The geological science has been in recent years an excellent playground for
GIS applied studies, especially regarding the mineral deposits prospectivity. Other
fields of study in the geological science (e.g. soil risk management, mining
exploitation, geothermal resources…) also took advantages of this geocomputing
methodology to extract spatial information. The geoscientist community fairly agrees
that interrelations between mineral deposits and certain geological features are
observed in the terrain, presenting also a non-random spatial regional distribution
pattern in a vast majority of cases. This is where the spatial analysis using
geocomputational techniques, in this particular case for rare-elements pegmatites, can
be used as a great analytical tool to produce a mapping of mineral potential, or unveil
the regional zonation patterns for this type of mineralization. In this study, statistical
spatial analyses were performed for the pegmatites to highlight any possible
relationship, or lack of it, between them and the surrounding granitic plutons, shear
zones or schistose foliations. To accomplish our proposed objectives, the
geocomputational method of Distance to Nearest Neighbours (DNN), Ripley’s L’-
function and pegmatites orientations families were employed to study the spatial
distribution pattern of the pegmatites, whereas Euclidean distance and Kernel density
distributions aimed the spatial association between these same pegmatites to the
various geological features within the study area. The obtained results show: i)
Pegmatites spatial distribution following a clustering pattern, presenting the Lienriched
pegmatites a higher rate and extent compared to the total pegmatites, as well
as a spatial association with moderate to high pegmatites density; ii) Three distinct
families of pegmatites orientation; iii) No statistically significant spatial relationship
for the total pegmatites or Li-enriched relatively to the granitic pluton; iv) A regime of
deformation within the study area, suggesting the presence of corridors of deformation with NW to NNW orientations; and v) Pegmatites spatial emplacement suggesting
shear-zones control.
Keywords: DNN, GIS, Geostatistics, Interpolated foliation, Kernel density,
Pegmatites, Ripley’s L’-function, Shear-Zones, Spatial analysis, Variogram.
