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地理研究 >

2014 , Vol. 33 >Issue 2: 296 - 309

DOI: https://doi.org/10.11821/dlyj201402009

城市研究

珠三角县域城市潜力的空间集聚演化及影响因素

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  • 华南师范大学地理科学学院, 广州 510631
梅志雄（1976- ），男，湖北黄梅人，博士，副教授，主要从事GIS空间分析、空间经济学研究。E-mail：zhixiongmei76@126.com

收稿日期: 2013-04-23

  修回日期: 2013-11-25

  网络出版日期: 2014-02-10

基金资助

国家自然科学基金项目（41001078）

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Spatial agglomeration pattern evolvement and its influencing factors of urban potential at county level in the Pearl River Delta

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  • School of Geography, South China Normal University, Guangzhou 510631, China

Received date: 2013-04-23

  Revised date: 2013-11-25

  Online published: 2014-02-10

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摘要

运用因子分析、扩展的潜力模型、ESDA和空间计量经济学模型，基于五个时间断面的数据，探讨了1990-2009年珠三角县域潜力的空间集聚格局演变特征及其影响因素。研究发现：总体上珠三角县域潜力具正空间集聚特征，但集聚程度不高且趋于减弱；大多数县域潜力的局部空间集聚特征保持相对稳定且规律性明显，高潜力县域集中在广—佛都市区并呈向深—莞—惠都市区发展态势，低潜力县域进一步向研究区西部集聚，并在西部形成面状连续分布区；局部空间集聚格局也发生了一些变化：HH和LL集聚区位有所变化，局部集聚类型间有一定的转化，县域潜力的空间集聚的不均衡性在西部与中东部地带间有进一步扩大倾向。从县域潜力集聚演化的影响因素上看，县域间相互作用、地理区位、消费者购买力、人力资本、劳动力成本、信息化水平有显著正向影响；企业数量、城市化水平有显著负向影响；交通运输条件、固定资本投入和两个经济政策因素的影响不显著。

关键词： 城市潜力; 空间集聚; ESDA; 空间计量经济学模型; 珠三角

本文引用格式

梅志雄, 徐颂军, 欧阳军 . 珠三角县域城市潜力的空间集聚演化及影响因素[J]. 地理研究, 2014 , 33(2) : 296 -309 . DOI: 10.11821/dlyj201402009

Abstract

Using the methods of factor analysis, extended potential model, ESDA and spatial econometrics model, and based on the data of 1990, 1994, 2000, 2005 and 2009 of county units in the Pearl River Delta, this paper analyzes the spatial agglomeration pattern evolvement and its influencing factors of urban potential at county level in the Pearl River Delta from 1990 to 2009. The results are obtained as follows: (1) As a whole, the spatial agglomeration of county potential in the region showed a positive effect. But the positive effect of the global spatial agglomeration was not strong and showed a weakening trend. (2) The local spatial agglomeration features of most counties kept relatively stable and displayed some obvious rules, that is, counties with higher potential were concentrated in Guangzhou-Foshan metropolitan region and tended to extend to Shenzhen-Dongguan-Huizhou metropolitan region, counties with lower potential were clustered further to the west part of the study area and formed a surface-shaped continuous distribution area. (3) The local spatial agglomeration pattern also involved some changes: the locations of HH and LL agglomeration changed; there were certain transformations among four types of local spatial agglomeration, which are HH, LL, HL and LH; the imbalance of spatial agglomeration of county potential between the western part and the central and eastern parts had an extending trend. (4) The results from influencing factors analysis show that interregional interaction, geographic location, consumer purchasing power, human capital, labor cost and information level had significant positive impacts on the spatial pattern evolvement of county potential agglomeration of the study area, and corporation number and urbanization level had remarkable negative impacts. However, the impacts of traffic condition, fixed assets investment and economic policy factors, such as openness level and government intervention, were not significant in statistics. The key findings of the paper have important policy implications.

Key words： urban potential; spatial agglomeration; ESDA; spatial econometrics model; Pearl River Delta

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