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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Supplement to Qseek: A Data-Driven Framework for Automated Earthquake Detection, Localization and Characterization

Research datakeyboard_double_arrow_right Dataset 04 Feb 2025 English Publisher:ZenodoFunded by:DFG | unidentified
Authors: Isken, Marius;

doi: 10.5281/zenodo.14802237 , 10.5281/zenodo.14802236

Supplement to Qseek: A Data-Driven Framework for Automated Earthquake Detection, Localization and Characterization

Abstract

Supplementary material to Qseek: A Data-Driven Framework for Machine-Learning Earthquake Detection, Localization and Characterization. The dataset presents earthquake catalogs as CSV: Reykjanes Peninsula, 2020 Eifel Large-N Experiment, 2022 Utah FORGE, 2024 The qseek catalogs feature WKT coordinated for native plotting in QGIS. The `-earthmodel.nd` files contain the seismic velocity model in Named Discontiunities format.

Related Organizations
Keywords

Machine learning, Earthquakes, Volcano, Seismology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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Average