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TitleLiDAR-based semi-automated mapping of drumlins and mega-scale glacial lineations of the Green Bay Lobe, Wisconsin, USA: ice sheet beds as glaciotribological systems
AuthorEyles, N; Bukhari, S; Sookhan, S; Ruscica, P; Paulen, R CORCID logo
SourceEarth Surface Processes and Landforms 2022 p. 1-65, Open Access logo Open Access
Alt SeriesNatural Resources Canada, Contribution Series 20210662
PublisherJohn Wiley & Sons on behalf of the British Society for Geomorphology
Mediapaper; on-line; digital
File formatpdf
AreaWisconsin; United States of America
Lat/Long WENS -92.5308 -79.1628 49.6225 39.2806
SubjectsScience and Technology; Nature and Environment; Green Bay Lobe; machine learning
Illustrationslocation maps; diagrams; cross-plots
ProgramGEM-GeoNorth: Geo-mapping for Energy and Minerals GEM Program Coordination
Released2022 09 15
AbstractA 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.

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