Abstract
Geographical Information Systems (GIS) adopt a top-town approach which may have limitations for solving many landscape simulation and planning problems. Recently, a number of bottom-up models, such as cellular automaton models (CAs), agent-based models (ABMs), and swarm intelligence models (SIMs), have emerged as an important tool for assisting complex decision-making processes associated with landscape changes. These bottom-up models can be combined together and integrated with GIS to produce better modeling effects. This paper discuses the potentials and challenges for using these models.
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