Current climate change in the Arctic is unpreceded in the instrumental record, with profound consequences for the environment and landscape on both regional and global scales. Understanding past landscape (in)stability and evolution in this sensitive area is essential for understanding the response of the Arctic to current and future climate change impacts. This understanding starts with accurate and detailed mapping. However, traditional landform mapping approaches are often conducted at a local scale and the results cannot easily be scaled up to wider areas. As such, regional-scale mapping information is required for robust analysis of landscape evolution. Semi-automatic data-driven analysis provides a mechanism for efficient investigation of large areas, addressing this gap.
In this project, we aim to:
1) Develop a systematic, semi-automatic mapping approach to produce a regional polygon-based inventory of aeolian sand dunes in the European Arctic (northern Sweden, Finland and Norway)
2) Interpret the distribution and orientation of mapped dunes within geomorphic settings in terms of sediment sources, sand transport vectors (wind directions) and reworking history
3) Apply radiocarbon and luminescence dating techniques to constrain the timing of dune stabilization and reworking events
4) Combine the mapping interpretation with geochronological data to constrain the history and nature of dune reworking, and link to possible (climatic or other) causes via data mining of existing North Atlantic/Arctic past climate data