The main aim of this study was to model and predict rangeland readiness using and phenology in rangelands of Isfahan Province. and phenology were investigated three phases of field sampling, remote sensing and modeling. In order to find the best vegetation index for vegetation monitoring, 14 vegetation indices were derived from Landsat 8 (OLI) images and compared with ground-based canopy cover in Khansar County. The best-performing index was then used to study other vegetation parameters such as leaf area index (LAI) and crop production and also monitor drought (using SPI index) in Khansar County. Ultimately, the amount of change in , soil moisture and phenology across the entire Isfahan Province were assessed. According to results, NDVI was selected for vegetation assessment and monitoring due to its ease of calculation, acceptable accuracy and availability. LAI monitoring using this index indicated that it peaked in May and then decreased. Moreover, LIA index correlated more strongly with NDVI than canopy cover and annual production in Khansar County. In total, the amount of modeled in this research ranged from 0 to 79 g m-2y-1. The plant phenology determined using MODIS-derived GDD indicated that the amount of GDD in Isfahan province differed significantly in eastern and western regions due to climatic disparities such that it increased from 0- 160 in the onset of the growing season to 577- 5090 towards the end this season. The rangeland grazing readiness produced from phenology, and moisture showed that the grazing capacity of the province ranged from 0 to 1.6 Unit/ha/y-1. More than 91% of the province’s area had a grazing capacity of 0 to 0.25 Unit/ha/y-1, nearly 7% had a grazing capacity of 0.25 to 0.5 Unit/ha/y-1 and the remaining area had a high grazing capacity of more than 0.5 Unit/ha/y-1. Eastern parts of the province had no grazing capacity because of significant water resource limitation. Next, the results of -based modeling of , soil moisture, phenology and rangeland readiness showed that precipitation contributed most in plant production. Precipitation was found to be the most important factor in modeling soil moisture
