The purpose of this report is to summarize the progress in use of digital image analysis techniques in developing a conceptual model for assessing porphyry copper mineral potential. The study area consists of approximately the southern one-half of the 1? by 3? Nabesna quadrangle in east-central Alaska. The digital geologic data base consists of data compiled under the Alaskan Mineral Resource Assessment Program (AMRAP) as well as digital elevation data and Landsat spectral reflectance data from the Multispectral Scanner System. The digital data base used to develop and implement a conceptual model for porphyry-type copper mineralization consisted of 16 original data types and 18 derived data sets formatted in a grid-cell (raster) structure and registered to a map base in the Universal Transverse Mercator (UTM) projection. Minimum curvature and inverse distance squared interpolation techniques were used to generate continuous surfaces from sets of irregularly spaced data points. Processing requirements included: (1) merging or overlaying of data sets, (2) display and color coding of maps and images, (3) univariate and multivariate statistical analyses, and (4) compound overlaying operations. Data sets were merged and processed to create stereoscopic displays of continuous surfaces. The ratio of several data sets were calculated to evaluate relative variations and to enhance the display of surface alteration (gossans). Factor analysis and principal components analysis techniques were used to determine complex relationships and correlations between data sets. The resultant model consists of 10 parameters that identify three areas most likely to contain porphyry copper mineralization; two of these areas are known occurrences of mineralization and the third is not well known. Field studies confirmed that the three areas identified by the model have significant copper potential.
Additional publication details
USGS Numbered Series
Digital data base application to porphyry copper mineralization in Alaska; case study summary
U.S. Geological Survey
Earth Resources Observation and Science (EROS) Center