Investigation of the vegetation Cover Pattern Change Using MODIS Images and its Relation with Rainfall distribution

Rainfall is one of the most important factors affecting vegetation cover. Fluctuation and year-to-year variation of rainfall always affect vegetation cover patterns. The main aim of this study was to investigate and modeling the effects of rainfall changes on the variation of the vegetation cover in the Meyghan basin in Arak province using MODIS satellite images. NDVI, DVI, RVI and EVI indices were used to manifest vegetation covert variations linear and nonlinear relationship between vegetation cover changes and rainfall investigated simultaneously (May), with one and two month delay (April and March) ) during the statistical period of 2000-2017. The rainfall trend analysis was done using non-parametric Mann-Kendall test. According to the results, the minimum rainfall during the 18-year period was increased. Between vegetation indices, NDVI index showed the maximum and the average incremental trend. Between precipitation and vegetation, third-order non-linear relationship was stronger than linear, quadratic, power, logarithmic and exponential. The maximum correlation between DVI index and rainfall was obtained for synchronous times, while, the maximum correlation was observed between NDVI index and precipitation. The study with two month delay showed that the maximum correlation (0.52) was between the RVI index and precipitation. Vegetation modeling using simultaneous rainfall and delay of up to two months showed that the indices of DVI, RVI and EVI provided the best regression relationship at the same time, while the NDVI index had the best regression relationship with rainfall of two months ago.