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

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

More Information
  • Received Date: February 20, 2023
  • Available Online: July 21, 2022
  • 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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