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ABSTRACT:This research is dedicated to the investigation of the relations between the XXI century climate changes and Normalized Difference Vegetation Index (NDVI) variability of the taiga zone. For this purposes was used the observations of vegetation variability on the test area located nearby Syktyvkar city (Komi Republic, Russia), 16-day averages of NDVI data derived from TERRA/MODIS space imagery (spatial resolution is about 250 meters), and the air temperature and precipitation observations from Syktyvkar meteorological station. The research results confirmed the statistically significant positive correlation between NDVI and air temperature for all vegetation types of the test area, for both spring and autumn seasons. The weakest correlation was found for coniferous forest, namely, pine forest on poor soils, and the strongest correlation was found for meadows and bogs. Additionally the map of NDVI trends of the test area shows that the sectors of greatest positive trend located on the territories with non-forest cover, and as a result, the positive trend of air temperature is indicated most brightly on vegetation of non-forest lands. Thereby these lands can serve as climate changes indicator in the investigated region.

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ABSTRACT:The study is devoted to the investigation of regional climate change in Northern Russia. Due to sparseness of the meteorological observation network in northern regions, we investigate the application capabilities of remotely sensed vegetation cover as indicator of climate change at the regional scale. In previous studies, we identified statistically significant relationship between the increase of surface air temperature and increase of the shrub vegetation productivity. We verified this relationship using ground observation data collected at the meteorological stations and Normalised Difference Vegetation Index (NDVI) data produced from Terra/MODIS satellite imagery. Additionally, we designed the technique of growing seasons separation for detailed investigation of the land cover (shrub cover) dynamics. Growing seasons are the periods when the temperature exceeds +5°C and +10°C. These periods determine the vegetation productivity conditions (i.e., conditions that allow growth of the phytomass). We have discovered that the trend signs for the surface air temperature and NDVI coincide on planes and river floodplains. On the current stage of the study, we are working on the automated mapping technique, which allows to estimate the direction and magnitude of the climate change in Northern Russia. This technique will make it possible to extrapolate identified relationship between land cover and climate onto territories with sparse network of meteorological stations. We have produced the gridded maps of NDVI and NDWI for the test area in European part of Northern Russia covered with the shrub vegetation. Basing on these maps, we may determine the frames of growing seasons for each grid cell. It will help us to obtain gridded maps of the NDVI linear trend for growing seasons on cell-by-cell basis. The trend maps can be used as indicative maps for estimation of the climate change on the studied areas.