EVALUATION OF DETAILED AND AUTOMATED METHODOLOGIES FOR HYDROTHERMAL ALTERATION MAPPING FROM SPACE: APPLICATION TO GEOENVIRONMENTAL AND MINERAL RESOURCE ASSESSMENTS AT THE SCALE OF WATERSHEDS AND PERMISSIVE TRACTS

Hydrothermal alteration has been demonstrated to have a direct impact on acidity, metal content, and faunal populations in surface water. Mining activity may exacerbate such baseline conditions which must be taken into account when designing remediation programs. Alteration mapping is becoming more routine in geoenvironmental assessment programs as one of the key inputs for accurate prediction of surface water quality at both watershed and regional scales.

As alteration commonly accompanies mineralization in many types of ore deposits, it is routinely identified, characterized, and mapped as a part of mineral exploration programs. Such mapping can aid in the delineation of favorable areas within permissive tracts for a deposit type, and be useful in establishing vectors towards mineralization.

Spectral remote sensing using data collected by airborne and spaceborne sensors have been used for decades to map alteration minerals, and is an efficient way to perform such mapping at local and regional scales. Using test areas in alpine/temperate and arid/semi-arid climates, field-verified mineral maps generated by analysis of high spectral- and spatial-resolution NASA AVIRIS airborne data are compared to those generated from detailed spectroscopic analysis of lower spectral- and spatial-resolution ASTER satellite data. Maps of hypogene alteration types were developed from the ASTER-derived maps using Boolean combinations of identified minerals and mineral assemblages. These types include advanced argillic, argillic ± ferric iron, phyllic, pyritic, propylitic ± sericite ± ferric iron, regional propylitic, and hydrous silica. These alteration types can be classified as to acid producing and neutralizing potential for use in GIS-based, multi-variable, predictive modeling of surface-water quality.

A new technique for the automated mapping of mineral groups using ASTER data also has been developed and results are compared with the detailed maps. This technique can produce GIS-ready maps of advanced argillic-kandite, argillic-sericite-smectite, carbonate-propylitic, hydrous silica-jarosite-sericite, and ferric iron mineral groups, as well as green vegetation, in under five minutes per scene. Such maps are ideal for regional mineral-environmental and mineral resource assessments.