Amin Mohammadi Dehcheshmeh - Senior expert of Jahad Nasr company of Yazd, Yazd, Iran
Razieh Mirfazlullah - Employee of document registration office of Mashhad, Mashhad, Iran

Remote sensing is one of the effective tools to study the process of land use change on a large scale and in a short time. In this research, the aim is to monitor and analyze land use changes using satellite images and remote sensing from ۲۰۱۰ to ۲۰۲۰ in Sabzevar city with Landsat images. For research, preprocessing included atmospheric correction and radiometric and geometric correction. A total of ۲۰۰ ground control points were collected to classify and evaluate the accuracy of the classification with the maximum probability classification algorithm in the ground visit. The classification results showed that the forest area in ۲۰۱۰ was equal to ۶۸۹۸۰.۲۱ hectares, which with the change of use and its conversion to residential use, barren and rainfed agriculture in ۲۰۲۰ reached ۶۶۰۴۴.۹۹ hectares, ie ۲۹۳۵.۲۲ hectares, its area has decreased. Residential use with its growth in ۲۰۱۰ to ۲۰۲۰ has increased from ۲۸۵۵.۸۹ to ۴۵۶۳.۹۸, ie ۱۷۰۸.۰۹ hectares. Land use changes in semi-dense rangeland have also decreased from ۱۶۷۱۶۴.۸۹ to ۱۵۳۲۸۷.۶۸ hectares, i.e. ۱۳۸۷۷.۲۱. Kappa coefficient and overall accuracy in ۲۰۲۰ were ۹۸.۴۲ and ۹۷.۸۴, respectively, which was the highest value compared to previous years. In this study, it can be recommended that the government increase the vegetation of the land to protect pasture and forest uses against further changes, and to compensate for these changes, to plant fast-growing forests.

land use, remote sensing, Maximum Probability, Landsat