Hyperspectral data analysis is commonly carried out during the reconnaissance phase of an exploration program in conjunction with field surveys and exploration geophysics. GER hyperspectral data analysis is performed after lower-resolution multispectral satellite Landsat imagery has been processed and analyzed in house to map regional structure including lineament, fault and fracture trends, regional lithologic relationships and target anomalous concentrations of hydroxyl-sulfate and/or ferric iron-bearing rocks which may indicate the presence of hydrothermal alteration and related supergene mineral enrichment. Hyperspectral data analysis is applied to target areas identified by field and Landsat satellite reconnaissance to produce detailed maps of surface mineral distribution and local structural features invisible on the satellite imagery. Mineral maps derived from the hyperspectral data is used to guide subsequent geochemical field sampling programs, and to provide digital base map upon which the field sample locations can be plotted by Geographic Information System (GIS).

Minerals which can be identified and differentiated through GER hyperspectral image analysis include: kaolinite, montmorillonite, sericite, alunite, calcite, dolomite, gypsum, jarosite, goethite, hematite, buddingtonite and silica.