Abstract
Cluster analysis algorithms enable the rapid and objective integration of multi-method data bases with unknown parameter relationship between the individual data types present in the data base. We are employing the fuzzy Gustafson-Kessel (GK) cluster algorithm to integrate a data base comprising 2D information from Landsat satellite imagery, airborne radiometric and regional geochemical data acquired over a survey area in the Northern Cape Province of South Africa. We are combining the structural information provided by satellite and airborne radiometric data with regional geochemical soil sample data to obtain an objective 2D classified zoned map reflecting sub-surface lithology. Ground truth control supports to ascribe the various clusters to lithology and generate mineral exploration target areas.
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