人口研究 ›› 2012, Vol. 36 ›› Issue (4): 53-63.

• 论文 • 上一篇    下一篇

基于地理加权回归的山区人口分布影响因素实证研究——以贵州省毕节地区为例

张耀军1任正委2   

  1. 1 中国人民大学人口与发展研究中心,北京100872; 2  浙江大学公共管理学院
  • 出版日期:2012-07-29 发布日期:2012-11-09
  • 通讯作者: Zhyaojunruc@126.com
  • 作者简介:1 中国人民大学人口与发展研究中心副教授;2 浙江大学公共管理学院 博士研究生
  • 基金资助:

    中国人民大学科学研究基金(中央高校基本科研业务费专项基金资助)

Factors Affecting Population Distribution in Mountainous Areas: Geographically Weighted Regression Using Data from Bijie

Zhang Yaojun1, Ren Zhengwei2   

  1. 1 Center for Population and Development Studies,Renmin University of China, Beijing 100872; 2 College of Public Administration,Zhejiang University
  • Online:2012-07-29 Published:2012-11-09
  • Contact: Zhyaojunruc@126.com
  • About author:1 Associate Professor,Center for Population and Development Studies, Renmin University of China; 2 PhD student,College of Public Administration,Zhejiang University

摘要: 山区人口分布受多种经济、社会等非空间因素的影响外,还与不同区域的地理分布有密切关系。文章以贵州省毕节地区为例,以乡镇区域为研究单元,运用地理加权回归(GWR)分析方法,兼与全局普通二乘法(OLS)方法进行比较,研究人口密度和经济、社会、自然等因素的空间相关关系。研究表明,社会经济因素对毕节山区人口分布的影响大于自然环境因素的影响;海拔对毕节山区人口分布的影响不如坡度的影响显著;综合经济实力、城镇化水平、交通条件和地形条件的好坏与其对人口分布的影响大小呈反相关,而医疗条件的好坏与其对人口分布的影响大小呈正相关。因此,"加强城镇建设、鼓励人口聚集,加强生态移民工作、保护资源环境"是未来毕节地区相关政策的基础。

关键词: 山区人口, 人口空间分布, 地理加权回归

Abstract: This is a case study in which data are collected from Bijie in Guizhou Province and geographically weighted regression is performed,with comparison with OLS,to explore the influence of economic,social and natural factors on population density.Results demonstrate that economic and social factors have larger impact on population distribution than natural factors.Altitude does not influence population distribution significantly while slope does.There is negative correlation between population distribution and economic strength,urbanization level,transportation and terrain conditions.Medical conditions have positive influence on population distribution.Therefore in the future Bijie should enhance city and town construction,strengthen the ecological immigration and protect natural resource and environments to optimize population distribution.

Keywords: Mountainous Population, Population Spatial Structure, Geographically Weighted Regression