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MSNoise

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Journal Article
Published: 01 May 2014
Seismological Research Letters (2014) 85 (3): 715–726.
...‐level helper functions in order to be pluggable and extensible. Finally, it must produce exportable data, either in waveform format, tabular text files, or high‐quality figures. This is the purpose of Monitoring using Seismic Noise (i.e., MSNoise). We do not want to provide another black box...
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Schematic view of the <b>MSNoise</b> workflow, the one‐time installation part ente...
Published: 01 May 2014
Figure 1. Schematic view of the MSNoise workflow, the one‐time installation part enters the routine workflow before the job definition step.
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Comparison of the detrended  δv &#x2F; v  results obtained using <b>MSNoise</b> for fiv...
Published: 01 May 2014
Figure 8. Comparison of the detrended δv / v results obtained using MSNoise for five different moving‐window stacks (1, 2, 5, 10, and 30 days) without forcing the slope estimate to cross the origin (equation 10) in the δt / t estimation process. Eruptions of the Piton de la Fournaise
Journal Article
Published: 01 April 2020
Seismological Research Letters (2020) 91 (3): 1853–1866.
... for embarrassingly parallel problems. NoisePy also uses a small memory overhead and stable memory usage. Benchmark comparisons with the latest version of MSNoise demonstrate about four‐time improvement in compute time of the cross correlations, which is the slowest step of ambient‐noise seismology. NoisePy...
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Journal Article
Journal: The Leading Edge
Published: 01 December 2017
The Leading Edge (2017) 36 (12): 1009–1017.
... package MSNoise was used to compute crosscorrelations and measure changes in velocity between each time period relative to the initial (prestimulation) time period. The majority of channel pairs showed a velocity reduction (average −3% relative velocity change) following both stimulations. We used a 3D...
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(a) NoisePy performance on computing cross‐correlation functions and (b) be...
Published: 01 April 2020
Figure 6. (a) NoisePy performance on computing cross‐correlation functions and (b) benchmark with MSNoise. (a) Strong scaling of NoisePy, such that the compute time is inversely proportional to the number of cores with a slope close to − 1 . In the benchmark, NoisePy and MSNoise process
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Example delay, error, phase coherence, data selection, and delay time varia...
Published: 01 May 2014
is the central time lag of the moving windows in the MWCS process. Each matrix has its own color scale. The bottom line of the matrices is the filtered column weighted average (see text for details) and is called “ALL” within MSNoise. The “ALL” line is only calculated between ‐left_maxlag:‐left_minlag
Journal Article
Published: 11 December 2018
Bulletin of the Seismological Society of America (2019) 109 (1): 424–432.
... . Laske G. 1995 . Global observation of off‐great‐circle propagation of long‐period surface waves , Geophys. J. Int. 123 , no.  1 , 245 – 259 . Lecocq T. Caudron C. , and Brenguier F. 2014 . MSNoise, a Python package for monitoring seismic velocity changes using ambient...
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Journal Article
Published: 01 September 2017
South African Journal of Geology (2017) 120 (3): 341–350.
...), tomographic inversion, and error analysis (resolution testing). The first 3 steps are discussed at length by Bensen et al. (2007) , and were done using the MSNoise software ( Lecocq et al. 2014 ). The next 3 steps were done using MSNoise-TOMO. For all stations (ArrayA and ArrayB) the raw waveforms...
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Journal Article
Published: 01 May 2019
Seismological Research Letters (2019) 90 (4): 1663–1669.
..., and correlation and denoising operations are done per station pair. ObsPy ( Krischer et al. , 2015 ) and MSNoise ( Lecocq et al. , 2014 ) are open‐source packages for Python that are excellent for proof‐of‐concept studies and often sufficient for preprocessing. Compiled programming language solutions using...
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Journal Article
Published: 26 September 2018
Seismological Research Letters (2018) 89 (6): 2413–2419.
.... Bozda E. , and Tromp J. 2016 . An adaptable seismic data format , Geophys. J. Int. 207 , no.  2 , 1003 – 1011 . Lecocq T. Caudron C. , and Brenguier F. 2014 . MSNoise, a Python package for monitoring seismic velocity changes using ambient seismic noise , Seismol. Res...
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Journal Article
Published: 31 May 2017
Seismological Research Letters (2017) 88 (4): 1141–1145.
... using the high‐level programming language Python; for example, Whisper ( Briand et al. , 2013 ) and MSNoise ( Lecocq et al. , 2014 ). Although Python eases development and is therefore suitable for working on new seismological concepts, a compiled language is clearly more suitable to harness...
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Journal Article
Published: 01 July 2014
Seismological Research Letters (2014) 85 (4): 905–911.
... to data acquisition tools like ObsPyLoad and wavesdownloader ( Bernardi and Michelini, 2013 ) and analysis tools like ObsPy ( Beyreuther et al. , 2010 ; Megies et al. , 2011 ), AIMBAT ( Lou et al. , 2013 ), MSNoise and pyTDMT (see Data and Resources ), and the SciPy Stack (e.g., Jones et al. , 2001...
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Journal Article
Published: 19 November 2019
Bulletin of the Seismological Society of America (2020) 110 (1): 110–126.
.... , 2018 , for information on the large‐ N deployment). For the ambient noise study, 51 station pairs are used, with 36 pairs from the UNR network and 15 pairs from the SPE backbone network (Fig.  2 ). We used the MSNoise software package ( Lecocq et al. , 2014 ) to process the ambient noise data set...
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Journal Article
Published: 16 June 2020
Bulletin of the Seismological Society of America (2020) 110 (5): 2541–2558.
... International Federation of Digital Seismograph Networks (FDSN) standardized webservices at KNMI: http://rdsa.knmi.nl/fdsnws/dataselect/1 . Groundwater table information for St. Eustatius was retrieved from https://library.wur.nl/WebQuery/theses/directlink/2094045 . Processing of data was done by MSNoise...
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Journal Article
Journal: The Leading Edge
Published: 01 April 2017
The Leading Edge (2017) 36 (4): 350a1–350a6.
... time in correlations : Geophysics , 75 , no. 5 , SA85 – SA93 , 10.1190/1.3483102 . Lecocq T. , Caudron C. , and Brenguier F. , 2014 , MSNoise, a python package for monitoring seismic velocity changes using ambient seismic noise : Seismological Research Letters , 85...
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Journal Article
Journal: Interpretation
Published: 15 July 2016
Interpretation (2016) 4 (3): SJ77–SJ85.
.... Brenguier , 2014 , MSNoise, a Python package for monitoring seismic velocity changes using ambient seismic noise : Seismological Research Letters , 85 , 715 – 726 , doi: 10.1785/0220130073 . SRLEEG 0895-0695 Lobkis , O. , and R. Weaver , 2001 , On the emergence of the Green’s...
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Journal Article
Published: 02 October 2019
Seismological Research Letters (2019) 90 (6): 2154–2164.
... structure as inferred from correlation analyses of ambient noise during volcano deformation at Izu‐Oshima, Japan , J. Geophys. Res. 122 , doi: 10.1002/2017JB014340 Thomas L. Caudron C. , and Brenguier F. 2014 . MSNoise, a Python Package for monitoring seismic velocity changes using...
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Journal Article
Published: 30 September 2020
Seismological Research Letters (2021) 92 (1): 517–527.
.... 2012 . ImageNet classification with deep convolutional neural networks , Adv. Neural Inf.. Process. Syst. 25 , 1097 – 1105 . Lecocq T. Caudron C. , and Brenguier F. 2014 . MSNoise, a Python package for monitoring seismic velocity changes using ambient seismic noise , Seismol...
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Journal Article
Published: 07 August 2018
Bulletin of the Seismological Society of America (2018) 108 (5A): 2565–2579.
.... Caudron C. , and Brenguier F. 2014 . MSNoise, a python package for monitoring seismic velocity changes using ambient seismic noise , Seismol. Res. Lett. 85 , no.  3 , 715 – 726 . Lewis M. A. , and Ben‐Zion Y. 2010 . Diversity of fault zone damage and trapping structures...
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