Quantifying effect of geological factor on distribution of earthquake occurrences by inhomogeneous Cox processes

TL;DR

This paper introduces inhomogeneous Cox process models to quantify how geological factors like subduction zones, faults, and volcanoes influence earthquake distribution in Indonesia, improving understanding of seismic risk.

Contribution

It develops and compares new inhomogeneous Cox process models incorporating geological variables, enhancing the analysis of earthquake spatial patterns.

Findings

Subduction zone and volcano proximity significantly affect earthquake risk.

Cauchy and variance-Gamma models fit earthquake data well.

Model selection via AIC supports the proposed models.

Abstract

Research on the earthquake occurrences using a statistical methodology based on point processes has mainly focused on the data featuring earthquake catalogs which ignores the effect of environmental variables. In this paper, we introduce inhomogeneous versions of the Cox process models which are able to quantify the effect of geological factors such as subduction zone, fault, and volcano on the major earthquake distribution in Sulawesi and Maluku, Indonesia. In particular, we compare Thomas, Cauchy, variance-Gamma, and log-Gaussian Cox models and consider parametric intensity and pair correlation functions to enhance model interpretability. We perform model selection using the Akaike information criterion (AIC) and envelopes test. We conclude that the nearest distances to the subduction zone and volcano give a significant impact on the risk of earthquake occurrence in Sulawesi and Maluku. Furthermore, the Cauchy and variance-Gamma cluster models fit well the major earthquake distribution in Sulawesi and Maluku.