Integrating the system dynamic and cellular automata models to predict land use and land cover change

- System dynamic and CA-Markov models are integrated to predict LULCC.
- Socioeconomic factors strongly affect LULCC area and distribution.
- The integrated approach represents the impacts of external factors on LULCC well.
- Our method can accurately simulate the area and spatial pattern of LULCC.
- Different future development pathways will result in various LULCC patterns.

Land use and land cover change (LULCC) is a widely researched topic in related studies. A number of models have been established to simulate LULCC patterns. However, the integration of the system dynamic (SD) and the cellular automata (CA) model have been rarely employed in LULCC simulations, although it allows for combining the advantages of each approach and therefore improving the simulation accuracy. In this study, we integrated an SD model and a CA model to predict LULCC under three future development scenarios in Northern Shanxi province of China, a typical agro-pastoral transitional zone. The results indicated that our integrated approach represented the impacts of natural and socioeconomic factors on LULCC well, and could accurately simulate the magnitude and spatial pattern of LULCC. The modeling scenarios illustrated that different development pathways would lead to various LULCC patterns. This study demonstrated the advantages of the integration approach for simulating LULCC and suggests that LULCC is affected to a large degree by natural and socioeconomic factors.

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