Predicting changes in land use of using multitemporal images and CA_ Markov Model(Case Study: gonbad kavoos)

Nowadays, modeling and simulation of urban growth using satellite images can be a very useful tool for describing the interactions between man-made and natural environments to help planners make decisions in complex situations. Inrecent years, many lands of Iran cities, especially marginallands of cities affected bythe processof urbanization andthe citizens need tonew house,landusechanged and have been converted to made areas.Given that, The proper detection of changes in surface forms provides a better understanding of the relationships and interactions among human and natural resources to enhance management of the resources. There are several methods for detecting land use and land cover changes. Post- classification is one of the most effective ways to detect the changes. The purpose of this study is to detect land cover change in Gonbad Kavoos province. For this purpose satellite images for the years 1987-2000 and 2010 were prepared and for processing of these images and obtaining the subsequent data, a number of softwares including GIS and ENVI, IDRISI were employed. This study sought to assess changes in land use in Gonbad Kavoos province during the years 1987, 2000 and 2010 and then anticipate the development of the province using CA Markov model. The results of the study revealed that the growth changes between 1987 and 2010 were for urban users 217.3%, irrigated land 53.5%, rainfed land -40.4%, Barren lands 87.7%and parks 198.6%. The growth of Gonbad Kavoos over the coming years irrigated lands in the south, the southeast and the east of the province will be took over by the growth of the Gonabd Kavoos city,