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TitleQuantitative mapping of eskers using DEM and multispectral data
AuthorBroscoe, D; Russell, H A JORCID logo
SourceGeological Society of America, Abstracts With Programs vol. 46, no. 6, 2014 p. 522
LinksOnline - En ligne
Alt SeriesEarth Sciences Sector, Contribution Series 20140200
PublisherGeological Society of America
MeetingGeological Society of America, Annual Meeting 2014; Vancouver, BC; CA; October 19-22, 2014
Mediapaper; digital
File formatpdf
Subjectssurficial geology/geomorphology; eskers; computer mapping; mapping techniques; remote sensing; topography; glacial landforms; LANDSAT; LANDSAT imagery
ProgramGroundwater Geoscience Aquifer Assessment & support to mapping
AbstractEskers have commonly been mapped and symbolized manually from aerial photographic interpretation as either lines (ridges) and polygons (sand and gravel). To-date no method has been deployed that could automatically extract esker extents and quantify the esker volume. 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. EDM results have been tested against the input training data and a local data set generated manually from aerial photographic interpretation. Depending upon terrain characteristics the success of the data extraction ranges from 65 to 81 % against the esker line work and 35 to 72 % against the more limited aerial photographic interpretation. The variable success reflects esker size related to both relief and width in the CDED data. Ongoing development of this methodology focuses on enhanced delineation of low-relief areas of the esker not captured by the DEM analysis through incorporation of spectral imagery. A multiclass (80-90) iso-cluster unsupervised classification of SPOT MSS data was completed to characterize the landscape. The isocluster classification is 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.
Summary(Plain Language Summary, not published)
Documents an automated approach using training data to the quantification of eskers.

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