جستجوی مقالات مرتبط با کلیدواژه « majority owa » در نشریات گروه « جغرافیا »

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.