عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Multi spectral images of remote sensing are very efficient in gaining a better understanding of the environment. Therefore, with regard to the extensive changes in land use and vegetation, using remote sensing technology and monitoring has become an important tool. This study aims to assess land use changes in the percentage of vegetation cover in Yasooj city and surrounding areas. Therefore, the image sensor TM satellite LANDSAT dated 21 and 22 December 1998 and 2010, 13 and 14 June in 1987 and 2010, maps land use and normalized vegetation index NDVI algorithm maximum likelihood Mahalanobis Distance and the minimum distance; Supervised Classification were provided. Results showed that the highest amount of use area was devoted to 1986 barren with 14.2 square kilometers and then urban use with 26.3 and afterward green space with 15.2 square kilometer area had the lowest value, whereas in 2010, the highest rate in the area was devoted to urban use with 10.27 square kilometers and then barren use with 8.68 square kilometers and finally at the end of the vegetation cover with 0.66 square kilometer had the lowest space in the area. The highest rate of changes were related to residential use with 157 percent during this period (an increase of 7 square kilometers). However, the barren land (5.52 square kilometers) and green space (1.49 square kilometer) saw a decreasing trend in surface area in 1986 to 2010. . Providing buffer traced of five kilometers around the city, it was revealed that a map of vegetation index and vegetation of the area decreased over 70% (to 16.42 square kilometers) and 60 to 70 percent (to 55/13 square kilometers) whereas the area of vegetation increased less than 60% (to 56/71 square kilometer). Also overall accuracy for evaluation algorithms represented that monitor changes in the maximum likelihood and Mahalanobis Distance methods had the highest accuracy and while the minimum distance had the least accuracy in extracting triple uses of residences, barren and green space.