پیش بینی تغییرات کاربری اراضی با استفاده از مدل زنجیره ای مارکوف و CA مارکوف (مطالعه موردی: حوزه آبخیز گرین)

Land use change prediction is an important factor in appropriate planning and integrated ecological management of watersheds. There are various methods for modeling and prediction of land use, i.e. Markov chain and CA Markov. In this research, for predicting the land use of Gareen watershed in Iran in 2042, Landsat satellite images of 1986, 2000 and 2014, and the Markov chain and CA Markov was used. In addition, for assessing the accuracy of land use classification, overall accuracy and Kappa coefficient were used. Overall accuracy and Kappa coefficient was obtained higher than 90% that indicate high accuracy of images classification. Results showed that in case of the land use fixed trend during 1986 to 2014, the watershed forest area will increase 5.77% and rangeland area will decrease 6.34% in 2042.