地理科学进展 ›› 2018, Vol. 37 ›› Issue (2): 287-298.doi: 10.18306/dlkxjz.2018.02.011

• 研究论文 • 上一篇    下一篇

广东省“人口—经济—土地—社会—生态”城市化协调度时空变化及其聚类模式

李久枫1(), 余华飞1, 付迎春1,2,*(), 赵耀龙1,2   

  1. 1. 华南师范大学地理科学学院,广州 510631
    2. 广东省智慧国土工程技术研究中心,广州 510631;
  • 收稿日期:2017-04-17 修回日期:2017-09-18 出版日期:2018-02-28 发布日期:2018-02-28
  • 通讯作者: 付迎春 E-mail:2016022047@m.scnu.edu.cn;fuyc@m.scnu.edu.cn
  • 作者简介:

    作者简介:李久枫(1993-),男,河南商丘人,硕士研究生,主要从事环境遥感与定量遥感研究,E-mail: 2016022047@m.scnu.edu.cn

  • 基金资助:
    国家自然科学基金项目(41101152);广东省科技计划项目(2015A010103013)

Spatial-temporal changes of population-economy-land-society-ecology coordination level of urbanization and clustering: A case of Guangdong Province, China

Jiufeng LI1(), Huafei YU1, Yingchun FU1,2,*(), Yaolong ZHAO1,2   

  1. 1. School of Geography, South China Normal University, Guangzhou 510631, China
    2. Guangdong Provincial Center for Smart Land Research, Guangzhou 510631, China
  • Received:2017-04-17 Revised:2017-09-18 Online:2018-02-28 Published:2018-02-28
  • Contact: Yingchun FU E-mail:2016022047@m.scnu.edu.cn;fuyc@m.scnu.edu.cn
  • Supported by:
    National Natural Science Foundation of China, No.41101152;Science and Technology Planning Project of Guangdong Province, China, No.2015A010103013

摘要:

多维城市化协调度评价是衡量区域城市化质量的重要方面,探究城市化时空聚类模式则是分析区域城市化特征的有效方法。针对目前城市化协调度评价缺乏多维度时空综合分析的现状,本文以广东省为例,提出一种基于时空权重矩阵的复杂时空系统协调度评价模型,运用此模型分析2006-2014年城市化协调度的时空变化特征,并借助时空扫描方法分析其聚类模式。研究结论为:①近10年来城市化水平呈现3种时序特征,人口城市化水平表现出随时间均衡发展的“集中”特征,而经济与土地表现出低频次的“集中与分散”交替,社会、生态及综合水平表现出高频次的“集中与分散”交替;稳定型城市主要位于珠三角核心区。②各维度及综合系统协调度时空聚类区既有空间分异性又有重叠性,人口协调度时空聚类于粤西地区,经济与土地维度协调度时空聚类高度重合于珠三角与粤北地区,社会与生态维度协调度时空聚类交叉于珠三角与粤东地区,而综合系统协调度居中。此外,时空聚类区的人口、经济与社会维度的协调度稳定性要优于土地与生态维度。本文结论有助于揭示区域城市化的时空特征。

关键词: 城市化协调度, 时空变化, 复杂时空系统协调度评价模型, 时空聚类模式, 广东省

Abstract:

Multidimensional urbanization coordination evaluation is an important aspect for measuring the quality of urbanization of a region, and spatial-temporal clustering models are effective means for analyzing features of urbanization. Considering the lack of multidimensional comprehensive spatial-temporal analysis of urbanization coordination degree at present, this article takes Guangdong Province as an example and propose a complex spatial-temporal coordination degree evaluation model based on spatial-temporal weight matrix. This model is used to analyze the urbanization coordination level from 2006 to 2014, and the clustering is analyzed by the spatiotemporal scanning method. The results show that: (1) The coordination level of urbanization in recent years shows three kinds of temporal characteristics: the level of population urbanization shows the "concentrated" characteristics of development with time, while the economy and land show low frequency alternations of "concentrated and scattered " development, and social, ecological, and comprehensive level show a high frequency alternation of "concentrated and scattered" development. The spatial-temporal changes of each dimension and comprehensive system coordination degree show that the stable cities are mainly located in the core area of the Pearl River Delta. (2) The spatial-temporal clustering characteristics of each system are not only differentiated, but also overlapped. Western Guangdong Province forms a spatial-temporal cluster featuring coordination of population urbanization; the economic and land dimensions of the coordination of spatial-temporal clustering coincide in the Pearl River Delta and northern Guangdong; the social and ecological dimensions of coordination of spatial-temporal clustering cross in the Pearl River Delta and eastern Guangdong Province, and system coordination is centered. In addition, the stability of population, economic, and social dimensions in the spatial-temporal clusters is superior to that of land and ecological dimensions. The conclusion of this study is helpful for revealing the spatial-temporal characteristics of urbanization in the region.

Key words: urbanization coordination level, spatial-temporal changes, complex spatial-temporal system coordination degree evaluation model, spatial-temporal clustering model, Guangdong Province