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TitleQuantitative mapping of eskers
AuthorBroscoe, D; Cummings, D I; Russell, H A JORCID logo; Sharpe, D R
Source42nd Annual Yellowknife Geoscience Forum, abstracts; by Irwin, D; Normandeau, P; Northwest Territories Geoscience Office, Yellowknife Geoscience Forum Abstracts Volume vol. 2014, 2014 p. 85 Open Access logo Open Access
Alt SeriesNatural Resources Canada, Contribution Series 20190328
PublisherNorthwest Territories Geoscience Office (Yellowknife, Canada)
Meeting42nd Annual Yellowknife Geoscience Forum; Yellowknife, NT; CA; November 25-27, 2014
Mediapaper; on-line; digital
File formatpdf
Subjectssurficial geology/geomorphology; geophysics; economic geology; Science and Technology; Nature and Environment; glacial landforms; eskers; remote sensing; satellite imagery; spectral analyses; software; mineral exploration; exploration methods; Canadian Digital Elevation Data (CDED); methodology; geological mapping techniques; digital elevation data; Landsat; SPOT; geographic information systems; ArcGIS; digital elevation models (DEM); classification; automation; Phanerozoic; Cenozoic; Quaternary
ProgramGEM2: Geo-mapping for Energy and Minerals, Hudson/Ungava Project Management
Released2014 11 01
AbstractEskers have commonly been mapped manually from aerial photograph as lines (esker ridges) and polygons (sand and gravel). This process is qualitative. To date no method has been deployed that could automatically extract esker extents and quantify esker volumes. A methodology is presented for the quantification of eskers that uses Canadian Digital Elevation Data (CDED), spectral remotely sensed imagery (e.g. LandSat, Spot), and legacy esker line work from Geological Survey of Canada publications. Using ArcGIS and an esker detection module (EDM) coded in Python, the CDED data are smoothed using user defined filter windows. A difference surface is produced that emphasizes ridge areas and is used to create polygons. The legacy esker line work is used as a training dataset to extract ridge areas within a user defined buffer. Results have been tested against the input training data and a local dataset generated manually from aerial photograph interpretation. Depending upon terrain characteristics the success of the data extraction ranges from 65 to 81% for the esker line work and 35 to 72% for the more limited aerial photograph interpretation. The variable success reflects esker size related to both relief and width in the CDED data.
Ongoing development of this methodology focused on enhanced delineation of low-relief areas of the esker not captured by the digital elevation model (DEM) analysis through incorporation of spectral imagery. A multiclass (80-100) iso-cluster unsupervised classification of SPOT MSS data was completed to characterize the landscape. The iso-cluster classification was then overlain on the esker polygons. The most dominant classes in terms of area are identified and the user can specify the number of classes to be chosen. The originally topographically defined polygons are then merged with the selected intersecting spectral classification.
The ability to extract an esker signature by a semi-automated methodology that generates a dataset for quantitative analysis provides an opportunity to improve understanding of the geometry and sediment landform relationship of eskers. This data is suitable for improving the understanding of heavy mineral sampling programs of eskers and hence could contribute to improved data analysis in mineral exploration programs. The quantification of esker volume could also aid in assessing the aggregate resource potential of eskers.
Summary(Plain Language Summary, not published)
Documents a semiautomated method for mapping esker extent using legacy geological data, Digital Elevation Models (DEM) and Remotely Sensed spectral data from the SPOT Geobase archive. Method is scripted in Python and is run in ArcInfo Geographic Information System (GIS) package.

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