Mapping of anomalies in continuous and discrete fields of stream sediment geochemical landscapes

Abstract

ABSTRACT In this study, continuous field models of geochemical landscapes were obtained by interpolating stream sediment geochemical data while discrete field models of geochemical landscapes were obtained by attributing stream sediment geochemical data to their sample catchment basins. This study aimed to: (1) compare and contrast anomaly maps derived from continuous and discrete field models of stream sediment geochemical landscapes; and (2) determine which empirical frequency distributions – those of original point data or those of pixels values in models of stream sediment geochemical landscapes – are more useful in mapping of anomalies in such geochemical landscapes. Anomalies were mapped by using the mean+2 SDEV (standard deviation), median+2 MAD (median absolute deviation) and concentration–area (C–A) fractal methods of identifying threshold values in a geochemical data set. The results of the study in the Aroroy gold district (Philippines) highlight the following findings. In mapping of anomalies in either continuous or discrete field models of stream sediment geochemical landscapes, the C–A fractal method performs best, followed by the median+2 MAD method and then by the mean+2 SDEV method. Anomalies mapped in discrete field models, compared to anomalies mapped in continuous field models, of stream sediment geochemical landscapes mostly have stronger positive spatial associations with the known epithermal Au deposit occurrences in the study area. Empirical frequency distributions of either the original point data or the pixels values in the models of stream sediment geochemical landscapes are similarly useful in applying the C–A fractal method, but not in applying either the median+2 MAD or mean+2 SDEV method, to map anomalies in either continuous or discrete field models of such geochemical landscapes.