[6]  Xiang Yu,et al.  Discovering functional zones using bus smart card data and points of interest in Beijing , 2015, ArXiv.

[7]  Anrong Dang,et al.  Beijing Urban Development Model: Urban Growth Analysis and Simulation * , 2009 .

[8]  Paul M. Torrens,et al.  Geographic Automata Systems , 2005, Int. J. Geogr. Inf. Sci..

[9]  Mitsuhiko Kawakami,et al.  Simulating Spatial Market Share Patterns for Impacts Analysis of Large-Scale Shopping Centers on Downtown Revitalization , 2011 .

[10]  G. Orcutt,et al.  A new type of socio-economic system , 1957 .

[11]  Liming Wang,et al.  Microsimulating Parcel-Level Land Use and Activity-Based Travel: Development of a Prototype Application in San Francisco , 2010 .

[12]  Suzana Dragicevic,et al.  A GIS-Based Irregular Cellular Automata Model of Land-Use Change , 2007 .

[13]  Suzana Dragićević,et al.  High Resolution Urban Land-use Change Modeling: Agent iCity Approach , 2011, Applied Spatial Analysis and Policy.

[14]  Xingjian Liu,et al.  Featured Graphic. How Mixed is Beijing, China? A Visual Exploration of Mixed Land Use , 2013 .

[15]  Xing Xie,et al.  Discovering regions of different functions in a city using human mobility and POIs , 2012, KDD.

[16]  Ying Long,et al.  Disaggregating heterogeneous agent attributes and location , 2013, Comput. Environ. Urban Syst..

[17]  M L Bobrow,et al.  On planning and design. , 1976, Hospital forum.

[18]  Danielle J. Marceau,et al.  VecGCA: A Vector-Based Geographic Cellular Automata Model Allowing Geometric Transformations of Objects , 2008 .

[19]  Xia Li,et al.  Coupling Simulation and Optimization to Solve Planning Problems in a Fast-Developing Area , 2011 .

[20]  Franco Chingcuanco,et al.  A microsimulation model of urban energy use: Modelling residential space heating demand in ILUTE , 2012, Comput. Environ. Urban Syst..