The use of agent-based models (ABMs) and modelling for understanding landscape change and dynamics continues to grow. One reason for the popularity of ABMs is that they provide a framework to represent multiple, discrete, multi-faceted, heterogeneous actors (human or otherwise) and their relationships and interactions between one another and their environment, through time and across space. This collection showcases innovative uses of ABMs for investigating and explaining landscape change and dynamics and to explore and identify how researchers in different disciplines can learn from one...