Abstract
Abstract Decomposing mixed geochemical patterns is a challenge in geochemical exploration and environmental assessment. In this paper, the spectrum–area technique (S–A) is used to decompose a mixed pattern of arsenic in Gangdese belt based on stream sediment data. S–A is a multifractal model based on power–law relationships between area of the set consisting of wave numbers with spectral energy density above S[A(>S)] on the 2D frequency domain. The original spatial distribution map of arsenic obtained by inverse distance weighted (IDW) shows a mixed pattern due to superposition of different geological processes or events and is converted into the frequency domain by means of Fourier transformation. Two components, including power spectrum density and phases, are obtained. The spectrum energy density (S) and the area (A) enclosed by the above-threshold spectrum energy density is plotted on a log–log scale. Two cutoff values determined by three straight lines define three filters which decompose the original map of arsenic into background, anomalous, and high frequency (noise) components. The areas with high anomaly of arsenic mainly are located surrounding known Cu deposits, indicating that arsenic anomalies may be related to Cu mineralization.
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