Geocarto International (Dec 2023)

Research on land use pattern change and its influencing factors based on the coupling model: evidence from Zhongshan, China

  • Jingzhao Feng,
  • Yile Chen,
  • Senyu Lou,
  • Jianqiang Yin

DOI
https://doi.org/10.1080/10106049.2023.2280559
Journal volume & issue
Vol. 38, no. 1

Abstract

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AbstractThe change in the land spatial structure affects regional development and stability. In the context of the construction of the Guangdong-Hong Kong-Macao Greater Bay Area, studying the spatial structure changes in its important cities will contribute to the coordinated development of the region. This study uses spatial analysis and coupling models to explore the basic characteristics and evolutionary trends of the land spatial structure in Zhongshan city in 2000, 2011, 2022, and 2035. Through research, it is found that (1) in general, the urban space is divided into different geometric forms by the water network system. The spatial structure of living land is ‘fragmentation-aggregation-aggregation and fragmentation’. (2) Ecological land is concentrated in the southeast and remained relatively stable. Productive land accounts for the largest proportion in Northeast China, becoming the main area of agricultural development. (3) From 2022 to 2035, the area of productive land will increase in different ranges under four scenarios, and the area of productive land will increase the fastest under the urbanization development scenario (UDS). (4) The ecological land area increases only in the ecological protection scenario (EPS), and the area decreases in the other three scenarios. An increase in construction land area occurs in the urbanization development scenario (UDS) and nature development scenario (NDS). (5) The habitat quality of Zhongshan city showed a significant decline from 2000 to 2022. In 2035, the habitat quality will significantly improve in the ecological protection scenario (EPS) and sustainable development scenario (SDS) scenarios, and the ecological regions in Southeast China will be significantly clustered and expanded.

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