Machine Learning in Discriminating Active Volcanoes of the Hellenic Volcanic Arc

Athanasios G Ouzounis,George A Papakostas

doi:10.3390/app11188318

Athanasios G Ouzounis, George A Papakostas

Open Access

https://doi.org/10.3390/app11188318

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Journal: Applied sciences	Publication Date: Sep 8, 2021
Citations: 2	License type: CC BY 4.0

Affiliation: International Hellenic University

Abstract

Identifying the provenance of volcanic rocks can be essential for improving geological maps in the field of geology and providing a tool for the geochemical fingerprinting of ancient artifacts like millstones and anchors in the field of geoarchaeology. This study examines a new approach to this problem by using machine learning algorithms (MLAs). In order to discriminate the four active volcanic regions of the Hellenic Volcanic Arc (HVA) in Southern Greece, MLAs were trained with geochemical data of major elements, acquired from the GEOROC database, of the volcanic rocks of the Hellenic Volcanic Arc (HVA). Ten MLAs were trained with six variations of the same dataset of volcanic rock samples originating from the HVA. The experiments revealed that the Extreme Gradient Boost model achieved the best performance, reaching 93.07% accuracy. The model developed in the framework of this research was used to implement a cloud-based application which is publicly accessible at This application can be used to predict the provenance of a volcanic rock sample, within the area of the HVA, based on its geochemical composition, easily obtained by using the X-ray fluorescence (XRF) technique.

Highlights

The Hellenic Volcanic Arc (HVA) in Southern Greece consists of four volcanic regions (Figure 1), namely the Methana region, which includes Methana, Aigina, and Poros in the west; the Melos region, consisting of Melos, Antimelos, and Kimolos in the southwest; the Santorini region, consisting of Santorini, Kolumbus, and Christianoi in the southeast; and the Nisyros region consisting of Nisyros, Giali, and Pergousa in the east
The extent of the HVA is well-mapped on the surface [1], but little is known about its extent under the seafloor
The results of this research prove that the Machine learning (ML) methodology used for discriminating tectonic environments can be used to discriminate volcanic regions belonging to the same tectonic setting

Summary

Introduction

The Hellenic Volcanic Arc (HVA) in Southern Greece consists of four volcanic regions (Figure 1), namely the Methana region, which includes Methana, Aigina, and Poros in the west; the Melos region, consisting of Melos, Antimelos, and Kimolos in the southwest; the Santorini region, consisting of Santorini, Kolumbus, and Christianoi in the southeast; and the Nisyros region consisting of Nisyros, Giali, and Pergousa in the east. A large part of the HVA is buried under the sediments of the Southern Aegean Sea. Future deep-sea drilling for mineral prospecting will provide rock samples to produce more precise geological borders for the HVA. In order for these rock samples to be used for mapping, they have to be correlated to one of the four active volcanic regions. Volcanic tocks from the HVA have been used to produce artifacts like millstones and anchors from prehistoric times. These artifacts can be found scattered all around the Mediterranean.

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