Journal of Geo-information Science ›› 2018, Vol. 20 ›› Issue (2): 205-216.doi: 10.12082/dqxxkx.2018.170368

• Orginal Article • Previous Articles     Next Articles

Simulation and Projection of the Spatial Pattern of the Population in Beijing under the Background of Non-capital Function Extraction

HU Zengzeng1,3(), ZHAO Zhilong2,*(), ZHANG Guixiang1,3   

  1. 1. College of Urban Economics and Public Administration, Capital University of Economics and Business, Beijing 100070, China
    2. Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    3. Beijing Key Laboratory of Megaregions Sustainable Development Simulation, Beijing 100070, China
  • Received:2017-08-08 Revised:2017-11-23 Online:2018-03-02 Published:2018-03-02
  • Contact: ZHAO Zhilong;
  • Supported by:
    Beijing Social Science Foundation Research Base Project, No.14JDZHB007;Cultivation Program of Beijing Municipal Science and Technology Commission, No.Z171100002217021;Project from Collaborative Innovation Center for Economic and Social Development and Research of Megalopolis in CUEB, No.TDJD201401;Program of Postgraduates' Scientific and Technological Innovation in Capital University of Economics and Business


Based on population distribution data of Beijing City at the spatial scale of 1 km×1 km grid in 2005 and 2010 and CA-Markov model, we simulated the spatial distribution of the population in 2015, 2020, 2025 and 2030. Then, we used the population data at the spatial scale of street to verify the simulation accuracy. On the basis of good reliability of the model and from the perspective that population redistribution is driven largely through industries transfer, we combined the data on employment quantity of different industries at the spatial scale of streets of Beijing city with the population redistribution goal and transfer direction of industries. Then, we calculated the decentralization weight of each street, and analyzed the spatial distribution after redistributing 15% of the population in the six central urban districts in 2020. The results indicated that, firstly, during 2005-2010, the region of the low population density at level 1 is accounting for 90%, focusing on Miyun District, Huairou District, Yanqing District and Fangshan District. Population density above level 10 focused on Xicheng District and Dongcheng District. Secondly, from 2015 to 2030, the low population density area shows a downward trend and the middle to high population density area shows an upward trend under natural conditions. Thirdly, under the impact of non-capital function extraction, population distribution in the six central urban districts shows a trend from focusing on middle-high level to low-middle level, and the high population density area shows a downward trend in 2020. Except Dongcheng District, the rest of five districts focus on population density area at level 5-8. In conclusion, this study can be useful for population management, resource allocation, and policy making.

Key words: spatia distribution of the population, kilometer grids, CA-Markov model, non-capital function, Beijing City