Seismogram waveform datasets for ConvNetQuake_INGV
<p>This data archive contains the training, validation and test datasets for ConvNetQuake_INGV as presented in this article:</p> <p>Lomax, A., Michelini, A., & Jozinović, D. (2019). An Investigation of Rapid Earthquake Characterization Using Single‐Station Waveforms and a Convolutional Neural Network. Seismological Research Letters, 90(2A), 517–529. https://doi.org/10.1785/0220180311</p> <p>The training [validation] datasets consist of 15,200 [1773] event and 10,724 [1198] noise three-component waveforms and associated metadata from MedNet stations using events from 2010 to 2018 at 0°–180° with lower magnitude limits set as a function of event epicentral distance.<br> The test datasets consists of 1003 event and 621 noise three-component waveforms and associated metadata and an extended set of 4074 test events from 2007 to 2009, selected otherwise with the same criteria as for the training and validation datasets.<br> </p> <p>The easiest way to work with the hdf5 file is to use the python library h5py. See README.txt</p>
ShareScore
48/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 20
- Reuse readiness
- 8
- Engagement
- 8
Topics
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