地理科学进展 ›› 2008, Vol. 27 ›› Issue (4): 110-116.doi: 10.11820/dlkxjz.2008.04.016

• 交通运输地理 • 上一篇    下一篇

重力模型系数时间变化路径分析 ———以中国城际铁路旅客交流为例

戴特奇1,2, 刘毅1   

  1. 1. 中国科学院地理科学与资源研究所,北京100101;
    2. 中国科学院研究生院,北京100039
  • 收稿日期:2008-02-01 修回日期:2008-04-01 出版日期:2008-07-25 发布日期:2008-07-25
  • 作者简介:戴特奇(1980- ),男,博士生.主要研究城市交通和城市经济.Email: daitq@igsnrr.ac.cn
  • 基金资助:

    国家自然科学基金重点项目(40635026),空间组织与空间效率的基础理论研究.

Tempor al Var iations in Par ameter s of Gr avity Model: an Analysis on China's Inter - city Railway Passenger Flows

DAI Teqi1,2, LIU Yi1   

  1. 1. Institute of Geographic Science and Natural Resource Research, CAS, Beijing 100101, China;
    2. Graduate School, the Chinese Academy of Sciences, Beijing 100039, China
  • Received:2008-02-01 Revised:2008-04-01 Online:2008-07-25 Published:2008-07-25

摘要:

重力模型是空间相互作用研究中得到广泛应用的基础模型,空间相互作用随着距离的增加而减小,随着 “质量”的增加而增加,对模型参数的测定和解释一直是多个学科关注的热点。但对模型参数时间变化路径方面的 研究比较薄弱。本研究采用无约束重力模型分析了1990 年代以来主要时间点的中国城际铁路旅客交流,得到了参 数的时间变化路径。我们发现质量参数与距离衰减参数均为增加趋势,并进行了解释,特别就距离衰减参数单调增 加路径与理论预期的差异从技术进步、经济和社会的制度框架以及区域经济发展的阶段性特征进行了试探性解释 和理论反思。

关键词: 动态变化, 距离衰减参数, 质量参数, 重力模型

Abstract:

Gravity models are the basic tools which are widely applied in the research of spatial interaction (SI). It is well known that SI decreases as the distance increases or the mass decreases. The measurement and explanation on parameters are hot topics but the temporal variations of them are not discussed so frequently. This paper deals with how and why the parameters change with time by using the unrestrained gravity model and the data set consists of China's railway passenger flows between about 200 cities. We find that scale parameters show an increasing trend with a little fluctuation and distance - decay parameters grow over time instead of monotonic decrease over time. And an empirical and theoretical explanation will be given to why the general assumptions of monotonic increasing scale parameters and monotonic decreasing distance - decay parameters are not obeyed.

Key words: distance- decay parameters, gravity model, scale parameters, temporal variations