Abstract
Abstract. In the field of geomorphological mapping, the demand for automated delineation of bedforms is growing due to the increasing availability of Digital Elevation Models (DEMs) in small to medium resolutions. This automated technique is not commonly applied in submarine DEMs, where bedform morphology is often subdued due to erosion and part-burial. Here we analyse drumlins in both terrestrial and submarine environments to compare and contrast the set of rules needed for their automated delineation from 3D topographic data. An existing set of rules for automated extraction to delineate the perimeter of terrestrial drumlins was developed in 2011 using object-oriented classification tools, available through eCognition Developer (V.8.7.2). This partly supervised method is evaluated here and subsequently adjusted to be applied to extract drumlins from a submarine DEM with a higher resolution. Several adjustments were needed due to the morphologic differences between the terrestrial and the submarine drumlins. For submarine drumlins, a focus on variation in elevation in the tool is needed, as part-burial and overprinting by other bedforms is common in submarine settings. A Canny Edge Detector filter was used instead of the Sobel Edge detection filter, whilst slope gradient and direction played a larger role in the set of rules. Visual and quantitative comparison with manually delineated drumlin perimeters confirms the success of this revised automated extraction method in both terrestrial and submarine environments. The flexibility and precision of this method thus allow for the future development of object-oriented classification tools to delineate a wide range of bedforms from large-scale DEMs collected from all environments.
Highlights
In the last decade, large geomorphological datasets have become increasingly available to the wider public
The bedforms preserved in these terrestrial and submarine Digital Elevation Models (DEMs) represent the region’s glacial, hydrological and sedimentary history. Drumlins are one such type of glacial bedform which are typically described as streamlined oval-shaped hills with a long axis parallel to the orientation of ice flow and with an upice face that is generally steeper than the down-ice face (Stokes et al, 2011)
The process starts with an onscreen digitization of drumlin boundaries of the terrestrial drumlins on Digital Raster Graphics (DRG) of the topographic maps in eCognition Developer
Summary
Large geomorphological datasets have become increasingly available to the wider public. A good agreement between the two methods showed that the automated method is reliable (Saha et al, 2011) This automated extraction is partly supervised: an initial set of rules is defined to recognize the object (bedform) of interest. The aim now is to assess whether the method by Saha et al (2011) is both robust and flexible enough to be adjusted and applied to a submarine DEM with a higher resolution of 10 m and with the challenges of a more complex environment, including the drumlins’ (1) more subtle shape, (2) overprinting by other types of bedforms and (3) variable orientation within the field. If the evaluated tool successfully extracts these submarine drumlins, we demonstrate flexibility in this partly supervised, yet automated method to delineate a wider variety of both glacial and sedimentary bedforms. A reliable tool to automatically extract geometric information from any object could assist the mapping of, for instance, private gardens in urban areas (Mathieu et al, 2007), neighborhoods with low and high socio-economic status (Stow et al, 2007), soil- and bedrock-dominated landslides (Martin and Franklin, 2005), and urban roof area (Aldred et al, 2011; Saha et al, 2016)
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