李静波, 关雪峰, 曾星, 杨昌兰, 邢巍然, 吴华意. 长株潭城市群建成区时空扩展特征及驱动力分析[J]. 武汉大学学报 ( 信息科学版), 2024, 49(6): 1028-1039. DOI: 10.13203/j.whugis20210634
引用本文: 李静波, 关雪峰, 曾星, 杨昌兰, 邢巍然, 吴华意. 长株潭城市群建成区时空扩展特征及驱动力分析[J]. 武汉大学学报 ( 信息科学版), 2024, 49(6): 1028-1039. DOI: 10.13203/j.whugis20210634
LI Jingbo, GUAN Xuefeng, ZENG Xing, YANG Changlan, XING Weiran, WU Huayi. Spatial-Temporal Expansion Pattern and Driving Mechanism of Built-up Area in Chang-Zhu-Tan Urban Agglomeration[J]. Geomatics and Information Science of Wuhan University, 2024, 49(6): 1028-1039. DOI: 10.13203/j.whugis20210634
Citation: LI Jingbo, GUAN Xuefeng, ZENG Xing, YANG Changlan, XING Weiran, WU Huayi. Spatial-Temporal Expansion Pattern and Driving Mechanism of Built-up Area in Chang-Zhu-Tan Urban Agglomeration[J]. Geomatics and Information Science of Wuhan University, 2024, 49(6): 1028-1039. DOI: 10.13203/j.whugis20210634

长株潭城市群建成区时空扩展特征及驱动力分析

Spatial-Temporal Expansion Pattern and Driving Mechanism of Built-up Area in Chang-Zhu-Tan Urban Agglomeration

  • 摘要: 作为新型城镇化的主体,城市群的发展极大地影响着中国城市空间格局的演变。以中国中部崛起重要引擎之一的长株潭城市群为例,从建成区扩展空间分异与交互为视角,基于多时相不透水面数据提取建成区范围,利用分形维数、空间扩展强度、Moran’s I系数与空间关联指数等多维测度长株潭城市群建成区的组织结构、扩展进程及空间格局,并采用主成分分析、地理加权回归定量揭示扩展驱动机制。结果表明,2003-2018年,长株潭城市群的空间结构具有显著的轴线特征,建成区集中分布在湘江生态轴及铁路、高速、国道等五纵五横综合交通干线上。长沙、株洲、湘潭建成区面积与扩展速度总体趋于上升,但长沙的空间主导地位持续加强。城市群空间增长的聚集态势减弱,建成区扩展及分布格局的总体空间差异减小;其中部存在扩展极核,圈层式辐射带动外围“冷点区”的扩展格局演化。长株潭城市群扩展驱动机制呈现空间异质性,整体主要受社会经济对外联系、行政力及区位与通达性的影响。

     

    Abstract:
    Objectives As the main form of urbanization, the urban agglomeration can greatly affect the urban spatial pattern in China.
    Methods Based on the impervious area data of Chang-Zhu-Tan urban agglomeration (CZT-UA), the spatial organization structure, dynamic development pattern and spatially heterogeneous driving mechanism of the expansion of built-up areas in CZT-UA are quantitatively revealed with a collection of measurement methods, e.g., fractal dimension, expansion intensity index, Moran's I, Getis-Ord Gi*, principal component analysis and geographically weighted regression.
    Results From 2003 to 2018, the spatial structure of CZT-UA shows obvious axial distribution, which generally follows Xiang-jiang River and the transportation network consisting of five vertical and five horizontal trunk lines. The built-up area and expansion speed of Changsha, Zhuzhou and Xiangtan show an upward trend. Compared with Changsha, Zhuzhou and Xiangtan expanded more slowly and the gap is gradually widened. The overall spatial differences in expansion and distribution of the built-up area in CZT-UA are gradually narrowed. The hotspot regions of urban expansion form a kernel in central CZT-UA, which provides driving force to the peripheral areas.
    Conclusions The geographically weighted regression model demonstrates that the flow of residents and economy between cities, clear policy guidance from government, convenient transportation network as well as the radiation effect of the central city can jointly attribute to the expansion of built-up areas. However, the importance and effects of each factor varied in different regions of CZT-UA.

     

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