Cluster analysis for a standardized classification and description of
volcanic ash: Case study of the 1983 eruption at Miyakejima, Japan
Abstract
The composition of volcanic ash, which is a source of primary
description data in volcanological study, is important information for
estimating the eruption styles and sequences. However, its description
under a microscope by human operation has difficulties in classification
thresholds and time and effort-consumptions. This study demonstrates an
accurate and rapid description of volcanic ash samples that consist of
thousands of grains. We analyzed nine tephra samples (two magmatic (dry)
and seven phreatomagmatic (wet)), which were produced in the 1983 A.D.
fissure eruption event at Miyakejima volcano, Japan. Our dataset, which
is consists of multivariate shape and transparency parameters, was
rapidly obtained using an automated grain analyzer. In this study, we
applied a two-step cluster analysis to objectively and quantitatively
define grain type and classify samples. To define grain types, we
referred to the statistically appropriate number of clusters of
whole-ash grains in our samples. For our samples, the appropriate number
of clusters for grain type was five. Each grain type is characterized by
parameters and has different proportions among our samples. In wet
tephra samples, grains that were categorized as transparent and highly
irregularly shaped types were relatively abundant. Those grains can be
considered as vesicular sideromelane grains, which are often found in
products of phreatomagmatic eruptions. Such a standardized description
of volcanic ash based on statistically determined grain type will
contribute to initial descriptions before subsequent detailed analysis.