The Polar Terrestrial Environmental Systems Research Group at the Alfred-Wegener-Institut has multiple field trips a year that, among other goals, aim to collect data to monitor the landcover and vegetation dynamics in the Arctic region. Vegetation dynamics can provide an insight into the effects of global warming on the environment. The aim of the current project is to employ Machine Learning and Deep learning methods to analyse this data to gain better insights into the dynamics of the vegetation species and how these are changing over time. In order to accomplish this goal, various types of Remote Sensing data is used such as Sentinel-2, Landsat 7/8 as well as drone data collected in the field. The ultimate goal is to develop a fusion method that can utilise the available data to create a comprehensive overview of vegetation dynamics of the past, present and future.