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Abstract
Climate change is an important environmental issue because the melting processes of glaciers and snow density are sensitive to climate change. Today, a variety of satellite sensors such as AVHRR, MODIS, GEOS, MERIS are available for snow monitoring and are widely used to investigate and investigate the fluctuations and changes in snow cover globally. Modis sensor has been considered more because of its global spatial coverage with suitable spatial accuracy and frequent temporal coverage on different scales , Therefore, in the present study, snow products of this sensor were used. In this study, after collecting statistics and data on snow-related days during the statistical period (1989-2018) in three provinces of Kermanshah, Ilam and Lorestan, they were processed using Modis snow cover data in middle Zagros as well as remote sensing techniques, Finally, the snow cover changes in the study area were studied in detail. NDSI index was used in MODIS sensor products to detect snow cover. Consequently, in order to differentiate pixels and identify different phenomena, the received images were processed in GIS environment. .  Investigation of snow cover changes in different seasons using Modis sensor images shows that most of the studied area has a significant decreasing trend, especially in the elevated areas of the study area And only in the western and southwestern regions of the study area, there is no specific decreasing trend. Also, the study of snow covered days during the study period indicates a decrease in middle Zagros snow cover and these changes have been intensified in recent years, especially in snow-covered areas of the region. Also, changes in winter and snow-capped and elevated areas were more and more severe than other seasons and other regions in the study area.           

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Widespread and frequent droughts in recent decades in Khuzestan province have become one of the most important challenges of this province. The use of remote sensing products in temporal and spatial monitoring of drought can play a key role in managing this risk and reducing and adjusting its destructive effects. The main goal of this research is to provide a remote sensing index for temporal and spatial monitoring of drought in Khuzestan province and its validation using station meteorological drought indices. In this research, by using the products of vegetation (MOD13C2) and land surface temperature (MOD11C3) of MODIS sensor, a drought index based on vegetation called VHI plant health index was produced. SPI Meteorological Drought Index, which was based on station rainfall data during the statistical period of 2000-2012, was used to evaluate and quantify this index. The comparison of VHI drought index with three-month SPI meteorological drought index values showed a significant correlation between 0.68 and 0.75. By identifying 4 years with widespread and relatively severe drought in Khuzestan province (based on both VHI and SPI indices), which included the years 2000, 2005, 2012, 2015, the spatial distribution pattern of meteorological drought and VHI plant drought to In general, it indicated that the northern parts of the province were generally involved in mild to moderate droughts and the southern parts were generally involved in moderate to severe droughts. The spatial correlation matrix based on the number of 2500 pixels with dimensions of 5x5 km, which included VHI and SPI values of selected drought years, indicated the existence of a significant spatial correlation between the two mentioned indicators. In the widespread drought of 2000, at the level of Khuzestan province, two drought indices VHI and SPI, the correlation was equal to 0.47, and in 2005, equal to 0.35, and

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