Geochemical pattern classification of recent volcanic products from Mt. Etna, Italy, based on Kohonen maps and fuzzy clustering

Abstract

We present the application of a classification method based on Kohonen maps and fuzzy clustering to geochemical analyses of volcanic products erupted on Mt. Etna from 1995 to 2005. Based on 13 major and trace elements, the classification allows a new way to visualize distinct compositional features of magma both considering long period as well as single eruptive events, such as in 2001 and 2002–03 flank eruptions. Products of the various vents do not necessarily form homogeneous groups, but show clear trends of chemical evolution with time. Using a convenient color code, the graphical visualization of the results in just a single picture allows the rapid identification of the compositional features of each sample and their comparison with all the products analyzed in the 10-year-long time span. This single picture accounts for the mutual interactions of the 13 components avoiding shortcomings of classical low-dimensional plots where components relevant for the discrimination have to be found in a priori study of many diagrams. On the basis of the synoptic information provided by pattern classification, we identify links between the products of different eruptive vents which deliver a reliable picture of a multifaceted plumbing system, in agreement with geochemical and geophysical evidence reported in literature. The analysis of the 13-dimensional data set using the Kohonen maps and fuzzy clustering simultaneously turned out to be straightforward and easy. Accordingly, the results of this application will be useful also as a contextual data set for new data in future ongoing eruptive episodes.