Uncovering Stakeholders’ Participation to Better Understand Land Use Change Using Multi-Agent Modeling Approach: An Example of the Coal Mining Area of Shanxi, China

Recent decades have witnessed increasing human disruption and the acceleration of fragile natural habitats, especially in coal mining areas in developing countries or regions, which will inevitably lead to sharp land use and cover change (LUCC). Most LUCC models focus more on the research of “land” than “human” in human-land coupled systems, while the simulation and prediction of LUCC involving stakeholders are still deficient. Aiming to reveal the shaping process of LUCC through the stakeholders’ participation, we conducted an in-depth interview in a typical coal mining area of Shanxi, China, and developed an agent-based model by quantifying the stakeholders’ land-use decision-making rules to simulate and predict land use change in different scenarios. The analysis illustrated that the stakeholders’ participation in different periods had shaped the land use pattern in the coal mine area. The area of cultivated land has decreased from 272.34 hm 2 to 118.89 hm 2 , while industrial and mining land increased dramatically by 78.66 hm 2 from 2012 to 2019. The attitude and willingness of farmers towards land use varied greatly and were affected by livelihood capital. Part-time farmers whose agricultural income only accounted for 20–80% of the total income were in favor of farmland requisition by coal mining enterprises compared to full-time farmers. We quantified the rules between the attributes of the stakeholders at the micro level and land use changes at the macro level and proposed the multi-agent simulation model, which was effective and verified by a fitting test where the overall accuracy of the Kappa coefficient was 0.83 and could be used to predict future LUCC in research areas by setting the decision parameters in specific scenarios. These outcomes provided a scientific reference for landscape simulation and the prediction of a human-land coupling system while promoting the effectiveness of spatial planning policies.