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中国科学院大学学报 ›› 2015, Vol. 32 ›› Issue (3): 325-332.DOI: 10.7523/j.issn.2095-6134.2015.03.006

• 环境科学与地理学 • 上一篇    下一篇

吉林省县域工业发展水平测度及空间格局演变

张利平1,2, 马延吉1   

  1. 1. 中国科学院东北地理与农业生态研究所, 长春 130102;
    2. 中国科学院大学, 北京 100049
  • 收稿日期:2014-08-11 修回日期:2014-09-12 发布日期:2015-05-15
  • 通讯作者: 马延吉
  • 基金资助:

    国家自然科学基金(41371135)和吉林省科技引导计划软科学项目(20120635)资助

Level measurement and spatial pattern evolution of county industry development of Jilin province

ZHANG Liping1,2, MA Yanji1   

  1. 1. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2014-08-11 Revised:2014-09-12 Published:2015-05-15

摘要:

县域工业发展是东北老工业基地振兴与空间优化的关键问题.通过构建工业发展指标评价体系,采用熵值法赋权重并计算得分来测度县域工业发展综合水平,并以此为分析的基础变量,利用马尔可夫链分析方法对吉林省县域工业发展水平的空间格局以及热点区演化进行研究.结果表明:吉林省中心城区工业发展水平明显高于周边县域单元;2000—2004年吉林省县域工业发展水平差距在扩大,2004—2012年县域工业发展水平都有所提高且发展均衡;热点区历年来一直集中于工业基础条件较好的长吉及其周边县域,未发生明显迁移;最后提出提升县域工业发展水平的路径与可持续发展对策.

关键词: 熵值法, 马尔可夫链, 县域工业发展, 空间格局, 吉林省

Abstract:

County industry development is a key issue to spatial optimization and "revitalization of the old industrial base in Northeast China". By constructing an industry development index system, we use the entropy method to calculate the comprehensive level scores for every county industry. Then by taking this achievement as a spatial analytic basic variable we use Markov chains to analyze the evolution of spatial pattern and hot spots in Jilin county industry. Finally we analyze the factors which lead to this evolution. The results show that the level of industrial development in the central cities was significantly higher than in the surrounding counties in Jilin. The gap of the industrial development level in Jilin province was expanded from 2000 to 2004. The industrial development level has increased and balanced from 2004 to 2012. The hot spot was focused on Changchun-Jilin area where there is a better industrial infrastructure, and the hot spot was stable over the years. Finally, we propound the path for raising the level of industrial development.

Key words: entropy method, Markov chains, county industry development, spatial pattern, Jilin province

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