Automatic seismic event locations in Germany using TieBeNN

🗂️ Description This repository contains automatic absolute locations of local seismic events in Germany and surrounding regions, computed using the automatic location system TieBeNN (TiefenBestimmung mittels Neuronaler Netze). Event date times and epicenter coordinates were taken from manual catalogs to test TieBeNN. All events have: A minimum local magnitude of 1.0 A tectonic origin The following event catalogs are included: automatic_catalog_2021-2023_tiebenn.csv – 591 local events from the BGR catalog (2021–2023) automatic_catalog_2024_BENS.csv – 55 events from the BENS catalog (2024) automatic_catalog_2024_LED.csv – 50 events from the LED catalog (2024) automatic_catalog_2024_SED.csv – 50 events from the SED catalog (2024) automatic_catalog_2024_TSN_EdB.csv – 50 events from the TSN catalog (2024), located using BGR’s 1D velocity model automatic_catalog_2024_TSN_WB2012.csv – 50 events from the TSN catalog (2024), located using the WB2012 1D velocity model (Růžek & Horálek, 2013) 🔹 Abbreviations: BGR = Bundesanstalt für Geowissenschaften und Rohstoffe BENS = Erdbebenstation Bensberg SED = Schweizerischer Erdbebendienst LED = Landeserdbebendienst Baden-Württemberg TSN = Thüringer Seismologisches Netz 📊 Catalog structure Each CSV file contains: Hypocenter coordinates and uncertainties Eight normalized features used to compute the Location Quality Score (LQS) These are the columns and their descriptions: datetime: Event origin time latitude / longitude (°): Epicenter coordinates depth (km): Hypocentral depth unc_x / unc_y / unc_z (km): location uncertainty in x, y, z directions norm.det.cov: Normalized location covariance norm.sta.den: Normalized station density norm.azgap: Normalized azimuthal gap norm.sec.azgap: Normalized secondary azimuthal gap norm.aui: Normalized azimuthal uniformity index norm.near.sta: Normalized nearest station distance norm.rms: Normalized RMS of travel time residuals norm.npicks: Normalized number of phase picks LQS: Location Quality Score 🤖 About TieBeNN TieBeNN is a Python-based wrapper that integrates open-source, machine-learning tools for: Phase picking Denoising Phase association Probabilistic hypocenter estimation via NonLinLoc 🔗 Code: https://github.com/Cthuulhaa/tiebenn 🔗 DOI: https://zenodo.org/records/15384316 📘 Docs: https://tiebenn.readthedocs.io/en/latest --- 📄 Citation A paper describing TieBeNN and the Location Quality Score (LQS) is currently in preparation. A pre-print will be available soon! In the meantime, feel free to use this dataset and cite this Zenodo record.