Modeling Urban Growth using Fuzzy Cellular Automata

Urban modeling is an important tool for efficient policy designing. We herein present a methodological framework for urban modeling which attempts to access the multi-level urban growth dynamics and express them in linguistic terms. The suggested framework incorporates a set of fuzzy systems, each one of which focuses on different aspects of the urban growth dynamics, while the systems’ structure and connection provides a work flow closer to the human conceptualization of the phenomenon. Cellular automata techniques are incorporated in the main system’s inference engine. The proposed modeling structure has been applied and calibrated in Mesogia – Athens.