Using fuzzy cellular automata to access and simulate urban growth

In this paper we present a methodological framework designed to access urban growth dynamics and simulate urban growth. To do so, it utilizes the descriptive power of Fuzzy Logic and Fuzzy Algebra to map the effects of various parameters to the urban growth phenomenon and express them in comprehensible terms. Sensitive Sum, a new fuzzy operator is proposed to employ a parallel connection between the effects of separate variables while taking into account the (statistical) correlation between them. As a result, the model implements a reducible/extensible form of Knowledge Base which can include both data-driven and empirical rules and does not require certain variables/data to run. In order to simulate urban growth Cellular Automata techniques are incorporated that are enhanced by pseudo-agent behavior. The proposed model is applied in the broader Mesogia area in east Attica (Athens, Greece) for the period 2000-2007 during which urban land cover grew by 66% and appears to capture the urban growth dynamics occurred in a satisfactory way.