Classification and mapping of the Devon Ice Cap based on TerraSAR-X data from 2017 to 2020

Abstract

Devon Ice Cap in Nunavut, Canada, is one of the largest ice caps in the Canadian Arctic. A complete melting of the glacier would mean a global sea level rise of 1 cm. Since data collection and exploration of the glacier began in 1961, the glacier area has decreased by 2.4% (about 340 km2) (Boon et al., 2010). This bachelor thesis deals with the classification and mapping of the different glacier zones for the observation period from 2017 to 2020 by analysing satellite radar data. As source data, TerraSAR-X backscatter values in the X-band pre-processed by the German Aerospace Center (DLR) into the MutliSAR System were used. These contain the backscatter values of radar image scenes as georeferenced raster files. The data are available for the observation period for three orbits in temporal resolution of 11 days. The geometric resolution is 40 m * 40 m per pixel. Backscatter values of objects in the radar image depend on their dielectric constant (signal transmission) and the image geometry of the radar zone. The backscatter of glacier zones can be used for the detection of zone classes. In this work, backscattered areas are associated with specific glacier zones, linked to an elevation model of the TanDEM-X mission and temperature data to provide information about the structure of the Devon Ice Cap and its development over the observation period. The goal of this work is to use remote sensing data to make statements about the composition and changes of the glacier and to link these to local meteorological data. Finally, the influence of the topography of the terrain on the classification quality is analyzed. To visualize the results, maps and time series are generated, on which the seasonal and long-term effects can be traced.