Page 63 - Geochemical Anomaly and Mineral Prospectivity Mapping in GIS

62 Chapter 3

APPLICATIONS OF GIS IN EDA

Management of spatial data

EDA clearly requires a spatial database of sample location coordinates, geochemical
data attributes and other pertinent geological and geomorphological attributes that may
have been recorded during the field sampling campaign. A spatial database may or may
not be created in a GIS. On the one hand, because there are GIS software packages that
do not have EDA statistical and graphical tools, a spatial database created in a GIS
should be readily exportable to or importable by any statistical software package that
supports EDA. On the other hand, because most statistical software packages do not
have mapping tools, a spatial database created outside a GIS must be readily exportable
to or importable by the GIS software available to the user. Thus, inter-operability of a
spatial database between a GIS and an EDA-supporting statistical software package is
highly desirable.

Operations on spatial data
Spatial query operations in a GIS are useful in subdividing a uni-element
geochemical data set into subsets according to certain spatial attributes of variables (e.g.,
lithology) that control geochemical variability. There may be cases where the digital
geochemical database acquired does not consist of other thematic data attributes (e.g.,
lithology at sample sites) that are important for analysis and interpretation, but such
thematic data are available as digital maps (vector or raster). In such cases, a spatial join
operation (see Chapter 2) between a map of point sample locations and a thematic map
can be performed to add a new thematic data attribute in the geochemical database.
Depending on GIS software, a spatial join operation can be performed simply via table
calculation (Fig. 3-7). In some GIS software, adding new thematic attributes in a
geochemical database requires a map intersect operation followed by a table join
operation. The newly added attribute can then be used as categorical variable in creating
boxplots (Fig. 3-5).
Classification of a uni-element geochemical data set (or subsets) as well as
standardisation of geochemical data according to boxplot-defined classes and EDA
statistics can be performed in a GIS. These operations can be carried out via either
attribute table calculation or map calculation. Fig. 3-8 shows an example of a table
calculation to standardise the soil Fe data based on the median and IQR of data subsets
according to rock type at sample site (see Fig. 3-5A) and using equation (3.10).

Visualisation of spatial data or geo-information
A GIS can clearly support mapping and visualisation of EDA results in order to
describe or explain plausible underlying processes that govern the spatial distributions of
uni-element geochemical data. Maps of geochemical attributes or derivative attributes
using, say boxplot-defined classes, can be readily created in a GIS (e.g., Fig. 3-6). Most