Application of the ASTER data and multivariate analysis techniques to forecasting porphyry copper mineralization within territories under significant sedimentary and vegetation cover: The case of the Kraichikovo copper occurrence, Middle Urals
DOI: 10.47765/0869-5997-2026-10006
Keywords:
ASTER, remote sensing, principal component analysis (PCA), porphyry copper mineralization, hydrothermal alterations, Middle Urals, Kraichikovo ore occurrence, spectral indices, lineament analysis.Abstract
Efficiency of Terra/ASTER satellite multispectral data as applied to forecast of porphyry copper mineralization under conditions of the thick sedimentary and dense vegetation cover was assessed on an example of the Kraichikovo occurrence (Middle Urals). Direct application of the mineralogical indices yielded only the patterns controlled by landscape and anthropogenic factors, which was consistent with the global experience. At the same time, it was demonstrated that the interfering factors were effectively suppressed using the principal component analysis (PCA) technique. The key components identified were PC4 (marking fault zones and bedrock exposures) and PC6 (representing a direct indicator of Al–OH containing metasomatic alterations). The ore-controlling structure was detailed by means of the lineament analysis. A map of ranked prospectivity with new target areas was synthesized based on integrating of the PC6 and PC4. Reasons for the success of the method (extraction of weak, statistically independent spectral signals) and its limitations (anthropogenic noise) are discussed. The results of the research confirm practicability of the adaptation of the PCA-based ASTER interpretation techniques for early-phase exploration at overcovered territories within the temperate zone.
