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). 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). 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. 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. 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我国城市空间格局的演变。目前城市群扩展研究不断发展日趋深入,但仍存在扩展形态定量测度不足、扩展模式空间分异对比欠缺、扩展驱动空间交互因子匮乏等问题。鉴于此,本文以我国中部崛起重要引擎之一的长株潭城市群为例,首先基于全球30m不透水面数据(GAIA)提取2003-2018年多时相建成区范围,利用分形维数、空间扩展强度、Moran’s I指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;进而构建人口、社会经济、交通通达性及城市群交互作用等因子,基于主成分分析、地理加权回归定量揭示长株潭扩展驱动机制。结果表明:(1)长株潭城市群建成区的空间结构具有显著的轴线特征,主要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网络干线上。(2)2003-2018年长沙、株洲、湘潭三市建成区面积与扩展速度总体呈上升趋势,但株洲、湘潭与长沙差距逐步扩大,长沙在城市群中的主导地位持续加强。(3)长株潭城市群建成区空间增长的聚集态势逐渐减弱,建成区扩展及分布格局的总体空间差异有所减小。此外,长株潭建成区在城市群中部存在扩展极核,其辐射作用圈层式带动着外围“冷点区”的扩展格局演化。(4)驱动力模型结果显示2003-2018年长株潭扩展主要受社会经济对外联系、行政力及区位与通达性的影响,说明城市群内部人流/经济流的交互作用、行政上的政策引导与扶持、发达的交通网络与中心城市的辐射作用均驱动了建成区扩展。同时各驱动力的作用呈现着空间分异特征:行政力对长株潭建成区扩展的影响最为显著,城市群北部对该驱动力更为敏感;其次区位与通达性对长株潭的驱动由北至南减弱;而社会经济对外联系对城市群南部的驱动作用更大。

     

    Abstract:   Objectives:   The urban agglomeration has evolved into the main form of China's urbanization in the next stage, which can greatly affect the urban spatial pattern in China. At present, although the research on the expansion of urban agglomerations is deepening and becoming mature, there still exists some problems, e.g., insufficient quantitative measurement on the expansion form of urban agglomerations, neglection of the analysis on the spatial differentiation of expansion modes and lack of the spatial interaction factors in driving forces. In view of this, taking Chang-Zhu-Tan Urban Agglomeration (CZT-UA), which is the earliest integration in central China and is of strategic value to the rise of the central region, as the case study, a comprehensive study has been conducted on the spatial expansion of CZT-UA as well as the interaction between different cities.   Methods:   30m impervious surface data is firstly used to extract time series of CZT-UA's built-up area from 2003 to 2018 owing to its time-sequence stability and accessibility. Then a collection of measurement methods, e.g., fractal dimension, expansion intensity index, Moran's I and Getis-ord Gi* are applied to quantitatively reveal the spatial structure, expansion process and spatialtemporal patterns of CZT-UA's built-up area. Finally, principal component analysis and geographically weighted regression are integrated to explore the driving forces for the built-up area's expansion in CZT-UA. In this regression model, two special factors are established to represent the interaction inside the urban agglomeration besides the traditional population, social economy and transportation accessibility factors.   Results:   The results show that:(1) The CZT-UA's built-up area shows obvious axial distribution, which generally follows Xiangjiang River and the transportation network consisting of five vertical and five horizontal trunk lines. (2) From 2003 to 2018, the built-up area and expansion speed of Changsha, Zhuzhou, and Xiangtan showed an overall upward trend. Compared with Changsha, Zhuzhou and Xiangtan expand more slowly and the gap is gradually widened, and thus Changsha's dominant position in the urban agglomeration continues to strengthen. (3) The expansion pattern analysis shows that the overall spatial differences in the expansion and distribution of built-up area in CZT-UA have gradually narrowed. In addition, the hotspot regions of urban expansion formed a kernel in central CZT-UA, and exerted a driving force to the peripheral areas. (4) The GWR regression model demonstrates that three principal factors are involved in the expansion of CZT-UA's built-up area, including socio-economic external connections, location and traffic accessibility, and administrative power. The model output indicates 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, each factor shows different importance, among which the administrative power has the most positive impact, and the northern parts in CZT-UA are more sensitive to it; the driving force of location and traffic accessibility decreases from the north to the south, while socioeconomic external connections show a much more important effect on the expansion of the southern CZT-UA.   Conclusions:   Based on the thorough analysis, this paper suggests that relevant decision-making departments should further promote the integration and sustainable development of CZT-UA by strengthening the allocation of resources and financial support to Zhuzhou and Xiangtan through appropriate policy tilt and giving full play to the radiation function and trickle-down effect of Changsha to narrow the regional gap in the urban agglomeration. Given that expansion of the built-up area in CZT-UA has been significantly attracted by road network, it is feasible to improve the construction of comprehensive transportation infrastructure such as intercity expressway in remote areas to enhance the accessibility and interaction between regions.

     

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