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Simulating Block-Level Urban Expansion for National Wide Cities

Ying Long () and Kang Wu ()
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Ying Long: School of Architecture and Hang Lung Center for Real Estate, Tsinghua University, Beijing 100084, China
Kang Wu: Beijing Key Laboratory of Megaregions Sustainable Development Modelling and School of Urban Economics and Public Affairs, Capital University of Economics and Business, Beijing 100070, China

Sustainability, 2017, vol. 9, issue 6, 1-19

Abstract: Large-scale models are generally associated with large spatial modelling units, for example, counties or super grids (several to dozens of km 2 ). Few applied urban models can achieve a large spatial coverage with irregular spatial units due to data availability and computation load. The framework of automatic identification and characterization of blocks developed by Liu and Long (2016) makes such an ideal model possible by establishing the existing urban blocks using road networks and points of interest for very large areas (e.g., a country or a continent). In this study, we develop a mega-vector-blocks cellular automata model (MVB-CA) to simulate urban expansion at the block level for 654 Chinese cities. The existing urban blocks in 2012 were used for initiating the MVB-CA and are generated using multi-levelled road networks and ubiquitous points of interest. We then simulate block-based urban expansion of all the cities from 2012 to 2017. The national spatial development strategies of China are discussed extensively by academia and policy makers, while the baseline scenario and other simulated urban expansion scenarios have been tested and compared horizontally. As one of the first block-based urban expansion models at a national scale, its academic contributions, practical applications, and potential biases are also discussed in this paper. The developed MVB-CA using general approaches is also applicable for other counties.

Keywords: urban expansion simulation; vector cellular automata; applied urban modelling; land block; MVB-CA (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2017
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