Title | LiDAR-based semi-automated mapping of drumlins and mega-scale glacial lineations of the Green Bay Lobe, Wisconsin, USA: ice sheet beds as glaciotribological systems |
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Author | Eyles, N; Bukhari, S; Sookhan, S; Ruscica, P; Paulen, R C |
Source | Earth Surface Processes and Landforms 2022 p. 1-65, https://doi.org/10.1002/esp.5486 Open Access |
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Year | 2022 |
Alt Series | Natural Resources Canada, Contribution Series 20210662 |
Publisher | John Wiley & Sons on behalf of the British Society for Geomorphology |
Document | serial |
Lang. | English |
Media | paper; on-line; digital |
File format | pdf |
Area | Wisconsin; United States of America |
Lat/Long WENS | -92.5308 -79.1628 49.6225 39.2806 |
Subjects | Science and Technology; Nature and Environment; Green Bay Lobe; machine learning |
Illustrations | location maps; diagrams; cross-plots |
Program | GEM-GeoNorth: Geo-mapping for Energy and Minerals GEM Program Coordination |
Released | 2022 09 15 |
Abstract | A machine learning methodology for processing and visualizing high resolution LiDAR digital data is used to map drumlins and mega-scale glacial lineations (MSGLs) on the bed of the Late Wisconsin Green
Bay Lobe in Wisconsin, USA which exhibited surge-like behaviour during deglaciation. Previous work has shown that streamlined bedforms are the product of erosional streamlining of pre-existing sediment. Analysis of bedform height and elongation ratio
using Curvature-based Relief Separation (CBRS) and K-means clustering of 32,003 bedforms reveals a continuum of six morphotypes ranging from drumlins, through 'channeled' more elongated multi-crested drumlins, to MSGLs. Further statistical analysis
shows morphotypes cluster into six types of streamlined surfaces (S1-S6) recording progressive elimination of an antecedent overridden topography to produce a smoother bed. Initial, relatively high relief drumlinized surfaces (S1, S2) occur around
the slower flowing lateral flanks of the lobe where a pre-existing hummocky morainal topography was only partially modified by subglacial erosion. More streamlined surfaces (S3, S4) dominated by multi-crested more elongate drumlins of reduced relief
amplitude, are transitional to flow sets of MSGL-dominated surfaces (S5, S6) indicative of much faster flowing ice streaming along the lobe's axis. Estimates of basal drag based on roughness calculations for each surface type, identify a 61%
reduction in frictional retardation from poorly-streamlined surfaces S1 and S2 to MSGL-dominated surfaces S5 and S6 with a step-like reduction between drumlins and channeled drumlins (S3, S4) possibly recording the rapid onset of fast flow.
Subglacial streamlining is argued to be accomplished by a thin (< 1 m) 'third layer' of deforming subglacial debris between ice and its bed which functioned as an erodent layer. A thin (< 3 m) till cap, formed by aggradation of deforming debris,
rests unconformably on heterogenous core sediments. Streamlined subglacial surfaces are comparable to the 'functional' surfaces resulting from erosion by a 'third layer' of wear debris in engineering tribological systems, and also, by gouge on
faults. Pleistocene ice sheets expanded over pre-existing landsystems pointing to the broader relevance of the methodology and findings reported here. |
Summary | (Plain Language Summary, not published) Processing and visualization of high resolution LiDAR digital topographic data using a newly developed machine learning methodology, is used to map
drumlins and megascale glacial lineations. This records progressive erosion of pre-existing proglacial sediments as the ice sheet sculpts its its bed to reduce frictional drag over time, transforming drumlins to mega scale glacial
lineations. |
GEOSCAN ID | 329631 |
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