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Rainfall and temperature are the key factors responsible for vegetation condition, health and growth. This research work analysis spatiotemporal phenomena in between SPI, LST and VIs in summer session from 2000 to 2018 in European Russia. This study used MODIS, NDVI, LST and TRMM data. The negative SPI values represent increasing drought events with reducing rainfall and vice-versa. Numerical consequences specify that mean annual rainfall, VIs variate according to SPI values and they completely change in the year 2004, 2009 and 2015. VIs also indirectly related to LST as high LST values (high temperature) associated with low VIs values (low vegetation) and vice-versa, with correlation coefficients 0.90. Correlation analysis of VIs, SPI and LST indicate close relationship in between vegetation, rainfall and temperature and this relationship can be used for near real time vegetation drought dynamics monitoring through satellite data for short term to long term changes in vegetation growth.

Detecting vegetation drought dynamics in European Russia