Vent Distribution on Jeju Island, South Korea: Glimpses Into the Subvolcanic System

Abstract

The spatial distribution of vents is ultimately controlled by the geometry of the magma source at depth, stress orientation and pre‐existing crustal structures. In this work, the spatial patterns of vent distribution in Jeju Island, South Korea, are examined through several methods. Comparison of the obtained distribution patterns with previous knowledge about the volcanic evolution of the island, and recent results of seismic tomographic images provides a comprehensive interpretation of vent distribution in terms of the underlying structure of the sub‐volcanic system. Thus, it is proposed that under certain conditions the probability density functions of some groups of vents can be used to obtain rough estimates of the depths of magma storage. Also, it is shown that the overall spatial pattern of vents provides an integrated image of the sub‐volcanic system both in space and time. The results reported in this work can therefore help us to avoid unjustified speculations concerning the nature of activity present in zones of distributed volcanism elsewhere.

Sub‐Volcanic Structure Beneath Marius Hills, Moon, Inferred From Vent Distribution

“…Based on the experience obtained with recent analyses of vent distribution in two zones of active volcanism on Earth (Cañón‐Tapia, 2021c, 2021d), we obtained a Probability Density Distribution (PDF) of each core group identified on Marius Hills. The PDF of each group was characterized by having nested contours with a small change of shape between the central and external contours.…”

“…On Earth, vent distribution has been shown to yield information that is roughly compatible with the structure of magma distribution inferred from seismic tomography (Cañón-Tapia, 2021c, 2021d. Due to the lack of sufficient seismic information, such comparison is impossible to be completed on the Moon.…”

“…Our characterization of the distribution of vents on the Marius Hills region modifies the four‐stage analysis described in detail by Cañón‐Tapia (2021c) by substituting the last two steps with the determination of clusters using a fuzzy c‐means algorithm (fcm). A reason to include this step instead of the hybrid algorithm adopted by Cañón‐Tapia (2021c) is the characteristic of the fcm to provide a membership‐based on a probability value in a more straightforward form than the hybrid algorithm. Such characteristics allow the user to select a probability threshold to define which vents are associated with which cluster reducing the influence of subjective criteria.…”

“…Besides gravimetric anomalies, information concerning the magmatic plumbing structure beneath a given region can be obtained by examining the surface distribution of volcanic vents (e.g., Cañón-Tapia, 2021b, 2021cConnor, 1990;Deng et al, 2017;Kiyosugi et al, 2012;Spörli & Eastwood, 1997). This is the case because magma transport away from a region of storage beneath the surface commonly occurs through conduits formed by the brittle fracture of the outermost planetary solid layer.…”

Kernel Analyses of Volcanic Vent Distribution: How Accurate and Complete are the Objective Bandwidth Selectors?

“…There is a vast literature discussing several probability aspects that may produce variable and mutually inconsistent hazard and risk estimates in both seismic and volcanic contexts (e.g., Bernreuter et al, 1988;Marzocchi et al, 2008;Neri et al, 2008;Marzocchi and Bebbington, 2012;Marzocchi and Jordan, 2014;Ake et al, 2018;Bevilacqua et al, 2018;Selva et al, 2019;Marzocchi et al, 2021). Works with a more pronounced statistical approach, however, are not as common (Richardson et al, 2012;Cañón-Tapia, 2014;Cañón-Tapia and Mendoza-Borunda, 2014;Delcamp et al, 2019;Jacobo-Bojórquez and Cañón-Tapia, 2020;Cañón-Tapia, 2021b). It must be remarked that the difference made here between the probabilistic and statistic reports is based on the purpose of the study rather than on the tools used for the presentation of data.…”