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中国农学通报 ›› 2019, Vol. 35 ›› Issue (4): 147-157.doi: 10.11924/j.issn.1000-6850.casb18030112

• 三农研究 • 上一篇    下一篇

基于熵权TOPSIS和ESDA的甘肃省县域经济时空演变研究

马能文1, 党国锋1,2   

  1. 1.西北师范大学地理与环境科学学院;2.西北师范大学甘肃省地名研究中心
  • 收稿日期:2018-03-22 修回日期:2018-10-22 接受日期:2018-10-31 出版日期:2019-01-31 发布日期:2019-01-31
  • 通讯作者: 党国锋
  • 基金资助:
    国家自然科学青年科学基金项目“面向西北内陆河流域的InVEST模型优化及时空权衡研究”(41701634)。

County Economy in Gansu: Spatio-temporal Evolution Based on Entropy Weight TOPSIS and ESDA

  • Received:2018-03-22 Revised:2018-10-22 Accepted:2018-10-31 Online:2019-01-31 Published:2019-01-31

摘要: 县域经济是我国国民经济的基本单元,研究县域经济差异对于一个地区的发展以及整个国民经济的发展都有重大意义。本文以甘肃省86个县域及嘉峪关市共87个地域为研究单元,选取人均GDP 、第二、三产业比重等12项相关指标建立了县域经济发展水平综合评价体系,利用熵权TOPSIS法和ESDA法对近20年来甘肃省各县域经济发展水平进行时间和空间两方面的评测。结果表明:从1995—2015年20年期间,甘肃省经济明显增长,但与全国各地经济发展水平相比还处于缓慢发展阶段;甘肃省县域经济发展水平两极差异明显,排名靠前及靠后的县域在20年间变化不明显,省会兰州及河西地区发展水平较高,陇中和陇南地区县域发展水平整体较低,呈现“强者恒强,弱者恒弱”的格局;空间自相关性显著,低值聚类的显著性更强;热点分析显示,甘肃省县域经济呈现明显的单核型经济空间结构,发展水平较高的地区对周边城市带动作用很小,地域差异明显。

关键词: 大暴雨, 大暴雨, 干旱沙漠区, 急流, 切变线, 对流云团

Abstract: The paper aims to reveal the economic development of Gansu. We took a total of 87 regions (86 counties and Jiayuguan) in Gansu as the research unit and selected 12 related indexes, including the per capita GDP, the proportion of the second industry and proportion of the third industry and so on, to establish a comprehensive evaluation system of the county economic development level, and evaluated the economic development level of every region in Gansu during 1995-2015 from the aspects of time and space by using the methods of entropy TOPSIS and ESDA. The results showed that: from 1995 to 2015, the economy of Gansu increased significantly, but it was still in a slow development stage compared with the level of economic development across the country; the differences of the county economy in Gansu was obvious, the top and bottom counties did not change significantly during 1995-2015, Lanzhou and Hexi area had a higher level of development, county development level was low in Longzhong and Longnan, the pattern was“strong constant strong, weak constant weak”; the spatial autocorrelation was significant and the low value clustering was more significant; the hotspot analysis showed that: the county economy of Gansu had obvious monocular economic spatial structure, and the area with high development level had little effect on the surrounding cities, and the regional difference was obvious.