Coupling fuzzy sets theory and GIS-based cellular automata for land-use change modeling

Cellular automata (CA) theory in a geographic information systems (GIS) based framework is commonly used for modeling complex system such as urban growth or land-use change. However the geospatial data used in GIS databases and in CA models rely on the traditional crisp/Boolean representation of land-use classes with sharp boundaries. Furthermore, the definition of a CA set of transition rules is based on the concept of crisp rules despite the fact that some descriptive or uncertain knowledge of the system behavior can be better represented with fuzzy logic rules. This paper presents the potential of coupling fuzzy sets and fuzzy logic theory in current GIS-based cellular automata models of land-use transformations.