Integration of Multi-Source Data in Mineral Exploration |
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Abstract | This paper describes several multivariate statistical analysis applications of geochemical, geophysical and spectral variables in mineral exploration. Mahalanobis' distance is described in some detail and based on four multi-source variables this measure is applied to produce a map that gives an expression of the statistical proximity of each point in the map to a mineralized area. The four multi-source variables chosen from a much larger set of variables have all been subject to extensive data processing: the geochemical variable is the noise MAF (minimum-maximum autocorrelation factor) of eleven kriging interpolated stream sediment variables; the geophysical variables are kriged aeromagnetic data iteratively moving average corrected to minimize the flight line striping and kriged Bouguer gravity anomaly data corrected for a quadratic trend; and the spectral variable is the density of automatically generated linear features based on Landsat TM data. The results indicate among other things a not previously recognized subsurface continuation of an already mapped lineament. |
Type | Conference paper [With referee] |
Conference | Eighth Thematic Conference on Geologic Remote Sensing |
Year | 1991 Vol. II pp. 1053-1066 |
Publisher | Environmental Research Institute of Michigan (ERIM) |
Address | Denver, Colorado, USA |
Electronic version(s) | [pdf] |
BibTeX data | [bibtex] |
IMM Group(s) | Image Analysis & Computer Graphics |