Abstract. Understanding and describing spatial arrangements of mineral particles and determining the mineral distribution structure are important to model the rock-forming process. Geometric properties of individual mineral particles can be estimated from thin sections, and different models have been proposed to quantify the spatial complexity of mineral arrangement. The Gejiu tin-polymetallic oreforming district, located in Yunnan province, southwestern China, is chosen as the study area. The aim of this paper is to apply fractal and multifractal analysis to quantify distribution patterns of pyrrhotite particles from twentyeight binary images obtained from seven basalt segments and then to discern the possible petrological formation environments of the basalts based on concentrations of trace elements. The areas and perimeters of pyrrhotite particles were measured for each image. Perimeter-area fractal analysis shows that the perimeter and area of pyrrhotite particles follow a power-law relationship, which implies the scaleinvariance of the shapes of the pyrrhotites. Furthermore, the spatial variation of the pyrrhotite particles in space was characterized by multifractal analysis using the method of moments. The results show that the average values of the area-perimeter exponent (D AP ), the width of the multifractal spectra ( (D(0) − D(2)) and (D(q min ) − D(q max ))) and the multifractality index (τ (1)) for the pyrrhotite particles reach their minimum in the second basalt segment, which implies that the spatial arrangement of pyrrhotite particles in Segment 2 is less heterogeneous. Geochemical trace element analysis results distinguish the second basalt segment sample from other basalt samples. In this aspect, the fracCorrespondence to: S. Xie (tinaxie2006@gmail.com) tal and multifractal analysis may provide new insights into the quantitative assessment of mineral microstructures which may be closely associated with the petrogenesis as shown by the bulk-rock geochemical analysis.

Abstract. This contribution introduces a fractal filtering technique newly developed on the basis of a spectral energy density vs. area power-law model in the context of multifractal theory. It can be used to map anisotropic singularities of geochemical landscapes created from geochemical concentration values in various surface media such as soils, stream sediments, tills and water. A geochemical landscape can be converted into a Fourier domain in which the spectral energy density is plotted against the area (in wave number units), and the relationship between the spectrum energy density (S) and the area (A) enclosed by the above-threshold spectrum energy density can be fitted by power-law models. Mixed geochemical landscape patterns can be fitted with different S-A power-law models in the frequency domain. Fractal filters can be defined according to these different S-A models and used to decompose the geochemical patterns into components with different self-similarities. The fractal filtering method was applied to a geochemical dataset from 7,349 stream sediment samples collected from Gejiu mineral district, which is famous for its word-class tin and copper production. Anomalies in three different scales were decomposed from total values of the trace elements As, Sn, Cu, Zn, Pb, and Cd. These anomalies generally correspond to various geological features and geological processes such as sedimentary rocks, intrusions, fault intersections and mineralization.