Page 60 - Geochemical Anomaly and Mineral Prospectivity Mapping in GIS

Exploratory Analysis of Geochemical Anomalies 59

different populations in a uni-element geochemical data set comparable (Fig. 3-5B). The
MAD can be used in lieu of IQR in equation (3.10), thus:

X − median
Z = ij j . (3.11)
ij
MAD j

The EDA standardised values according to equation (3.11) are thus analogous to the
classical standardised values according to equation (3.9).
In order to compare anomalies associated with different populations in a uni-element
geochemical data set, the boxplot-defined threshold and the IQR defined for each
population j can be used for standardisation (cf. Yusta et al., 1998):

X − threshold
Z = ij j . (3.12)
ij
IQR j

The standardisation via equation (3.12) should make use of the same type of boxplot-
defined threshold values (e.g., the boxplot UW). Alternatively, the median+2MAD and
the median can be used for standardisation:

X − ( median + 2 MAD)
Z = ij j . (3.13)
ij
median j

The standardisation algorithms in either equation (3.10) or equation (3.11) would
allow representation of uni-element geochemical data from different sampling media in
the same maps in order to, for example, compare spatial distributions of the same
elements in rocks and soils. Equation (3.12) or equation (3.13) could be used, for
example, to compare anomalies of the same (pathfinder) elements in different sampling
media. Standardisation of various uni-element geochemical data sets via either equation
(3.10) or equation (3.11) can be an important step prior to modeling of multi-element
signatures through application of multivariate analytical techniques, which require
proper estimation of the multivariate covariance (or correlation) matrix.

Mapping of classified uni-element geochemical data
EDA-mapping symbols (Tukey and Tukey, 1981; Kürzl, 1988; Reimann, 2005), such
as those shown in Fig. 3-4, have been proposed to represent data in robust-class intervals
defined by a boxplot. A boxplot can be conveniently used as a map legend explaining the
symbols of classes of data values. For point-symbol representation of uni-element
geochemical data (say, for stream sediment samples), circles and crosses are used
because they can be readily perceived to signify low and high values, respectively. Thus,
extremely low background values, which are usually more infrequent than anomalies in
an exploration uni-element geochemical data set, are represented by large open circles;