Mineral exploration in biogeochemistry is related to the detection of anomalies in soil, which is driven by many factors and thus a complex problem. Mikšová, Rieser, and Filz-moser (2019b) have introduced a method for the identification of spatial patterns with increased element concentrations in samples along a linear sampling transect. This proce-dure is based on fitting Generalized Additive Models (GAMs) to the concentration data, and computing a curvature measure from the pairwise log-ratios of these fits. The higher the curvature, the more likely one or both elements of the pair indicate local mineral-ization. This method is applied on two geochemical data sets which have been collected specifically for the purpose of mineral exploration. The aim is to test the technique for its ability to identify pathfinder elements to detect mineralized zones, and to verify whether the method can indicate which sampling material is best suited for this purpose.
|Tidsskrift||Austrian Journal of Statistics|
|Status||Udgivet - 13 apr. 2020|
- Programområde 4: Mineralske råstoffer