With the passage of time and increasing population growth, the pressure on exploitation of natural resources, especially on rangelands, has increased. The severity of degradation is increasing day to day. Evaluation of rangelands degradation is done using a variety of methods. The best solution is the combination of remote sensing, geographic information systems, and field studies. In this research, remote sensing technology was used to evaluate the rangelands degradation in Fereydounshahr region, Isfahan province.For this purpose, related Landsat 5 satellite imageson June 1987,related Landsat 8 image on May 26th, 2016, andrelated Sentinel 2 image on July 17th, 2016 in FereydounShahr region, Isfahan province, as well as related image of the MODIS sensor on July 2012 in Isfahan province has been used. Geometric, atmospheric, and topography correction algorithms were used to preprocess the images. In this study, the application of moving standard deviation index (MSDI) has been investigated for evaluating the rangelands degradation in Fereydounshahr county.To calculate this index, a 3 × 3 filter was passed through the red band of satellite images (Landsat 5 and 8, Sentinel 2 and MODIS). Then, by calculating the standard deviation of 9 pixels, the MSDI index was calculated for three rangeland locations with good, moderate and poor conditions. To compare the performance of the MSDI index, the NDVI vegetation index was calculated by using red and infrared bands. The results of this study indicate that considering the different nature of the data of different sensors, assessing rangelands degradation and determining rangelands positions,according to the NDVI and MSDI indexes extracted from these data, did not match the results of field studies.The reason is that the factors affecting rangeland conditions are different in remote sensing and field methods. However, by examining the results, it can be seen that among the four Landsat 5, Landsat 8, Sentinel 2 and MODIS images, Sentinel 2is the best image for working with NDVI and MSDI indexes. Because the NDVI and MSDI indexes have been able to better predict the conditions of rangeland locations on this image similar to their fieldconditions. Also, the results show that the NDVI index has been able to better determine rangeland positions in almost all images compared to MSDI.The reason is that in the field studies and NDVI index, the percentage of canopy is a very important and effective factor.So, there are more similarities in the results of these two methods. But the situation of MSDI index is different, because the index is affected by spectral heterogeneity and the rangeland condition is determined just by this factor.The results of ANOVA showed that NDVI index was statistically different in Sentinel-2 and MODIS images for different conditions of rangeland locations. But, this index did not show statistically differences between Landsat 5 and 8 in different rangeland locations. In none of the images, the MSDI index showed a significant difference between different conditions in rangeland locations. Since MSDI is dependent on spectral diversity, it is recommended that this index be evaluated and calibrated in areas with high vegetation degradation, such as surrounding villages and areas with high vegetation diversity. Key words : Landsat,MODIS,MSDI,NDVI,Sentinel,Rangeland condition.