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 Risk assessment of soil erosion, one of the most important land degradation problems worldwide, is very essential for land and water resources management, and development of soil conservation methods. In the present study, the temporal changes of soil erosion risk were assessed from 1987 to 2010, based on the Revised Universal Soil Loss Equation (RUSLE) using Remote Sensing (RS) and Geographic Information Systems (GIS) for the Navrood Watershed, Iran, with an area of 270 km². Two Landsat satellite imageries obtained in 1987 and 2010 were used to assess the changes in vegetation cover during this period, and to obtain the Cover factor (C) of RUSLE. Rainfall and soil texture data and a digital elevation model were used to calculate the rest of RUSLE factors, which were taken as constant for the study period. The results showed that the average annual soil loss over the watershed ranged from 0 to 1,056 t ha^-1 y^-1(Cumulative percentage> 99.9%). The area mapped as very high erosion risk (> 100 t ha^-1 y^-1) increased from 10% in 1987 to 12% in 2010, and the area of the next risk class (51-100 t ha^-1 y^-1) increased from 8 to 9%. These changes cover an area of about 800 ha in the watershed, in which erosion risk has been doubled or tripled in the last 23 years. Forest clearing and rangeland overgrazing were identified as the most important reasons for the increase in erosion risk.

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This study aimed first to investigate the relationship between Normalized Difference Vegetation Index (NDVI) and vegetation attributes (vegetation cover, bare soil, litter frequency, and the amount of biomass) and, then, evaluating the vegetation changes using NDVI in semi-arid rangeland in western Iran. Ground data were collected to assess the accuracy of NDVI index.   For this purpose, 14 sampling units were randomly selected for collection of vegetation attributes including biomass, vegetation cover, litter, and bare soil. Then, the correlation between digital pixel values ​​and the sampling units were analyzed. The results showed that NDVI was highly correlated with all vegetation attributes. The maximum correlation was related to vegetation cover (0.84). So, to evaluate the vegetation changes, the NDVI maps were created in 1986, 2001, and 2013. The results showed that the amount of class 1 (very poor vegetation cover) increased from 0.27 km² in 1986 to 12.89 km² in 2013, and also class 4 and 5 (good and very good vegetation cover, respectively) decreased about 27.8 and 37.7%, respectively. The relationship between precipitation and temperature with NDVI was investigated to assess the sensitivity of NDVI to these parameters. The results showed that the amount of precipitation decreased during the studied time periods. This parameter seems to be one of the most important factors affecting the vegetation in our study area.