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Remote sensing is a convenient tool for the study of vegetation cover conditions and dynamics using normalized difference and enhanced vegetation indices. Determination of the connection between weather and vegetation indices plays an important role in better understanding peculiarities of ecosystems reaction to changing climate conditions. The study devoted to the evaluation of annual and long-term dynamics under vegetation cover conditions, and its reaction to the climate factor, was performed through the establishment of the link between remote sensing information (smoothed time series data on normalized and enhanced vegetation indices) and results of on-land hydrometeorological observations for air temperature and precipitation amounts in Kherson oblast of Ukraine during the period from 2012 to 2019 by the means of linear regression analysis of the data. The values of the studied vegetation indices (Terrain MODIS NDVI and MODIS EVI 250 m smoothed time series) were calculated and generalized by the means of GDAL raster analysis toolkit in QGIS 3.10. Statistical data processing was performed using BioStat v7 software. It was found that there is a strong tendency towards the enhancement of vegetation in the region year by year. Climate has strong effect on the vegetation, and the main input belongs to air temperature, while precipitation amounts cannot be considered as a driving force of changes in the growth of vegetation. Enhanced vegetation index seems to be more reliable for the estimation of vegetation cover conditions in comparison to normalized difference vegetation index.
Pavlo Lykhovyd (Sun,) studied this question.