Prioritization and Selection of Protected Areas Using Simulated Annealing Algorithm

Most of the current protected areas in Iran have been selected using a non-systematic approach or at best used the general IUCN criteria. Economics and policies have important roles in the selection of such areas which in some cases contradict with their ecological values. Hence, most of these areas have relatively low economic value. Also, there are different goals and criteria for protection while people have different standpoints that create a situation where various sites are candidate for protection. Hence, there is a need to an approach that simultaneously considers all of these criteria, and goals and selects the largest, the most complete and integrated area for protection. One of the approaches to reach this goal is artificial intelligence. This approach includes different computer algorithms that present near optimal solutions based on the definition of an objective function. One of the most widely used algorithms in the optimization process and spatial arrangement of suitable sites is simulated annealing. This algorithm considers different areas for protection. In this algorithm, a multi-dimensional space is characterized in terms of objectives and various options are produced, that accommodate our multi-dimensional goals. Finally, areas that meet our objectives are selected. In the present paper, the application of simulated annealing, in the optimization process and in the prioritization and selection of suitable areas for protection through Marxan Software is discussed. Vegetation types and wildlife distribution areas have been used as protection criteria. Multi criteria evaluation and zonal land suitability were used to produce wildlife distribution maps. Result of the Marxan is a map of suitable sites for protection which can be used for selection of new areas and amendment of the current protected areas.