Abstract
Cellular Automata (CA) approach is based on complexity theory and is widely used in geospatial modeling. A reason for the increasing attention given to CA models is that they can easily be integrated with raster-based GIS environment. However, the behavior of the CA models is affected by uncertainties arising from the interaction between model elements, structures, and the quality of data sources used as model input. The objective of this study is to examine the impacts of model elements on the generated outputs of a GIS-based CA land- use growth model using sensitivity analysis (SA) approach. The proposed SA method consists of cross-tabulation maps, KAPPA index with coincidence matrices, and different spatial metrics. The neighborhood surface is kept constant when different neighborhood size and type configurations are used. The variations of the model simulation outputs were examined and the results suggest that CA model is sensitive on the variation of the neighborhoods elements.
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