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TitleApplication of GIS processing techniques for producing mineral prospectivity maps - a case study: mesothermal Au in the Swayze Greenstone Belt, Ontario, Canada
AuthorHarris, J R; Wilkinson, L; Heather, K; Fumerton, S; Bernier, M A; Ayer, J; Dahn, R
SourceNatural Resources Research vol. 10, no. 2, 2001 p. 91-124, https://doi.org/10.1023/A:1011548709573
LinksAbstract - Résumé
Year2001
Alt SeriesGeological Survey of Canada, Contribution Series 2000209
PublisherSpringer Nature
Documentserial
Lang.English
Mediapaper; on-line; digital
File formatpdf
ProvinceOntario
NTS41O/09; 41O/10; 41O/15; 41O/16
Lat/Long WENS -83.0000 -82.0000 48.0000 47.5000
Subjectsigneous and metamorphic petrology; metallic minerals; remote sensing; greenstone belts; LANDSAT; gold; mineralization; mineral exploration; Archean; epithermal deposits
Illustrationstables; geological sketch maps; schematic diagrams; geoscientific sketch maps
ProgramNorthern Ontario Development Agreement (NODA)
AbstractA Geographic Information System (GIS) is used to prepare and process digital geoscience data in a variety of ways for producing gold prospectivity maps of the Swayze greenstone belt, Ontario, Canada. Data used to produce these maps include geologic, geochemical, geophysical, and remotely sensed (Landsat). A number of modeling methods are used and are grouped into data-driven (weights of evidence, logistic regression) and knowledge-driven (index and Boolean overlay) methods. The weights of evidence (WofE) technique compares the spatial association of known gold prospects with various indicators (evidence maps) of gold mineralization, to derive a set of weights used to produce the final gold prospectivity map. Logistic regression derives statistical information from evidence maps over each known gold prospect and the coefficients derived from regression analysis are used to weight each evidence map. The gold prospectivity map produced from the index overlay process uses a weighting scheme that is derived from input by the geologist, whereas the Boolean method uses equally weighted binary evidence maps.
The resultant gold prospectivity maps are somewhat different in this study as the data comprising the evidence maps were processed purposely differently for each modeling method. Several areas of high gold potential, some of which are coincident with known gold prospects, are evident on the gold prospectivity maps produced using all modeling methods. The majority of these occur in mafic rocks within high strain zones, which is typical of many Archean greenstone belts.
GEOSCAN ID211879