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Main Authors: Abdi, Fatemeh, Saraò, Angela, Magrin, Andrea, Sugan, Monica, Cataldi, Laura, Messuti, Giovanni, Rossi, Giuliana, Picozzi, Matteo
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Published: Zenodo 2026
Online Access:https://doi.org/10.5281/zenodo.20178125
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author Abdi, Fatemeh
Saraò, Angela
Magrin, Andrea
Sugan, Monica
Cataldi, Laura
Messuti, Giovanni
Rossi, Giuliana
Picozzi, Matteo
author_facet Abdi, Fatemeh
Saraò, Angela
Magrin, Andrea
Sugan, Monica
Cataldi, Laura
Messuti, Giovanni
Rossi, Giuliana
Picozzi, Matteo
contents <p>This dataset contains quality-controlled focal mechanism solutions for 122 earthquakes that occurred in the Southeastern Alps between January 2024 and October 2025, with local magnitudes Md 1.0–4.6.<br>First-motion polarities were automatically classified using the Convolutional First Motion (CFM) deep-learning model (Messuti et al., 2023). Focal mechanisms were then computed using SKHASH, a Python implementation of the HASH algorithm for focal-mechanism inversion based on first-motion polarities (Skoumal et al., 2024).<br>The dataset includes hypocentral parameters (origin time, latitude, longitude, depth), local magnitude (Md), nodal-plane orientations (strike, dip, rake), and solution-quality metrics derived from the SKHASH inversion, including polarity misfit, nodal-plane uncertainty, number of polarities, and station distribution ratio (STDR).</p> <p>This dataset also includes Validation_dataset.csv file for the validation dataset used to evaluate the automated CFM–SKHASH workflow. The dataset includes 159 earthquakes from 2014–2023 and compares focal mechanisms estimated using CFM–SKHASH with reference mechanisms from Magrin et al. (2024), which were obtained using manually reviewed polarities and the FPFIT algorithm. In this file, Event_id is given in YearMonthDayHourMinuteSecond format; latitude and longitude are reported in decimal degrees; Magnitude_MD is the duration magnitude; and Depth_km is the hypocentral depth in kilometers. Strike_1, Dip_1, and Rake_1 are the nodal-plane parameters estimated in this study using the CFM–SKHASH workflow, whereas Strike_2, Dip_2, and Rake_2 are the corresponding reference nodal-plane parameters from Magrin et al. (2024), obtained using manually reviewed polarities and the FPFIT algorithm.</p> <p><strong>References</strong><br>Messuti, G., S. Scarpetta, O. Amoroso, F. Napolitano, M. Falanga, and P. Capuano (2023). CFM: A convolutional neural network for first-motion polarity classification of seismic records in volcanic and tectonic areas, Front. Earth Sci. 11, https://doi.org/10.3389/feart.2023.1223686.</p> <p>Magrin, A., M. Sugan, A. Snidarcig, M. A. Romano, M. Guidarelli, M. Santulin, P. Di Bartolomeo, and A. Saraò (2024). Focal mechanism solutions of 162 earthquakes occurred between 2014 and 2023 in the Southeastern Alps, Zenodo, https://doi.org/10.5281/zenodo.10851786.</p> <p><strong></strong>Skoumal, R. J., J. L. Hardebeck, and P. M. Shearer (2024). SKHASH: A Python package for computing earthquake focal mechanisms, Seismol. Res. Lett. 95(4), 2519–2526, https://doi.org/10.1785/0220230329</p>
format Recurso digital
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institution Zenodo
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publishDate 2026
publisher Zenodo
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spellingShingle Focal mechanism solutions of 122 earthquakes occurred between 2024 and 2025 in the Southeastern Alps
Abdi, Fatemeh
Saraò, Angela
Magrin, Andrea
Sugan, Monica
Cataldi, Laura
Messuti, Giovanni
Rossi, Giuliana
Picozzi, Matteo
<p>This dataset contains quality-controlled focal mechanism solutions for 122 earthquakes that occurred in the Southeastern Alps between January 2024 and October 2025, with local magnitudes Md 1.0–4.6.<br>First-motion polarities were automatically classified using the Convolutional First Motion (CFM) deep-learning model (Messuti et al., 2023). Focal mechanisms were then computed using SKHASH, a Python implementation of the HASH algorithm for focal-mechanism inversion based on first-motion polarities (Skoumal et al., 2024).<br>The dataset includes hypocentral parameters (origin time, latitude, longitude, depth), local magnitude (Md), nodal-plane orientations (strike, dip, rake), and solution-quality metrics derived from the SKHASH inversion, including polarity misfit, nodal-plane uncertainty, number of polarities, and station distribution ratio (STDR).</p> <p>This dataset also includes Validation_dataset.csv file for the validation dataset used to evaluate the automated CFM–SKHASH workflow. The dataset includes 159 earthquakes from 2014–2023 and compares focal mechanisms estimated using CFM–SKHASH with reference mechanisms from Magrin et al. (2024), which were obtained using manually reviewed polarities and the FPFIT algorithm. In this file, Event_id is given in YearMonthDayHourMinuteSecond format; latitude and longitude are reported in decimal degrees; Magnitude_MD is the duration magnitude; and Depth_km is the hypocentral depth in kilometers. Strike_1, Dip_1, and Rake_1 are the nodal-plane parameters estimated in this study using the CFM–SKHASH workflow, whereas Strike_2, Dip_2, and Rake_2 are the corresponding reference nodal-plane parameters from Magrin et al. (2024), obtained using manually reviewed polarities and the FPFIT algorithm.</p> <p><strong>References</strong><br>Messuti, G., S. Scarpetta, O. Amoroso, F. Napolitano, M. Falanga, and P. Capuano (2023). CFM: A convolutional neural network for first-motion polarity classification of seismic records in volcanic and tectonic areas, Front. Earth Sci. 11, https://doi.org/10.3389/feart.2023.1223686.</p> <p>Magrin, A., M. Sugan, A. Snidarcig, M. A. Romano, M. Guidarelli, M. Santulin, P. Di Bartolomeo, and A. Saraò (2024). Focal mechanism solutions of 162 earthquakes occurred between 2014 and 2023 in the Southeastern Alps, Zenodo, https://doi.org/10.5281/zenodo.10851786.</p> <p><strong></strong>Skoumal, R. J., J. L. Hardebeck, and P. M. Shearer (2024). SKHASH: A Python package for computing earthquake focal mechanisms, Seismol. Res. Lett. 95(4), 2519–2526, https://doi.org/10.1785/0220230329</p>
title Focal mechanism solutions of 122 earthquakes occurred between 2024 and 2025 in the Southeastern Alps
url https://doi.org/10.5281/zenodo.20178125