中国地理科学(英文版) ›› 2007, Vol. 17 ›› Issue (1): 34-39.doi: 10.1007/s11769-007-0034-9

• 论文 • 上一篇    下一篇

Spatial Autocorrelation and Localization of Urban Development

LIU Jisheng1, CHEN Yanguang2   

  1. 1. Department of Geography, Northeast Normal University, Changchun 130024, China;
    2. Department of Geography, Peking University, Beijing 100871, China
  • 收稿日期:2006-03-12 修回日期:2006-12-28 出版日期:2007-03-20 发布日期:2011-12-15
  • 通讯作者: LIU Jisheng.E-mail:liujs362@nenu.edu.cn E-mail:liujs362@nenu.edu.cn
  • 基金资助:

    Under the auspices of the National Natural Science Foundation of China (No.40371039)

Spatial Autocorrelation and Localization of Urban Development

LIU Jisheng1, CHEN Yanguang2   

  1. 1. Department of Geography, Northeast Normal University, Changchun 130024, China;
    2. Department of Geography, Peking University, Beijing 100871, China
  • Received:2006-03-12 Revised:2006-12-28 Online:2007-03-20 Published:2011-12-15

摘要:

A nonlinear analysis of urban evolution is made by using of spatial autocorrelation theory. A first-order nonlinear autoregression model based on Clark's negative exponential model is proposed to show urban population density. The new method and model are applied to Hangzhou City, China, as an example. The average distance of population activities, the auto-correlation coefficient of urban population density, and the auto-regressive function values all show trends of gradual increase from 1964 to 2000, but there always is a sharp first-order cutoff in the partial auto-correlations. These results indicate that urban development is a process of localization. The discovery of urban locality is significant to improve the cellular-automata-based urban simulation of modeling spatial complexity.

关键词: urban population density, nonlinear spatial autocorrelation, Clark’s law, localization, Hangzhou City

Abstract:

A nonlinear analysis of urban evolution is made by using of spatial autocorrelation theory. A first-order nonlinear autoregression model based on Clark's negative exponential model is proposed to show urban population density. The new method and model are applied to Hangzhou City, China, as an example. The average distance of population activities, the auto-correlation coefficient of urban population density, and the auto-regressive function values all show trends of gradual increase from 1964 to 2000, but there always is a sharp first-order cutoff in the partial auto-correlations. These results indicate that urban development is a process of localization. The discovery of urban locality is significant to improve the cellular-automata-based urban simulation of modeling spatial complexity.

Key words: urban population density, nonlinear spatial autocorrelation, Clark’s law, localization, Hangzhou City