Analysis of NDVI variation and snowmelt around Zackenberg station, Greenland with comparison of ground data and remote sensing
Abstract: Snow and permafrost are significant climatic factors affecting the climate in high latitudes and especially in arctic regions. Moreover, results of conducted scientific studies have shown that snow is crucial for photosynthetic activity and therefore vegetation vigor and growing season in arctic environments. This master thesis aims to investigate the changes in photosynthetic activity in Zackenberg, located in the eastern coast of Greenland with estimation of the fluctuation of the normalized vegetation index (NDVI) from satellite images and the changes in snowmelt and active layer thickness with the study of ground data obtained by scientific measurements conducted in the established research station of Zackenberg. Moreover, this study tries to relate the variations in photosynthetic activity expressed by the vegetation index with snow depth and length of snow season, as well as with properties of permafrost, like the thickness of the active layer. The time period for which this study is conducted includes the last 10 years, between 2005 and 2014. Analysis is performed with the help of statistics and by using principles of regression analysis. Results show fluctuations in photosynthetic activity as well as in the duration of the growing season. Furthermore, correlations between snow depth and time of snowmelt (expressed by snow cover percentage) and photosynthetic activity are detected from the regression analysis, showing that snow depth and time of snowmelt affect the seasonal vegetation activity and enhancing the argument on the importance of snow for the high northern latitudes. On the other hand, results from the regression analysis show that photosynthetic activity is not affecting the active layer thickness.
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