| Title | Geo-mapping Frontiers: predictive geology map of the Ennadai region, Nunavut |
| Download | Downloads |
| |
| Licence | Please note the adoption of the Open Government Licence - Canada
supersedes any previous licences. |
| Author | Hayward, N ;
Harris, J R; Grunsky, E; Beauchemin, M; Jefferson, C; Peterson, T |
| Source | Geological Survey of Canada, Open File 7485, 2013, 21 pages, https://doi.org/10.4095/293261  Open Access |
| Links | Geo-mapping
Frontiers
|
| Links | Les frontières de la géocartographie
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| Year | 2013 |
| Publisher | Natural Resources Canada |
| Document | open file |
| Lang. | English |
| Media | on-line; digital |
| File format | readme
|
| File format | pdf; shp; mxd; xml; rtf |
| Province | Nunavut |
| NTS | 55D; 65A; 65B; 65C; 65F; 65G; 65H; 65I; 65J; 65K; 65O/01; 65P |
| Area | Ennadai |
| Lat/Long WENS | -102.0000 -94.0000 63.7500 60.0000 |
| Subjects | geochemistry; geophysics; geochronology; stratigraphy; structural geology; economic geology; modelling; geophysical surveys; geochemical surveys; LANDSAT; lake sediment geochemistry; gravity surveys;
magnetic surveys; mineral occurrences; data collections; gamma-ray surveying; geographic information system application |
| Illustrations | location maps; tables |
| Program | GEM: Geo-mapping for Energy and Minerals Geomapping for Energy & Minerals (GEM) - Geo-mapping Frontiers |
| Released | 2013 12 04 |
| Abstract | In the final phase of the Geomapping for Energy and Minerals (GEM) Program, a project entitled Geo-mapping Frontiers (
http://www.nrcan.gc.ca/earth-sciences/about/current-program/geomapping/minerals/11975 ) was initiated to improve geoscience knowledge in the least understood parts of Canada's north. An inventory was first conducted to evaluate the state of knowledge
in parts of Nunavut, NWT and Yukon shown as having insufficient knowledge to support decision-making. Criteria included: 1) mapped at 250K scale or coarser; 2) mapped prior to aeromagnetic coverage; 3) lacking modern U-Pb age information on major
units; 4) lacking Nd-Sm model age data; 5) lacking thermochronological data; 6) lacking a stratigraphic framework for supracrustal rocks; 7) lacking subdivision of granitic rocks; and 8) mineral potential unconfirmed. Eleven areas identified during a
preliminary scan were discussed with territorial geological surveys in the spirit of the Intergovernmental Geoscience Accord. In light of the consultation process, four geographic areas were prioritized for investigation from a minerals perspective
(Chantrey, Ennadai, South Rae and Tehery transects), and two topics were selected for Energy research.
The project is consolidating and improving existing information (data mining, compilation and remote predictive mapping), acquiring new data
(e.g. geophysical, geochemical surveys), testing emerging models through targeted field work, contributing to completion of the Tri-territorial database, and advancing planning with regard to future work. Activities are also aimed at stimulating
direct industry interest through timely delivery of maps, reports, compilations and datasets.
The data in this Open File include data compilation and re-interpretation of the geology using Remote Predictive Mapping (RPM) techniques for the
Ennadai region shown in Figure 1. This region was selected as one of the areas requiring improved mapping as part of the GEM Geo-Frontiers mapping project. |
| Summary | (Plain Language Summary, not published)
This Open File provides the raw geoscience data used to make predictive geological maps of the Ennadai area within the Churchill Province. Predictive
lithological and structural maps using the IPY legacy geological map (Harrison et al., 2011) as a base were derived from visual interpretation of enhanced magnetic, gamma ray spectrometer, LANDSAT, and legacy geological data. In addition, predictive
maps of the southern portion of the study have been produced using multivariate statistical measures applied to lake sediment geochemical data. Predictive maps of outcrop and rocks high in ferric iron (possible gossans) have also been produced using
image processing techniques applied to LANDSAT 7 satellite data. |
| GEOSCAN ID | 293261 |
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