Multi-scale curvature for automated identification of glaciated mountain landscapes

- Morphometric analysis was carried out to automatically identify glaciated valleys
- U- and V-shaped valley cross sections were distinguished using multi-scale curvature
- Difference of Minimum Curvature was introduced to describe morphological differences
- The automated approach was tested in three mountain ranges in the western US
- Results show Difference of Minimum Curvature as a good predictor of glacial imprint

Erosion by glacial and fluvial processes shapes mountain landscapes in a long-recognized and characteristic way. Upland valleys incised by fluvial processes typically have a V-shaped cross-section with uniform and moderately steep slopes, whereas glacial valleys tend to have a U-shaped profile with a changing slope gradient. We present a novel regional approach to automatically differentiate between fluvial and glacial mountain landscapes based on the relation of multi-scale curvature and drainage area. Sample catchments are delineated and multiple moving window sizes are used to calculate per-cell curvature over a variety of scales ranging from the vicinity of the flow path at the valley bottom to catchment sections fully including valley sides. Single-scale curvature can take similar values for glaciated and non-glaciated catchments but a comparison of multi-scale curvature leads to different results according to the typical cross-sectional shapes. To adapt these differences for automated classification of mountain landscapes into areas with V- and U-shaped valleys, curvature values are correlated with drainage area and a new and simple morphometric parameter, the Difference of Minimum Curvature (DMC), is developed. At three study sites in the western United States the DMC thresholds determined from catchment analysis are used to automatically identify 5 × 5 km quadrats of glaciated and non-glaciated landscapes and the distinctions are validated by field-based geological and geomorphological maps. Our results demonstrate that DMC is a good predictor of glacial imprint, allowing automated delineation of glacially and fluvially incised mountain landscapes.