GIS and spatial analysis is suited mainly for static pictures of the
landscape, but many of the processes that need exploring are dynamic
in nature. Dynamic processes can be complex when put in a spatial
context; our ability to study such processes will probably come with
advances in understanding complex systems in general. Cellular
automata and agent-based models are two prime candidates for exploring
complex spatial systems, but are difficult to implement. Tools that
help build complex simulations will create larger user communities,
who will probably find novel solutions for understanding complexity.
KEYWORDS: AGENT-BASED MODELS, CELLULAR AUTOMATA, COMPLEX SYSTEMS, TOOL
DEVELOPMENT