Potential of dual-pol TerraSAR-X data for Land Cover Classification in Arctic Tundra Landscapes

• Main Authors: Sobiech, Jennifer, Ullmann, Tobias, Banks, Sarah, Roth, Achim, Dierking, Wolfgang
• Format: Conference Object
• Language: unknown
• Published: ESA 2013
• Subjects: Arctic; lena delta; Mackenzie Delta; permafrost; Tundra; Siberia
• Online Access: https://epic.awi.de/id/eprint/33934/; https://hdl.handle.net/10013/epic.42253

Arctic land covers play a critical role in linking the land, atmosphere, and oceans of the Arctic System as a whole, and in determining the role terrestrial ecosystems play in feedbacks to climatic change. Point measurements of ground and soil temperatures, as well as energy fluxes or associated surface parameters like land cover, however, cannot adequately represent the spatial heterogeneity and complexity of Arctic environments. Remote sensing on the other hand, provides a means of obtaining continuous and regional information of high Arctic environments where existing data networks are sparse. This study focuses on Arctic river deltas, namely the Lena Delta in northern Siberia and the Mackenzie Delta in Canada. Both areas are underlain by continuous permafrost. The surface is characterized by polygonal structures, thermo-erosion valleys, shallow lakes, and river channels. The vegetation cover is mainly composed of mosses, herbs, sedges, and shrubs. The surface is generally moist or wet, as the permafrost table acts as boundary for water drainage and evapotranspiration is low. Both deltas can be subdivided into unique geomorphologic units, which show differences in the soil texture, surface wetness and vegetation composition. In the Mackenzie Delta, recent tundra fires have also impacted the vegetation cover. Extensive ground truth data are available for both sites from field campaigns, automatic weather stations, and optical imagery. SAR intensity images alone are often insufficient for accurate classification of these environments, thus it is advantageous to include additional phase-related information. A high spatial resolution is essential to clearly distinguish land and water surfaces. The German X-band radar satellite TerraSAR-X can acquire dual polarized images, which enables the derivation of polarimetric features, including correlation coefficients, phase differences, polarization ratios, Kennaugh and dual-pol entropy / alpha decompositions and others. The goal of this study is to identify suitable ...