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92                                                              Chapter 4

             Multifractality of geochemical landscapes
                The two line segments fitted to the log-log plot of the concentration-area relationship
             (Fig. 4-3) indicate that there are at least two sets of fractal patterns in the soil Fe data.
             This suggests that geochemical landscapes can  be  multifractals.  A multifractal is
             considered to  be spatially intertwined sets  of  monofractals (Feder,  1988; Stanley and
             Meakin, 1988). Whereas monofractals are characterised by one fractal dimension and
             thus apply to binary patterns, multifractals  have  different fractal dimensions and thus
             apply to patterns with continuous spatial variability (Agterberg, 1994, 2001).  As the
             subset of “high” Fe value can be characterised by a fractal dimension, so can the subset
             of “low” Fe values, although this is not to say that either subset is a monofractal because
             they both have continuous spatial variability. Thus, the multifractality of geochemical
             landscapes can be related to the probability density distributions and spatial distributions
             of geochemical data (Cheng and Agterberg, 1996; Gonçalves, 2001; Wei and Pengda,
             2002; Panahi and Cheng, 2004; Xie and Bao, 2004; Shen and Cohen, 2005), which are
             influenced by various processes that have occurred throughout geological time at various
             rates and at  various  scales (e.g., Rantitsch,  2001). If that is the case, then the
             concentration-area relation introduced earlier is appropriately a  multifractal model,
             which can  be  used to separate geochemical anomalies from background as proposed
             originally by  Cheng et al.  (1994).  The concentration-area fractal method  has been
             demonstrated by several workers to  map significant anomalies using  various
             geochemical sampling media (e.g., Cheng et al., 1996, 1997, 2000; Cheng, 1999b; Sim
             et al., 1999; Gonçalves et al., 2001; Panahi  et al., 2004) and is  reviewed and further
             demonstrated here.

             THE CONCENTRATION-AREA METHOD FOR THRESHOLD RECOGNITION

                The  following discussion  of the concentration-area method for separation  of
             geochemical anomalies from background is adapted  from Cheng et al. (1994).  For  a
             series of contours of uni-element concentrations, the concentration contours v and the
             areas of uni-element concentrations equal to or greater than v or the areas enclosed by
             each contour [i.e.,  A(•v)] satisfy the following  power-law relation if they have
             multifractal properties:

             A( ≥v) ∝ v − α                                                     (4.5)

             where ∝ denotes proportionality and the exponent α represents the slope of a straight
             line fitted by least squares through a log-log plot of the relation. If, on the one hand, the
             concentration-area relation represents a fractal model, then the log-log plot can be fitted
             by one straight line and thus by one value of α corresponding to the whole range of v,
             representing a group of similarly-shaped concentration contours. If, on the other hand,
             the concentration-area relation represents a multifractal model, then the log-log plot can
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