Cellular automata-based spatial multi-criteria land suitability simulation for irrigated agriculture

Cellular automata (CA) models are increasingly used to simulate various dynamic courses,.g. urban spatial growth, forest fire spread and soil desertification. CA can express space tructures and patterns of complex systems, which are difficult to perform only with athematical quations. In this study, a new CA-based spatial multi-criteria evaluation MCE) methodology was eveloped to conduct land suitability simulation (LSS). The pproach incorporated MATLAB to build the analytical hierarchy procedure (AHP) for riteria weighting. The method is implemented as a tool, called AHP-CA-GIS, using C# NETcomputer language in ArcGIS environment. It has djustable parameter values which llow users to rectify model inputs for deriving different scenarios. It is spatial-based, lexible, low-cost and robust, as well as suitable for long-term evaluation. It has increased he scope of GIS application in MCE and makes the application practical for decisionmaking. he AHP-CA-GIS model has been applied to simulate an evaluation of irrigated ropland suitability in the Macintyre Brook catchment of southern Queensland, Australia. ive suitability scenarios were generated. The resultant land suitability map was compared ith present land use. The analysis has clearly revealed the potential for irrigation expansion n the catchment. It has also represented the possible suitability of spatial distribution in the long run. This, in turn, can help the decision-makers optimise land allocation and make better land-use planning decisions.