Acta Geographica Sinica ›› 2022, Vol. 77 ›› Issue (11): 2738-2756.doi: 10.11821/dlxb202211004

• Land Use/Land Cover Change • Previous Articles     Next Articles

Refined simulation of urban land use change with emphasis on spatial scale effect

LI Yan1,2(), LIN Anqi1,2, WU Hao1,2(), WU Xia1,2, CEN Luyu1,2, LIU He1,2, JIANG Zhimeng1,2   

  1. 1. College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China
    2. Hubei Province Key Laboratory for Geographical Process Analysis and Simulation, Wuhan 430079, China
  • Received:2021-12-20 Revised:2022-07-19 Online:2022-11-25 Published:2022-12-27
  • Contact: WU Hao;
  • Supported by:
    National Natural Science Foundation of China(42071358);National Natural Science Foundation of China(41671406)


Simulation of urban land use change is the scientific basis for optimizing land resource allocation, and improving its refinement and reliability is helpful to accurately grasp the development trend of urban land use. This is immensely crucial for accurate regulation of urban land resources. The simulation of land use change based on remote sensing classification is macroscopic and simple. However, it is difficult to apply this approach to reveal the change in urban land use social functions, as well as the source and mechanism of spatial scale effect in the refined simulation at block scale. This study identified the refined urban land use characteristics by combining remote sensing images and POI data. Moreover, the optimal spatial scale combination was calibrated for refined land use simulation with the response surface method. Based on the optimal spatial scale combination, the refined simulation of future land use change was performed by using the CA-Markov model. Considering the Wuhan core urban area as an example, the results demonstrate that: (1) POI-based refined urban land use identification method can deeply analyze the social functions of urban construction land, which greatly improves the traditional remote sensing-based macro interpretation of land cover. (2) Optimal spatial scale combination of CA-Markov model for refined land use change simulation in the study area is at the cell size of 30 m and neighborhood size of 7 using the Von Neumann neighborhood type, at which the reliability of refined land use change simulation can be improved. The results of the response surface design can effectively distinguish not only the main sources of the spatial scale effect, but also the magnitude of their influence and the positive or negative effects on the simulation accuracy in the refined simulation process. (3) It is predicted that by 2025 the construction land scope of the study area will continue to expand to the periphery with various types of land interlaced, and the spatial pattern of land use will become more fragmented.

Key words: urban land use change, refined simulation, spatial scale effect, cellular automata, Wuhan city