Elemental concentrations in artisanal and small-scale gold mining environments reflect overlapping geological and anthropogenic controls, complicating the identification of multielement geochemical anomalies. This study analysed 665 B-horizon soil samples for 14 elements using X-ray fluorescence (XRF) and applied principal component analysis (PCA), Classical Mahalanobis distance (MD), robust MD, and spatial autocorrelation. PCA retained three components explaining 62.89% of the total variance and identified 60 anomalies (9.02%), compared with 51 (7.67%) for Classical MD and 120 (18.05%) for robust MD. Overall, at least one method identified 164 samples (24.66%), at least two methods identified 57 (8.57%), and all three methods identified 10 (1.50%). PCA showed the strongest spatial dependence, with a Global Moran’s I of 0.1474 (p = 0.002). Local spatial analysis corroborated 25.00% of PCA, 13.73% of Classical MD, and 10.00% of robust MD anomalies. The results indicate that PCA identifies more spatially coherent anomalies, whereas robust MD detects a broader range of unusual multielement compositions. Integrating these methods provides complementary evidence for prioritising locations for field verification and environmental monitoring in mineralised and mining-affected areas.
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Kazapoe et al. (2026) studied this question.
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