TY - JOUR

T1 - Computational intelligence of GMT and R for modelling seismicity in Cuba

AU - Леменкова, Полина Алексеевна

PY - 2026/1/1

Y1 - 2026/1/1

N2 - Data analysis is essential in seismology which integrates cartographic techniques and geophysical information for monitoring seismic events: earthquakes, tsunamis and volcanism. Substantial gaps still persist in this domain which requires developing novel methods for visualization and rapid data processing. Addressing these challenges is imperative to maximize the efficiency of data modelling. Cuba is located in the zone of high seismic risk due to seismotectonic setting. High risk of seismicity in Cuba is caused by its location at the intersection of the two tectonic plates – the North American and Caribbean. Here we propose advanced scripting methods on seismic data processing using GMT and R scripts. The dataset on seismicity in Cuba was collected from the NSF SAGE and USGS and processed to visualize the distribution, frequency and magnitude of earthquakes from 1973 to 2025. The data on tsunami was obtained from the NCEI/WDS to analyse the retrospective occurrence of the events. The results of the data analysis shown that in 2024, significant earthquakes were recorded 35-40 km SSW of Bartolomé Masó with magnitude 5.8 and 6.8 ML Richter scale, and in 2020, the earthquake with the magnitude of 7.7 struck off the SE coast of Cuba. However, the data analysis shown that the most frequent type of earthquakes in Cuba has a low magnitude (ML 4.3 R. s.), which is causes no structural damages. This paper contributed to development of seismic hazards prognosis by presenting R and scripting GMT algorithms for seismological data analysis.

AB - Data analysis is essential in seismology which integrates cartographic techniques and geophysical information for monitoring seismic events: earthquakes, tsunamis and volcanism. Substantial gaps still persist in this domain which requires developing novel methods for visualization and rapid data processing. Addressing these challenges is imperative to maximize the efficiency of data modelling. Cuba is located in the zone of high seismic risk due to seismotectonic setting. High risk of seismicity in Cuba is caused by its location at the intersection of the two tectonic plates – the North American and Caribbean. Here we propose advanced scripting methods on seismic data processing using GMT and R scripts. The dataset on seismicity in Cuba was collected from the NSF SAGE and USGS and processed to visualize the distribution, frequency and magnitude of earthquakes from 1973 to 2025. The data on tsunami was obtained from the NCEI/WDS to analyse the retrospective occurrence of the events. The results of the data analysis shown that in 2024, significant earthquakes were recorded 35-40 km SSW of Bartolomé Masó with magnitude 5.8 and 6.8 ML Richter scale, and in 2020, the earthquake with the magnitude of 7.7 struck off the SE coast of Cuba. However, the data analysis shown that the most frequent type of earthquakes in Cuba has a low magnitude (ML 4.3 R. s.), which is causes no structural damages. This paper contributed to development of seismic hazards prognosis by presenting R and scripting GMT algorithms for seismological data analysis.

KW - seismicity

KW - cartography

KW - R programming

KW - statistical analysis

KW - geophysics

U2 - 10.5281/zenodo.18092130

DO - 10.5281/zenodo.18092130

M3 - Article

VL - 19

SP - 387

EP - 402

JO - Serie Científica de la Universidad de las Ciencias Informáticas

JF - Serie Científica de la Universidad de las Ciencias Informáticas

SN - 2306-2495

IS - 1

ER -