地理研究 ›› 2016, Vol. 35 ›› Issue (2): 337-352.doi: 10.11821/dlyj201602011

• 研究论文 • 上一篇    下一篇

中国地级以上城市经济承载力的空间格局

狄乾斌(), 韩帅帅, 韩增林   

  1. 辽宁师范大学 海洋经济与可持续发展研究中心,大连 116029
  • 收稿日期:2015-08-04 修回日期:2015-12-16 出版日期:2016-02-20 发布日期:2016-02-20
  • 作者简介:

    作者简介:狄乾斌(1977-),男,山东滕州人,博士,副教授,研究方向为经济地理。E-mail: dqbwmn@163.com

  • 基金资助:
    国家自然科学基金项目(41571127);辽宁省高等学校优秀科技人才支持计划(WR2014005)

Spatial pattern of economic carrying capacity of cities at prefecture level and above in China

Qianbin DI(), Shuaishuai HAN, Zenglin HAN   

  1. Center for Studies of Marine Economy and Sustainable Development of Liaoning Normal University, Dalian 116029, Liaoning, China
  • Received:2015-08-04 Revised:2015-12-16 Online:2016-02-20 Published:2016-02-20

摘要:

在探讨经济承载力内涵和特征的基础上,利用探索性空间数据分析和地统计全局趋势分析法,对中国288个地级以上城市的经济承载力空间格局分异特征进行分析,并在此基础上归纳城市经济承载力的驱动路径及提升策略。结果表明:① 城市经济承载力的空间分布,基本呈东、中、西三级阶梯依次递减的趋势,且各城市得分值从高至低的衰减速度由快到慢再变快。② 城市经济承载力空间分布呈现较弱的正向空间自相关,热点区域H-H类型集中,冷点区域H-L型和L-H型较多,且热度从东南沿海向西北内陆依次递减。③ 城市经济承载力的空间差异主要在东西方向,而经济发展的差异主要体现在南北方向,且两者由低级到高级的发展阶段基本对应中国的西部、中部和东部位置。④ 资源环境驱动路径、经济社会驱动路径和政策人才驱动路径是城市经济承载力提升的三种主要途径。

关键词: 地级以上城市, 城市经济承载力, 探索性空间数据分析, 空间格局, 驱动路径

Abstract:

Carrying capacity of urban economy is based on the concept of sustainable development. It refers to the capability of the enormous system of a given urban economy to carry the largest scale of economy when the urban economy develops to its full potential within the limits of resource conditions and environmental capacity. From the point of view of economy, economic carrying capacity takes into account both the consistency of the developing level and developing speed and the consistency of economic development and social progress. Using the Exploratory Spatial Data Analysis (ESDA) and statistical global trend analysis, we analyze the spatial pattern of economic carrying capacity of 288 cities at prefecture level and above in China, based on which the driving path and enhancement strategy of urban economic carrying capacity are concluded. Through the analysis of the spatial pattern differentiation of urban economic carrying capacity, the study proposes some suggestions for urban construction adjustment. According to the analysis, spatial distribution pattern of urban economic carrying capacity of the cities at prefecture level and above in China shows the following features: ① The spatial distribution of urban economic carrying capacity demonstrates a tendency of gradually descending following the three geographical regions of the East, the Middle and the West. And the high-to-low decreasing rates of the cities' scores show a trend of fast-slow-fast. ② Spatial distribution of the carrying capacity of urban economies is characterized by a weak positive spatial autocorrelation. There are many H-H types in the hot regions, while the H-L and L-H types are present in cold regions mostly. The heat decreases gradually from the southeast coastal region to the northwest inland region. ③ There are spatial disparities of the urban economic carrying capacity between the East and the West, while there are disparities of economic development between the South and the North. And the development stages from backward to advanced are in accordance with the spatial pattern of the East, the Middle and the West. ④There are three main ways to improve the urban economic carrying capacity, that is, the driving path of resource environment, driving path of economy & society and the driving path of policy and talent. In addition, economic location, talented personnel, the environment and the infrastructure are the factors that influence urban economic carrying capacity. The measures to improve urban economic carrying capacity are as follows, optimizing resource utilization and environmental protection, developing transportation industry, encouraging outside capital investment in the urban economy, and actively integrating into the national economy and regional development strategy.

Key words: cities at prefecture level and above, urban economic carrying capacity, exploratory spatial data analysis, spatial pattern, driving path