The assessment of relationships between satellite-derived vegetation indices and meteorological drought improves our understanding of how these indices respond to climatic changes. The combination of climate data and the Normalized Difference Vegetation Index (NDVI) product of Moderate Resolution Imaging Spectroradiometer (MODIS)imagery provided an opportunity to evaluate the impact of drought on land degradation over the growing seasons. The main goal of this study was to investigate the effect of drought on vegetation degradation in Meyghan plain, Arak, Iran. For this purpose, climatic and satellite data were used. The annual Standardized Precipitation Index (SPI) was calculated for 20 years (1998-2017). Then, the NDVI maps were classified into three classes according to the Tokunaga-Thug method. These classes are: Class 1) no vegetation; class 2) low-density or poor rangelands, and class 3) semi-dense and dense vegetation cover such as agricultural lands.The relationship between the percentage of vegetation cover classes (classes 2 and 3) and the drought index of the previous year was assessed using the Pearson correlation test. The results showed that the correlation between these variables was significantly dependent on vegetation degradation in the poor vegetation area (R=0.51; P-value<0.05). In contrast, there was a negative significant relationship between drought and the percentage of dense areas of vegetation (R=-0.46; P-value<0.06). Hence, it was concluded that the sensitivity of the low-density area (poor rangeland) to drought was more than dense vegetation covers (agricultural lands).Its reason is that the most important source of water supply for natural rangelands is the atmospheric precipitation that has been reduced due to the occurrence of droughts in recent years.
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