Land vulnerability one of the major global challenges as an objective case of degradation of arid, semi-arid and semi-humid ecosystems caused by natural processes and human activities. However, in order to assess the vulnerability of the land, it is necessary to know exactly the degree of tolerance of ecosystems and the use of indigenous knowledge systems to external conditions.The present study was based on the IDI hybrid index algorithm to assess the severity of Khorasan Razavi vulnerability over a 16-year period (2001-2016). For this purpose, two indicators of vegetation status (VCI) (MOD13Q1) and temperature status (TCI) (MOD11A2) based on the opinion of experts, and according to the availability of these indicators, based on satellite data and in The desired time period was selected. Then, the images of Modis sensor products were prepared and normalized, and the indices were scaled in the range of zero and one, and the hierarchical method in EDRISI software was used to evaluate the weights. Using 250 ground harvest points, the accuracy of the model was determined using kappa coefficient for vegetation status. Then, using IDI combination model and implementation of the model, the area has very low vulnerability (0-15 . 0), low vulnerability (0.3-0.3), medium vulnerability (3.5-3.0) 0), high vulnerability (0.5-0.7) and very high vulnerability (1-7 . 0). The results showed that the highest vulnerability in 2001 with more than 50 percent of the province's average in the middle class and in 2016, the highest vulnerability in the two medium and high classes is approximately equal to the proportion of 44 percent. The overall accuracy of the model for the IDI combination model was 78.6% and the Kappa coefficient was 0.7.