主管单位：中国科学技术协会
主办单位：中国地理学会
承办单位：华东师范大学
世界地理研究

世界地理研究 ›› 2020, Vol. 29 ›› Issue (3): 536-548.DOI: 10.3969/j.issn.1004-9479.2020.03.2018523

• 城市与区域 • 上一篇    下一篇

基于多元要素流的珠三角城市群功能联系与空间格局分析

林勋媛1(), 胡月明1,2,3(), 王广兴2, 樊舒迪1   

  1. 1.华南农业大学资源环境学院/国土资源部建设用地再开发重点实验室/广东省土地利用与整治重点实验室/广东省土地信息工程技术研究中心，广州 510642
    2.青海大学农牧学院，西宁 810016
    3.电子科技大学资源与环境学院，成都 610054
  • 收稿日期:2018-11-23 修回日期:2019-05-10 出版日期:2020-05-30 发布日期:2020-06-12
  • 通讯作者: 胡月明
  • 作者简介:林勋媛（1994-），女，硕士研究生，主要研究方向为城市规划与城市更新，E-mail:LINXunyuan1994@163.com。
  • 基金资助:
    广东省省级科技计划项目(2017B090907030);广州市科技计划项目(201807010048)

Analysis of functional connection and spatial pattern of Pearl River Delta urban agglomeration based on multi-element factor flows

Xunyuan LIN1(), Yueming HU1,2,3(), Guangxing WANG2, Shudi FAN1   

  1. 1.College of Natural Resources and Environment, South China Agricultural University/Key Laboratory for Construction Land Transformation, Ministry of Land and Resources/Guangdong Province Key Laboratory for Land Use and Consolidation/Guangdong Province Engineering Research Center for Land Information Technology, Guangzhou 510642, China
    2.College of Agriculture and Animal Husbandry, Qinghai University, Xining 810016, China
    3.College of Natural Resources and Environment, University of Electronic Science and Technology, Chengdu 610054, China
  • Received:2018-11-23 Revised:2019-05-10 Online:2020-05-30 Published:2020-06-12
  • Contact: Yueming HU

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摘要：

以珠三角城市群9个地级市为研究对象，结合当前热点网络开放大数据，对珠三角城市群内各城市的经济流、交通流、人口流和信息流的联系强度和作用方向进行测算与评价。借助赋值法分别对四种要素流的总量进行打分，以各城市的综合得分作为空间层级划分依据，提出关于“点—线—面”的空间互动格局，进而探索珠三角城市群未来的发展规划。研究结果表明：①从各要素流的联系强度上看，城市间的等级划分具有较高的重合度，说明四种要素流彼此之间相互联系、相互作用。从各要素流的作用方向上看，广州和深圳多作为区域内其它城市的首位空间联系城市，说明各要素流通常指向经济发展水平较高、通达性较好的城市。②从整体来看，珠三角城市群内部功能互动表现极度不平衡，一是中心城市占据了要素流强度的绝大部分，其余城市仅占据极小部分流量，两极分化严重；二是东西两岸发展不平衡，东岸发展水平明显要强于西岸发展水平。③广州、深圳、东莞和佛山等城市虽然在区域内起到了一定的辐射和带动作用，但是针对江门、肇庆等周边城市的辐射和带动强度仍有待提升,说明还需进一步优化珠三角城市群功能分工与产业布局，推进区域经济一体化。

关键词: 网络开放大数据, 多元要素流, 功能联系, 空间格局, 珠三角城市群

Abstract:

Taking 9 prefecture-level cities in the PRD urban agglomeration as the research object, combined with the current hot spots open big data to calculate and evaluate the contact strength and action direction of economic flow, traffic flow, population flow and information flow of cities in the PRD urban agglomeration, and used valuation method to consider the four factor flows’ intensity. Finally, according to the comprehensive scores of each city, the spatial hierarchy is divided, the spatial interaction pattern of “Point-Line-Plane” is proposed, and then the future development planning of the PRD urban agglomeration is explored. The results show that: (1) From the perspective of the contact strength of each factor flow, the hierarchical division between cities has a high degree of coincidence, indicating that the four factors flows are related to each other and interacted with each other. From the perspective of the action direction of each factor flow, Guangzhou and Shenzhen are mostly the first spatially connected cities in other cities in the region, indicating that each factor flow usually points to a city with a higher level of economic development and better accessibility. (2) From the overall point of view, the internal functional interactions within the PRD urban agglomeration are extremely unbalanced. Firstly, the central cities occupy the vast majority of the intensity of the factor flows, and the rest of the cities only occupy a small part of the flows, indicating the polarization is serious. Secondly, the development of the east bank and the west bank is not balance, and the development level of the east bank is obviously stronger than the development level of the west bank.(3) Although Guangzhou, Shenzhen, Dongguan, Foshan and other cities have played a certain role in radiation and driving in the region, their radiation and driving intensity to peripheral cities such as Jiangmen and Zhaoqing still need to be improved, indicating that further optimization of functional division and industrial layout of the PRD urban agglomeration is needed to promote regional economic integration.

Key words: open big data, multi-element factor flows, functional connection, spatial pattern, Pearl River Delta urban agglomeration