Investigating Sand Dune Location, Orientation and Geomorphometry Through GEOBIA-Based Mapping: A Case Study in Northern Sweden

• Main Author: Stammler, Melanie
• Format: Bachelor Thesis
• Language: English
• Published: Uppsala universitet, Institutionen för geovetenskaper 2020
• Subjects: sand dunes; geomorphological mapping; object-based image analysis; landscape development; sanddyner; geomorfologisk kartläggning; geografisk objektbaserad bildanalys; landskapsutveckling; Physical Geography; Naturgeografi; Arctic; Climate change; Norra Sverige; Northern Sweden
• Online Access: http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-424975

Climate change has repeatedly been framed as the defining issue of the Anthropocene and with the Arctic changing at unpreceded speed need is high for a profound understanding of the Northern Swedish landscape. Northern Swedish aeolian sand dunes have been impacted by climatic changes throughout time. Their location, orientation and geomorphometry can therefore be used to explore past wind patterns and dune activity. By systematically and spatially mapping the dunes, patterns in location can be illustrated, dune orientations investigated, the dunes’ geomorphometry characterised and sediment sources determined. Based on this knowledge, insight in landscape development along with a better understanding of long-term landscape (in)stability in Northern Sweden can be gained. This M. Sc. thesis sets out to summarize useful concepts to understand the formation of Northern Swedish aeolian sand dunes and to derive its implications for understanding landscape development. Based thereon, it deduces the strong need to systematically and spatially analyse aeolian sand dunes in Northern Sweden. The use of geographic object-based image analysis (GEOBIA) allows for the detection of potential dune locations over a large area and provides defined and reproducible mapping boundaries. Polygons are created by segmenting a residual-relief separated digital elevation model (DEM) as well as slope and curvature data. The multi-resolution segmentation provides best results with a scale parameter of 15 and a homogeneity criterion of 0.1 for the shape criterion, as well as 0.5 for the compactness criterion. A rule-based classification with empirically derived parameters accepts on average 2.5 % of the segmented image objects as potential dune sites. Subsequent expert-decision confirms on average 25 % of the classified image objects as identified dune locations. The rule-based classification provides best results when targeting a smaller area as this allows for less variability within the dune characteristics. The investigation of ...