ObsPy: A Python Toolbox for Seismology

By M. Beyreuther, Robert Barsch, Lion Krischer, T. Megies, Y. Behr, Joachim Wassermann. 2010

1,570 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Geophysics

View Paper: https://www.semanticscholar.org/paper/d17e93a483c744fed6c7d98bdd48ed6f63b952a3

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Citations in the corpus

On the Broadband Instrument Response of Fiber‐Optic DAS Arrays (2019, neutral): “1 of 16 (Beyreuther et al., 2010).”
PhaseNet: A Deep-Neural-Network-Based Seismic Arrival Time Picking Method (2018, result): “We have applied both basic STA/LTA in Obspy and our PhaseNet method on this sequence.”
AxiSEM: broadband 3-D seismic wavefields in axisymmetric media (2014, methodology): “of record sections, gnuplot for creating seismogram image files, Google Earth for visualization of source–receiver geometries and seismograms on the sphere, and python wrappers for streamlined input/output and linkage to ObsPy (Beyreuther et al., 2010).”
PLACE (2015, methodology): “26 ObsPy is used to define and save header information (metadata), store data in a list-like object known as a stream, 27 and append data to a file dynamically.”
Machine learning for data-driven discovery in solid Earth geoscience (2019, methodology): “…reproducibility of results from more-difficult-to-interpret, “ black-box ” MLmodels such as DNNs. Open source codes, often shared through on-line platforms ( 123 , 124 ), have already been adopted for general data processing in seismol-ogy with the ObsPy ( 125 , 126 ) and Pyrocko ( 127 ) toolboxes.”
ObsPy: a bridge for seismology into the scientific Python ecosystem (2015, background): “ObsPy [2] provides read and write support for essentially all file formats commonly distributed within the seismological community superseding an abundance of file format converters.”
Global adjoint tomography—model GLAD-M25 (2020, methodology): “(i) Signal processing to remove the instrument response from observed data to recover ground displacement using ObsPy (Beyreuther et al. 2010).”
Seismic Signal Denoising and Decomposition Using Deep Neural Networks (2018, background): “waveform of “EHZ” channel in obspy [62], which is recorded at station RTSH of the BayernNetz (BW) Network in Germany.”
STanford EArthquake Dataset (STEAD): A Global Data Set of Seismic Signals for AI (2019, methodology): “We used the database of metadata to request the associated waveforms from continuous time-series archived at the IRIS data management center [22], [23].”