Albedo is a key parameter in climatic research and depends on environmental and climatic factors. Modeling these factors greatly contributes to understanding environmental variations. To this end, the data of Land Surface Albedo, Land Surface Temperature (LST), Vegetation, Snow, Elevation, Slope, and Aspect of the MODIS sensor from 1/1/2001 to 30/12/2021 with a 1000-m spatial resolution were used. After pre-processing, monthly, seasonal, and annual albedo modeling was performed using multiple linear regression (MLR) in the highlands of Iran. The results of monthly modeling revealed the salient direct role of snow on the albedo of Iran's highlands in all months, except for July, August, and September. In these months, due to the lack of snow coverage and the fruiting of agricultural lands and gardens, the inverse role of vegetation on albedo variations is determining. Seasonal examinations also showed that snow plays a significant role on the albedo of Iran's highlands in winter, spring, and fall; however, vegetation has a determining role in the summer. The annual results indicated that snow, vegetation, elevation, slope, LST, and aspect, respectively, are the factors affecting albedo in the highlands of Iran. Furthermore, the role of snow, LST, and aspect is positive, while the role of vegetation, elevation, and slope is negative on albedo.
