Simulation of agricultural landscape dynamics using cellular automata

Based on cellular automata, this article proposes a new method of simulating changes in Chinese Northeastern agricultural landscape. This case study in Dehui, China illustrates that natural and human factors are the main drivers of landscape transition. The model is controlled macroscopically by natural and policy factors. A set of principles are generated derived from a former remote sensing data collected over ten years. The shapes of landscape batches and the morphological priority are considered to define the transition rules. It can be concluded that such an approach is effective for agricultural landscape simulation on a county scale.