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TitleMapping surficial materials south of Wager Bay area (Nunavut) using RADARSAT-2 C-HH and C-HV, Landsat-8 OLI, DEM and slope data
AuthorByatt, J; La Rocque, A; Leblon, B; Harris, J; McMartin, IORCID logo
SourceInternational Journal of Earth and Environmental Sciences vol. 4, 164, 2019 p. 1-16, Open
Access logo Open Access
LinksOnline - En ligne
Alt SeriesNatural Resources Canada, Contribution Series 20170246
PublisherGraphy Publications
Mediaon-line; digital
File formatpdf (Adobe® Reader®)
NTS46D; 46E; 55P; 56A; 56H
AreaWager Bay; Ukkusiksalik National Park
Lat/Long WENS -90.0000 -87.0000 65.8333 63.7500
Subjectssurficial geology/geomorphology; geophysics; mapping techniques; remote sensing; satellite imagery; alluvium; boulders; sands; gravels; organic deposits; silts; clays; marine sediments; glacial deposits; tills; vegetation; Classification; alluvial floodplain sediments; alluvial terraced sediments; marine offshore sediments; Phanerozoic; Cenozoic; Quaternary
Illustrationslocation maps; geoscientific sketch maps; tables; flow charts; bar graphs; plots; photographs
ProgramGEM2: Geo-mapping for Energy and Minerals Rae Province, Tehery-Wager Bay
Released2019 03 29
AbstractFor an area south of Wager Bay, Nunavut (NTS map sheets 046D, E, 055P, 056A, H), a map detailing 22 surface material classes was produced using a non-parametric classifier, Random Forests, applied to a combination of RADARSAT-2 C-band dual- polarized (horizontal transmitted and horizontal received (HH) and horizontal transmitted and vertical received (HV)) and Landsat-8 OLI images with a digital elevation model and slope data. We show that the addition of RADARSAT-2 CHH and C-HV images to the optical Landsat-8 OLI image in the classification process increases the overall classification accuracy from 96.7% to 99.3%. Similarly, the accuracy determined by comparing the resulting maps with georeferenced field data (i.e., mapping accuracy) increases from 72.1% to 78.0% when RADARSAT-2 C-HH and C-HV images are added to the classification. The material classes with the highest mapping accuracies were flooded alluvium and boulders, both with 100%. The class with the lowest mapping accuracy was thin sand and gravel over bedrock (11.1%), commonly confused with sand and gravel with vegetation and bedrock. Adding RADARSAT-2 data in the classification increases also the mapping accuracy that was established by comparing to georeferenced point observations.
Summary(Plain Language Summary, not published)
This paper reports on a surficial earth materials mapping research project completed south of Wager Bay along the northwestern shores of Hudson Bay, mainland Nunavut, as part of the surficial geology component of the GEM-2 Tehery-Wager Activity within the Rae Project area. A classification map with 22 surficial materials classes was produced using a combination of remote satellite data, a digital elevation model and derived slope data, and validated with georeferenced sites including field observations. The findings will support informed decision making for resource exploration and development, and for land use management.

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