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![Comparison between the DMLoc catalog (132 events) and the <span class="search-highlight">SeisComP3</span> catalog...]()
![(a) Frequency‐magnitude distributions for events reported in the <span class="search-highlight">SeisComP3</span>’...]()
![Performance of easyQuake relative to the real‐time <span class="search-highlight">SeisComP3</span> (SC3) system a...]()
![Screenshot of the <span class="search-highlight">SeisComP3</span> module SCESV which presents the automatic proce...]()
![Distribution of earthquakes by M L used in this study. M L is the def...]()
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![Flow diagram of earthquake monitoring system. IRIS, Incorporated Research I...]()
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![Blind zone for the four selected events for a six‐station configuration. Co...]()
![Comparison between (a) the earthquake locations detected in this study, (b)...]()
![Comparison of the seismicity (a,b) detected and (c) located by the differen...]()
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![Schematic diagram of scisola’s architecture scheme. Arrows depict the links...]()
![Data flow of the automatic data processing for earthquake detection (blue) ...]()
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1-20 OF 149 RESULTS FOR
SeisComp3
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1
Journal Article
SC2SEI: Exporting SeisComP3 Data to SEISAN
Journal: Seismological Research Letters
Publisher: Seismological Society of America
Published: 03 October 2018
Seismological Research Letters (2018) 89 (6): 2386–2391.
...Terje Utheim; Jens Havskov; Mustafa Çomoğlu ABSTRACT The SeisComP3 (SC3) real‐time software is widely used in the seismological community. It provides automatic hypocenter and magnitude solutions, but with limited manual processing capabilities. The SEISAN software is also well known and provides...
FIGURES
Journal Article
The Virtual Seismologist in SeisComP3: A New Implementation Strategy for Earthquake Early Warning Algorithms
Journal: Seismological Research Letters
Publisher: Seismological Society of America
Published: 01 March 2016
Seismological Research Letters (2016) 87 (2A): 363–373.
... in California since 2008, we demonstrate how our approach can be realized within the widely used monitoring platform SeisComP3. Because this software suite is already in production at many seismic networks worldwide, we have been able to test the new VS implementation across a wide variety of tectonic settings...
FIGURES
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Includes: Supplemental Content
Journal Article
Scisola: Automatic Moment Tensor Solution for SeisComP3
Journal: Seismological Research Letters
Publisher: Seismological Society of America
Published: 02 December 2015
Seismological Research Letters (2016) 87 (1): 157–163.
... present scisola, a new software for automatic moment tensor ( MT ) retrieval, based on the ISOLated Asperities ( ISOLA ) MT inversion code and SeisComP3 real‐time processing system. Scisola connects SeisComP3 with the ISOLA FORTRAN codes by retrieving event, station, waveform, and instrumental response...
FIGURES
Includes: Supplemental Content
Journal Article
An Almost Fair Comparison Between Earthworm and SeisComp3
Journal: Seismological Research Letters
Publisher: Seismological Society of America
Published: 01 September 2012
Seismological Research Letters (2012) 83 (5): 833.
Journal Article
An Almost Fair Comparison Between Earthworm and SeisComp3
Journal: Seismological Research Letters
Publisher: Seismological Society of America
Published: 01 July 2012
Seismological Research Letters (2012) 83 (4): 720–727.
..., we compare two of the leading cost-free options: Earthworm and SeisComP3. This opinion paper is intended to aid network seismologists who need to select or migrate to a new monitoring system for earthquake surveillance. We do not pretend to have the definitive answer to this complex decision. Indeed...
Image
Comparison between the DMLoc catalog (132 events) and the SeisComP3 catalog...
in DMLoc: Automatic Microseismic Locating Workflow Based on Deep Learning and Waveform Migration
> Seismological Research Letters
Published: 13 May 2024
Figure 4. Comparison between the DMLoc catalog (132 events) and the SeisComP3 catalog (92 events) for 6 January 2019, within the Dawson‐Septimus area. The small inset map shows the location of the study area (red point). The color version of this figure is available only in the electronic edition.
Image
(a) Frequency‐magnitude distributions for events reported in the SeisComP3’...
in Combining Deep Learning and the Source‐Scanning Algorithm for Improved Seismic Monitoring
> Bulletin of the Seismological Society of America
Published: 23 June 2022
Figure 13. (a) Frequency‐magnitude distributions for events reported in the SeisComP3’s catalog (white triangles), Geological Survey of Canada (GSC)’s catalog (blue circles), and this study (red squares) for February 2021 within northeastern British Columbia (NE BC). (b) Temporal distributions
Image
Performance of easyQuake relative to the real‐time SeisComP3 (SC3) system a...
in easyQuake: Putting Machine Learning to Work for Your Regional Seismic Network or Local Earthquake Study
> Seismological Research Letters
Published: 04 November 2020
Figure 2. Performance of easyQuake relative to the real‐time SeisComP3 (SC3) system at Oklahoma Geological Survey (OGS). (a) Earthquake magnitudes with time, since we started running easyQuake nightly to augment the real‐time SC3 detection. Black circles identify earthquakes detected by easyQuake
Image
Screenshot of the SeisComP3 module SCESV which presents the automatic proce...
in Toward an Earthquake and Tsunami Monitoring and Early Warning System for Nicaragua and Central America
> Seismological Research Letters
Published: 14 February 2018
Figure 3. Screenshot of the SeisComP3 module SCESV which presents the automatic processing result for the magnitude 8.2 earthquake in Chiapas/Mexico on 8 September 2017, obtained only with Central American stations. Meanwhile the epicenter coincides well with the results obtained by international
Image
Distribution of earthquakes by M L used in this study. M L is the def...
in A Revised Local Magnitude ( M L ) Scale for New Zealand Earthquakes
> Bulletin of the Seismological Society of America
Published: 22 March 2016
Figure 2. Distribution of earthquakes by M L used in this study. M L is the default M L calculated by SeisComP3 (SC3).
Journal Article
Calibration of the Local Magnitude Scale for Hungary
Publisher: Seismological Society of America
Published: 24 December 2024
Bulletin of the Seismological Society of America (2025) 115 (1): 163–173.
... not differ substantially in magnitude from those computed with the SeisComp3 software’s scale currently used in Hungary. However, the main improvement of the new scale is the reduction in variance between station magnitudes by 56.3%, using attenuation coefficients and station corrections. We suggest the use...
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Image
Flow diagram of earthquake monitoring system. IRIS, Incorporated Research I...
Published: 13 November 2019
Figure 5. Flow diagram of earthquake monitoring system. IRIS, Incorporated Research Institutions for Seismology; REST API, Representational State Transfer Application Program Interface; RTPD, REF TEK Protocol Daemon; Sc3, SeisComP3.
Journal Article
A Wrapper to Use a Machine‐Learning‐Based Algorithm for Earthquake Monitoring
Journal: Seismological Research Letters
Publisher: Seismological Society of America
Published: 16 February 2022
Seismological Research Letters (2022) 93 (3): 1673–1682.
... the Earthworm binder_ew associator module to use the phase identification from PhaseNet to detect and locate the events, which we archive in a SeisComP3 database. We assessed the performance of the algorithm by comparing the results with existing catalogs built to monitor seismic and volcanic activity...
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Image
Blind zone for the four selected events for a six‐station configuration. Co...
in A Regional Approach for Earthquake Early Warning in South West Iberia: A Feasibility Study
> Bulletin of the Seismological Society of America
Published: 24 March 2015
Figure 3. Blind zone for the four selected events for a six‐station configuration. Column (a) Earthworm, (b) SeisComP3, (c) PRobabilistic and Evolutionary early warning SysTem (PRESTo), and (d) estimated blind zone for the referenced IGN hypocenter.
Image
Comparison between (a) the earthquake locations detected in this study, (b)...
in Combining Deep Learning and the Source‐Scanning Algorithm for Improved Seismic Monitoring
> Bulletin of the Seismological Society of America
Published: 23 June 2022
Figure 14. Comparison between (a) the earthquake locations detected in this study, (b) earthquake locations detected in this study after relocation, (c) seismic events reported in the GSC’s catalog, and (d) SeisComP3’s catalog for February 2021 within NE BC. The color version of this figure
Image
Comparison of the seismicity (a,b) detected and (c) located by the differen...
in A Wrapper to Use a Machine‐Learning‐Based Algorithm for Earthquake Monitoring
> Seismological Research Letters
Published: 16 February 2022
Figure 3. Comparison of the seismicity (a,b) detected and (c) located by the different methods between December 2020 and January 2021. Daily histograms obtained with SeisComP3, PhaseWorm, and the manual identifications for the (a) volcano‐tectonic (VT) and (b) long‐period (LP) events. The color
Journal Article
A Regional Approach for Earthquake Early Warning in South West Iberia: A Feasibility Study
Publisher: Seismological Society of America
Published: 24 March 2015
Bulletin of the Seismological Society of America (2015) 105 (2A): 560–567.
...Figure 3. Blind zone for the four selected events for a six‐station configuration. Column (a) Earthworm, (b) SeisComP3, (c) PRobabilistic and Evolutionary early warning SysTem (PRESTo), and (d) estimated blind zone for the referenced IGN hypocenter. ...
FIGURES
Image
Schematic diagram of scisola’s architecture scheme. Arrows depict the links...
Published: 02 December 2015
Figure 1. Schematic diagram of scisola’s architecture scheme. Arrows depict the links of scisola to SeisComP3, ISOLated Asperities ( ISOLA ) codes, and MySQL/PostgreSQL database through the subprocess and the MySQLdb and psycopg2 Python packages, respectively.The color version of this figure
Image
Data flow of the automatic data processing for earthquake detection (blue) ...
Published: 17 February 2021
Figure 7. Data flow of the automatic data processing for earthquake detection (blue) and location and magnitude determination (orange). The workflow relies on SeisComp3 (top), Seisan (bottom), and routines developed in‐house. STA/LTA, short‐term average/long‐term average. The color version
Journal Article
DMLoc: Automatic Microseismic Locating Workflow Based on Deep Learning and Waveform Migration
Journal: Seismological Research Letters
Publisher: Seismological Society of America
Published: 13 May 2024
Seismological Research Letters (2024) 95 (5): 2997–3007.
...Figure 4. Comparison between the DMLoc catalog (132 events) and the SeisComP3 catalog (92 events) for 6 January 2019, within the Dawson‐Septimus area. The small inset map shows the location of the study area (red point). The color version of this figure is available only in the electronic edition. ...
FIGURES
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Includes: Supplemental Content
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