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East Antarctic Seismicity from different Automated Event Detection Algorithms Data DOI: https://doi.org/10.15784/601762 Cite as Hansen, S., Ho, L., & Walter, J. (2024) "East Antarctic Seismicity from different Automated Event Detection Algorithms" U.S. Antarctic Program (USAP) Data Center. doi: https://doi.org/10.15784/601762. AMD - DIF Record(s) USAP-1914767_1 Abstract As seismic data availability increases, the necessity for automated processing techniques has become increasingly evident. Expanded geophysical datasets collected over the past several decades across Antarctica provide excellent resources to evaluate different event detection approaches. We have used the traditional Short-Term Average/Long-Term Average (STA/LTA) algorithm to catalogue seismic data recorded by 19 stations in East Antarctica between 2012 and 2015. However, the complexities of the East Antarctic dataset, including low magnitude events and phenomena such as icequakes, warrant more advanced automated detection techniques. Therefore, we have also applied template matching as well as several deep learning algorithms, including Generalized Phase Detection (GPD), PhaseNet, BasicPhaseAE, and EQTransformer (EQT), to identify seismic phases within our dataset. Our goal was not only to increase the volume of detectable seismic events but also to gain insights into the effectiveness of these different automated approaches. Our assessment evaluated the completeness of the newly generated catalogs, the precision of identified event locations, and the quality of the picks. The final events corresponding to each of our three catalogs (based on STA/LTA, template matching, and machine learning, respectively) are listed in the provided files. Creator(s): Hansen, Samantha; Ho, Long; Walter, Jacob Date Created: 2024-01-24 Repository: USAP-DC (current) License: Creative Commons Attribution Only v4.0 Generic [CC BY 4.0] Spatial Extent(s) West: 148, East: 172, South: -78, North: -71.5 Temporal Extent(s) Start: 2012-11-15 - End: 2015-12-31 Award(s) NSF 1914698 Version: 1 Related Project(s) Collaborative Research: Resolving earth structure influence on ice-sheet stability in the Wilkes Subglacial Basin (RESISSt) References Ho, L.M., Walter, J.I., Hansen, S.E., Sánchez-Roldán, J.L., & Peng, Z. (2023). Comparison of Automatic Event Detection Algorithms: A Case Study in East Antarctica, AGU Fall 2023 Meet., Abstract S31C-0366. Ho, L.M., Walter, J.I., Hansen, S.E., & Peng, Z. (2022). Comparison of Automated Seismic Event Detection Approaches in East Antarctica, AGU Fall 2022 Meet., Abstract S42D-0183. Keywords Antarctica Geoscientificinformation Machine Learning Seismic Event Detection Seismology Seismometer