Simulation of land use changes in urban fabrics: Integration of Monte Carlo approach, fuzzy logic and cellular automata (Case study: Isfahan’s 7th municipal district)

Land-use change is one the most prominent problems which should be addressed by planners and decision makers. As this problem deals with a large set of data and variables, application of advanced techniques and computer-based methods for prediction and simulation of land-use change is inevitable. For this reason, various methods have been developed to obviate the underlying complexity of land-use changes. Due to the uncertainty of land-use change process, competitive essence of land types for occupying vacant lands and lack of these items in the structure of the existing models, this paper aimed at developing a model based on cellular automata (for representing dynamics of the change process), fuzzy logic (for representing uncertainty and probability underpinning land use change phenomenon) and Monte Carlo approach (for representing spatial competition) to make more satisfactory results than previous conventional CA-based models. Therefore, in this paper, firstly, a flexible framework of the proposed model (IMCFA) is completely described and the process of land use change is mathematically expressed. Then, the model is calibrated and implemented on the study area together with FCA and conventional CA for simulation of two pre-defined scenarios in two time periods, 2012-2022 and 2022-2032. Finally, three indicators (compactness, compatibility and land suitability) are measured on the outputs of the models to make modelling assessment process possible. The results showed that for our defined problem, IMCFA generated more satisfactory results than FCA and conventional CA. Moreover, FCA represented more acceptable outputs than conventional CA according to the above mentioned indicators.