Dynamic Simulation and Forecasting of Spatial Expansion in Small and Medium-Sized Cities Using ANN-CA-Markov Models

This study utilizes the ANN-CA-Markov (Artificial Neural Network-Cellular Automata-Markov) model to address spatial planning and expansion challenges in China’s small and medium-sized cities. With China’s urbanization rate reaching 59.58% in 2018 and expected to hit 70% by 2030, the country is entering a mid-stage of urbanization, leading to rapid expansion of megacities and a gradual decline in smaller cities. The study aims to dynamically simulate urban spatiotemporal evolution and predict future land use changes, integrating land use data, DEM elevation, transportation, administrative centers, and ecological information. The model forecasts the ecological spatial layout of Wanzhou District by 2025, with results indicating a slight decrease in ecological space and an increase in construction land. This suggests a need to balance urban development with ecological sustainability amidst rapid urbanization. The study demonstrates the high accuracy of the ANN-CA-Markov model in predicting land use changes and provides valuable insights for urban planners in making informed land use decisions.

@article{Gao2024,
  title     = {Dynamic Simulation and Forecasting of Spatial Expansion in Small and Medium-Sized Cities Using ANN-CA-Markov Models},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {15},
  number    = {8},
  year      = {2024},
  publisher = {The Science and Information Organization},
  author    = {Chengquan Gao},
  doi       = {10.14569/IJACSA.2024.01508101},
  url       = {https://doi.org/10.14569/IJACSA.2024.01508101}
}