fuzzy quantifiers

Abstract Ecotourism is the most sustainable form of tourism, so today it is described as one of the important development criteria. In this research, after preparation maps of 17 ecotourism index including altitude, vegetation density, vegetation type, land use and land cover, gradient (in terms of tourist attraction), geographic orientation, slope (in terms of domain stability) Sensitivity to erosion, landslide sensitivity, earthquake sensitivity, distance from the road, distance from the river, distance from the spring and well, distance from the village, distance from the city, distance from attraction Natural tourism and distance from holy places, map of the potential areas of ecotourism development in Dena county in northern Kohgiluyeh and Boyer Ahmad province with an area of over 1575 square kilometers was prepared using fuzzy quantifiers and different decision making scenarios under the OWA algorithm. According to the  analytical network process, the landslide susceptibility index and geographic direction had the highest and the least relative importance regarding identifying ecotourism development areas among the indicators studied. The suitable areas for the development of ecotourism in the county of Dena from the total area of the region in the highly optimistic decision-making scenario to there is no suitable area in the highly pessimistic decision-making scenario. In highly optimistic decision-making scenario, if at least one of the indices in the region is recognized as suitable for ecotourism, then that area in the final compilation map is considered suitable for the ecotourism. In the highly pessimistic decision-making scenario, all indices in the region should be is recognized as suitable for ecotourism, so that the area in the final compilation map is suitable for ecotourism.

Cities like living organisms will become more complex from the structure point of view and become greater from physical view and following this physical growth, their economical, social and cultural development is changed gradually. Always the physical environment of the cities are under the effect of such mechanism and factors which will change during the time by the economical, social, cultural, political , environmental progresses and changes. Also these impacts impose new changes on the feature and physical landscape of the city. Therefore, Preventing the unbalanced and uncontrolled growth of cities has high importance because of high value of land. Therefore, modeling and forecasting of land use changes in future have become more important for urban managers and other decision makers. The Cellular Automata model has vastly been used in temporal-spatial changes simulation because of its simple and dynamic structure and the power of geospatial analysis. In this paper, with considering the existing limitations in current cellular pattern, a combined automata model has been presented which is an integration of the cellular computational structure and multi criteria decision making approach, Majority OWA. The Cellular Automata model uses average method for combining land use suitability maps and computing the total general suitability that it is not suitable in many applications. But Majority OWA approach considers opinion of majority for combining several criteria to evaluate an alternative, so incorporation the two approaches cited can rectify one of the important defects in cellular automata model. This article, at first, by implementation of the proposed model for simulation of Shiraz city’s propagation between 2004 to 2009 years and then obtained results have evaluated.Comparing the obtained results in this article for year 2009 by the data obtained from satellite photos in this year shows that using Majority OWA method can model urban development process by 60% accuracy which in comparing with accuracy 53% of CA model, better results can be achieved. The research findings is a forward step, because the proposed model by increasing the capability of Cellular Automata in modeling the complicated location processes has achieved a better accuracy. The results obtained from this modeling can be presented to the urban planners as an appropriate tool for taking optimum decisions.