Agent-based modeling in land use and land cover change studies

This paper presents an overview of agent-based models in land-use/cover change studies. This special class of LUCC models combines a cellular landscape model with agent-based representations of decision making, integrating the two components through specification of interdependencies and feedbacks between agents and their environment. The authors first explain the related concepts of agent based models. Then we briefly discuss recent studies that apply agent-based modeling to study land use/cover change for practical cases. Finally, we discuss limitations of agent-based methods in LUCC modeling. We find that agent-based models are particularly well suited for representing complex spatial interactions under heterogeneous conditions and for modeling decentralized, autonomous decision making. We conclude that, while significant challenges exist, these models offer a promising new tool for researchers with the goal of creating fine-scale models of LUCC phenomena that focus on human-environment interactions.