Automated drumlin shape and volume estimation using high resolution LiDAR imagery (Curvature Based Relief Separation): A test from the Wadena Drumlin Field, Minnesota

- We develop a new volume estimation method adapted from visualisation techniques.
- The method is fully objective and can be applied to any study area.
- Drumlins with unconventional morphology are captured where manual inspection failed.
- Use of high resolution LiDAR data allows for superior level of analysis.

Resolving the origin(s) of drumlins and related megaridges in areas of megascale glacial lineations (MSGL) left by paleo-ice sheets is critical to understanding how ancient ice sheets interacted with their sediment beds. MSGL is now linked with fast-flowing ice streams but there is a broad range of erosional and depositional models. Further progress is reliant on constraining fluxes of subglacial sediment at the ice sheet base which in turn is dependent on morphological data such as landform shape and elongation and most importantly landform volume. Past practice in determining shape has employed a broad range of geomorphological methods from strictly visualisation techniques to more complex semi-automated and automated drumlin extraction methods. This paper reviews and builds on currently available visualisation, semi-automated and automated extraction methods and presents a new, Curvature Based Relief Separation (CBRS) technique; for drumlin mapping. This uses curvature analysis to generate a base level from which topography can be normalized and drumlin volume can be derived. This methodology is tested using a high resolution (3 m) LiDAR elevation dataset from the Wadena Drumlin Field, Minnesota, USA, which was constructed by the Wadena Lobe of the Laurentide Ice Sheet ca. 20,000 years ago and which as a whole contains ~ 2000 drumlins across an area of ~ 7500 km2. This analysis demonstrates that CBRS provides an objective and robust procedure for automated drumlin extraction. There is strong agreement with manually selected landforms but the method is also capable of resolving features that were not detectable manually thereby considerably expanding the known population of streamlined landforms. CBRS provides an effective automatic method for visualisation of large areas of the streamlined beds of former ice sheets and for modelling sediment fluxes below ice sheets.