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TitleDeveloping and testing surficial materials classification using remote predictive mapping methods: preliminary results near Repulse Bay, Nunavut
AuthorWityk, U; Ross, MORCID logo; McMartin, IORCID logo; Campbell, J; Grunsky, E; Harris, J
SourceGeological Association of Canada-Mineralogical Association of Canada, Joint Annual Meeting, Programs with Abstracts vol. 34, 2011 p. 235
LinksOnline - En ligne
Alt SeriesEarth Sciences Sector, Contribution Series 20100420
Meeting2011 GAC-MAC-SEG-SGA Joint Annual Meeting; Ottawa; CA; May 25-27, 2011
Mediapaper; CD-ROM
AreaRepulse Bay
Lat/Long WENS-88.0000 -86.0000 67.0000 66.0000
Subjectssurficial geology/geomorphology; economic geology; glacial deposits; mapping techniques; computer mapping; tills; sands; silts; clays; gravels; exploration methods; exploration; remote sensing; Cenozoic; Quaternary
ProgramGEM: Geo-mapping for Energy and Minerals Diamonds
Released2011 01 01
AbstractGeological mapping of Northern regions in Canada represents an essential step in providing key knowledge for resource development and economic prosperity of northerners. The Repulse Bay study area lies within one of the most active diamond exploration areas of the Western Churchill Geological Province. However, its surficial geology has never been mapped at an effective scale. Currently, surficial geology maps available for this region are at the coarse scale of 1:1,000,000, therefore hindering the potential for exploration programs by the diamond industry.
To direct and focus field mapping activities, and help in the surficial materials and glacial landform interpretation, first order predictive surficial materials maps are being created at a 1:100 000 scale for NTS 46M west and 46L of the Repulse Bay area using Remote Predictive Mapping (RPM) techniques. RPM is a process by which various geoscience data are compiled and interpreted to develop the best representation of what is truly on the surface. Preliminary fieldwork was conducted in the summer of 2010 to gather field observations and determine general classification of surficial materials. This fieldwork formed the basis of training area selection applied to the predictive mapping process,
producing categories of: thick till, thin till, bedrock, boulderfield, marine silty sands, marine silts and clays, coarse sands and gravels, morainic material and organic deposits. Using various software and methods to create predictive maps (i.e. ICM (now referred to as Iterative Classification Method) interface in ENVI), a multi-data approach is being taken, utilizing several types of imagery. The different imagery types are used both individually and in combination to determine the most optimal data (or data combination) to refine the materials classification and produce the best possible accuracy for the study area. LANDSAT 7 TM and finer resolution SPOT 4 and SPOT 5 data are used, along with MERIS, and a Digital Elevation Model (DEM). The imagery and data interpretation help explore the advantages of using different spatial and spectral resolutions, as the resolution across the data types are not uniform across the study area. Together with different types of imagery and a robust collection of field data, separate types of classification, including supervised and unsupervised, are applied and compared. This methodology will help improve the RPM process and results, and further predictive mapping successes in arctic terrain. Along with advancements in the RPM process and methodology, final maps will help guide future fieldwork and diamond exploration efforts in the north.

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