Machine Learning aids rapid assessment of aftershocks: Application to the 2022-2023 Peace River earthquake sequence, Alberta, Canada ...

• Main Authors: Li, Jinji, Rojas-Parra, Jesus, Salvage, Rebecca O., Eaton, David W., Innanen, Kristopher, Gu, Yu Jeffrey, Sun, Wenhan
• Format: Dataset
• Language: English
• Published: Zenodo 2023
• Subjects: Machine Learning; Seismology; Western Canada; PhaseNet; EQTransformer; Canada; Peace River
• Online Access: https://dx.doi.org/10.5281/zenodo.10436534; https://zenodo.org/doi/10.5281/zenodo.10436534

Two catalogs are provided as part of the publication "Machine Learning aids rapid assessment of aftershocks: Application to the 2022-2023 Peace River earthquake sequence, Alberta, Canada", in The Seismic Record. Catalog_PR_EQTransformer_TSR.csv was produced using PhaseNet (Zhu and Beroza, 2018); Catalog_PR_PhaseNet_TSR.csv was produced using EQTransformer (Mousavi et al., 2020). The files contain the following columns: UTCDateTime: UTC Date and Time of detected event NLL_Ev_Lat_Deg: Event Latitude in decimal degrees NLL_Ev_Long_Deg: Event Longitude in decimal degrees NLL_Ev_Z_km: Event Depth in kilometers NLL_Ev_Lat_err: Event Latitude Error in kilometers NLL_Ev_Long_err: Event Longitude Error in kilometers NLL_Ev_Z_err: Event Depth Error in kilometers Calibrated_Ml: Calibrated local magnitude Hypocenter locations and associated errors were calculated using NonLinLon (Lomax et al.. 2000; 2009) using the velocity model provided in Schultz et al., 2023. Magnitudes were calculated using Babaie-Mahani and Kao ...