Aridity is a climatic characteristic that has a significant impact on many aspects of life, mainly in agriculture but also in other economic sectors. In this study, a Google Earth Engine (GEE) platform was implemented to monitor and Evaluation of two aridity indexes, such as the De Martonne aridity index, and FAO aridity index at ten stations in Razavi Khorasan province from 2000 to 2021. The University of Idaho's monthly climate data set (TerraClimate) is used to calculate monthly potential evaporation and transpiration. MODIS dataset (MOD11A1 V6.1) used to calculate temperature. The product dataset (CHIRPS) is used for calculating the monthly rainfall. Satellite data, in comparison to the aridity index calculated with ground data, is evaluated using widely accepted statistical indices such as the correlation coefficient (CC), relative bias (RBIAS), root mean squared error (RMSE), Nash–Sutcliffe model efficiency coefficient (NSE), and probability of detection (POD). The results showed that the De Martonne aridity index in Mashhad, Torbat Jam, Neishabour, Gonabad, and Golmakan stations, with a correlation coefficient in the range of 0.704-0.851, root mean square error in the range of 1.228-2.419, relative bias (negative) in the range of 0.096-0.227, Nash-Sutcliffe index in the range of 0.142-0.633, and the probability of estimation in the range of 0.773-1, was chosen as the best method of calculating the yearly aridity index. In other studied stations, the FAO method is the best. Overall, the current study's use of satellite data is appropriate and yields dependable and satisfying results because of its suitable spatiotemporal separation.