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  • 1
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    Which picker fits my data? A quantitative evaluation of deep learning based seismic pickers (2021)
    arXiv
    In:  (Submitted) arXiv e-prints .
    Details
    Publication Date: 2021-11-24
    Description: Seismic event detection and phase picking are the base of many seismological workflows. In recent years, several publications demonstrated that deep learning approaches significantly outperform classical approaches and even achieve human-like performance under certain circumstances. However, as most studies differ in the datasets and exact evaluation tasks studied, it is yet unclear how the different approaches compare to each other. Furthermore, there are no systematic studies how the models perform in a cross-domain scenario, i.e., when applied to data with different characteristics. Here, we address these questions by conducting a large-scale benchmark study. We compare six previously published deep learning models on eight datasets covering local to teleseismic distances and on three tasks: event detection, phase identification and onset time picking. Furthermore, we compare the results to a classical Baer-Kradolfer picker. Overall, we observe the best performance for EQTransformer, GPD and PhaseNet, with EQTransformer having a small advantage for teleseismic data. Furthermore, we conduct a cross-domain study, in which we analyze model performance on datasets they were not trained on. We show that trained models can be transferred between regions with only mild performance degradation, but not from regional to teleseismic data or vice versa. As deep learning for detection and picking is a rapidly evolving field, we ensured extensibility of our benchmark by building our code on standardized frameworks and making it openly accessible. This allows model developers to easily compare new models or evaluate performance on new datasets, beyond those presented here. Furthermore, we make all trained models available through the SeisBench framework, giving end-users an easy way to apply these models in seismological analysis.
    Type: Article , NonPeerReviewed
    Format: text
    Location Call Number Limitation Availability
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    OceanRep: Article in a Scientific Journal - without review
  • 2
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    SeisBench - A Toolbox for Machine Learning in Seismology (2021)
    arXiv
    In:  (Submitted) arXiv e-prints .
    Details
    Publication Date: 2021-11-23
    Description: Machine Learning (ML) methods have seen widespread adoption in seismology in recent years. The abilityof these techniques to efficiently infer the statistical properties of large datasets often provides significantimprovements over traditional techniques when the number of data are large(»millions of examples). Withthe entire spectrum of seismological tasks, e.g., seismic picking and detection, magnitude and source propertyestimation, ground motion prediction, hypocentre determination; among others, now incorporating ML ap-proaches, numerous models are emerging as these techniques are further adopted within seismology. To evaluatethese algorithms, quality controlled benchmark datasets that contain representative class distributions are vital.In addition to this, models require implementation through a common framework to facilitate comparison.Accessing these various benchmark datasets for training and implementing the standardization of models iscurrently a time-consuming process, hindering further advancement of ML techniques within seismology. Thesedevelopment bottlenecks also affect ’practitioners’ seeking to deploy the latest models on seismic data, withouthaving to necessarily learn entirely new ML frameworks to perform this task. We present SeisBench as a soft-ware package to tackle these issues. SeisBench is an open-source framework for deploying ML in seismology.SeisBench standardises access to both models and datasets, whilst also providing a range of common processingand data augmentation operations through the API. Through SeisBench, users can access several seismologicalML models and benchmark datasets available in the literature via a single interface. SeisBench is built to beextensible, with community involvement encouraged to expand the package. Having such frameworks availablefor accessing leading ML models forms an essential tool for seismologists seeking to iterate and apply the nextgeneration of ML techniques to seismic data.
    Type: Article , NonPeerReviewed
    Format: text
    Location Call Number Limitation Availability
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    OceanRep: Article in a Scientific Journal - without review
  • 3
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    Which picker fits my data? A quantitative evaluation of deep learning based seismic pickers (2022)
    AGU (American Geophysical Union) | Wiley
    Details
    Publication Date: 2024-02-07
    Description: Seismic event detection and phase picking are the base of many seismological workflows. In recent years, several publications demonstrated that deep learning approaches significantly outperform classical approaches and even achieve human-like performance under certain circumstances. However, as most studies differ in the datasets and exact evaluation tasks studied, it is yet unclear how the different approaches compare to each other. Furthermore, there are no systematic studies how the models perform in a cross-domain scenario, i.e., when applied to data with different characteristics. Here, we address these questions by conducting a large-scale benchmark study. We compare six previously published deep learning models on eight datasets covering local to teleseismic distances and on three tasks: event detection, phase identification and onset time picking. Furthermore, we compare the results to a classical Baer-Kradolfer picker. Overall, we observe the best performance for EQTransformer, GPD and PhaseNet, with EQTransformer having a small advantage for teleseismic data. Furthermore, we conduct a cross-domain study, in which we analyze model performance on datasets they were not trained on. We show that trained models can be transferred between regions with only mild performance degradation, but not from regional to teleseismic data or vice versa. As deep learning for detection and picking is a rapidly evolving field, we ensured extensibility of our benchmark by building our code on standardized frameworks and making it openly accessible. This allows model developers to easily compare new models or evaluate performance on new datasets, beyond those presented here. Furthermore, we make all trained models available through the SeisBench framework, giving end-users an easy way to apply these models in seismological analysis.
    Type: Article , PeerReviewed
    Format: text
    Location Call Number Limitation Availability
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 4
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    SeisBench - A Toolbox for Machine Learning in Seismology (2022)
    SSA (Seismological Society of America)
    Details
    Publication Date: 2024-02-07
    Description: Machine‐learning (ML) methods have seen widespread adoption in seismology in recent years. The ability of these techniques to efficiently infer the statistical properties of large datasets often provides significant improvements over traditional techniques when the number of data are large (millions of examples). With the entire spectrum of seismological tasks, for example, seismic picking and detection, magnitude and source property estimation, ground‐motion prediction, hypocenter determination, among others, now incorporating ML approaches, numerous models are emerging as these techniques are further adopted within seismology. To evaluate these algorithms, quality‐controlled benchmark datasets that contain representative class distributions are vital. In addition to this, models require implementation through a common framework to facilitate comparison. Accessing these various benchmark datasets for training and implementing the standardization of models is currently a time‐consuming process, hindering further advancement of ML techniques within seismology. These development bottlenecks also affect “practitioners” seeking to deploy the latest models on seismic data, without having to necessarily learn entirely new ML frameworks to perform this task. We present SeisBench as a software package to tackle these issues. SeisBench is an open‐source framework for deploying ML in seismology—available via GitHub. SeisBench standardizes access to both models and datasets, while also providing a range of common processing and data augmentation operations through the API. Through SeisBench, users can access several seismological ML models and benchmark datasets available in the literature via a single interface. SeisBench is built to be extensible, with community involvement encouraged to expand the package. Having such frameworks available for accessing leading ML models forms an essential tool for seismologists seeking to iterate and apply the next generation of ML techniques to seismic data.
    Type: Article , PeerReviewed
    Format: text
    Format: text
    Location Call Number Limitation Availability
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    OceanRep: Article in a Scientific Journal - peer-reviewed
  • 5
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    Earthquakes in Switzerland and surrounding regions during 2015 and 2016 (2019)
    Details
    Publication Date: 2020-12-07
    Description: This report summarizes the seismicity in Switzerland and surrounding regions in the years 2015 and 2016. In 2015, the Swiss Seismological Service detected and located 735 earthquakes in the region under consideration. With a total of 20 earthquakes of magnitude ML C 2.5, the seismic activity of potentially felt events in 2015 was close to the average of 23 earthquakes over the previous 40 years. Seismic activity was above average in 2016 with 872 located earthquakes of which 31 events had ML C 2.5. The strongest event in the analyzed period was the ML 4.1 Salgesch earthquake, which occurred northeast of Sierre (VS) in October 2016. The event was felt in large parts of Switzerland and had a maximum intensity of V. Derived focal mechanisms and relative hypocenter relocations of aftershocks image a SSE dipping reverse fault, which likely also hosted an ML 3.9 earthquake in 2003. Another remarkable earthquake sequence in the Valais occurred close to Sion with four felt events (ML 2.7–3.2) in 2015/16. We associate this sequence with a system of WNW-ESE striking fault segments north of the Rhoˆne valley. Similarities with a sequence in 2011, which was located about 10 km to the NE, suggest the existence of an en-echelon system of basement faults accommodating dextral slip along the Rhoˆne-Simplon line in this area. Another exceptional earthquake sequence occurred close to Singen (Germany) in November 2016. Relocated hypocenters and focal mechanisms image a SW dipping transtensional fault segment, which is likely associated with a branch of the Hegau-Bodensee Graben. On the western boundary of this graben, micro-earthquakes close to Schlattingen (TG) in 2015/16 are possibly related to a NE dipping branch of the Neuhausen Fault. Other cases of earthquakes felt by the public during 2015/16 include earthquakes in the region of Biel, Vallorcine, Solothurn, and Savognin.
    Description: SwissEnergy (http:// www.energieschweiz.ch) and the Swiss Federal Office of Energy for the financial support of project GEOBEST-CH; Swiss Competence Center for Energy Research—Supply of Electricity (http://www.sccer-soe.ch); Swiss-AlpArray SINERGIA project CRSII2_154434/1 by the Swiss National Science Foundation (SNSF)
    Description: Published
    Description: 221–244
    Description: 2T. Sorgente Sismica
    Description: 1IT. Reti di monitoraggio
    Description: 5IT. Osservatori
    Description: JCR Journal
    Keywords: Seismicity ; Magnitude of completeness ; Focal mechanisms ; Seismotectonics ; Rhone-Simplon line ; Hegau-Bodensee graben ; Basel ; Aar massif ; 04. Solid Earth ; 04.06. Seismology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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    PAPER (OA)
  • 6
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    EPOS Seismology services and their users (2018)
    European Geosciences Union (EGU)
    Details
    Publication Date: 2020-12-15
    Description: The construction of seismological community services for the European Plate Observing System Research Infrastructure (EPOS) is by now well under way. A significant number of services are already operational, largely based on those existing at established institutions or collaborations like ORFEUS, EMSC, AHEAD and EFEHR, and more are being added to be ready for internal validation by late 2017. In this presentation we focus on a number of issues related to the interaction of the community of users with the services provided by the seismological part of the EPOS research infrastructure. How users interact with a service (and how satisfied they are with this interaction) is viewed as one important component of the validation of a service within EPOS, and certainly is key to the uptake of a service and from that also it’s attributed value. Within EPOS Seismology, the following aspects of user interaction have already surfaced: a) User identification (and potential tracking) versus ease-of-access and openness Requesting users to identify themselves when accessing a service provides various advantages to providers and users (e.g. quantifying & qualifying the service use, customization of services and interfaces, handling access rights and quotas), but may impact the ease of access and also shy away users who don’t wish to be identified for whatever reason. b) Service availability versus cost There is a clear and prominent connection between the availability of a service, both regarding uptime and capacity, and its operational cost (IT systems and personnel), and it is often not clear where to draw the line (and based on which considerations). In connection to that, how to best utilize third-party IT infrastructures (either commercial or public), and what the long-term cost implications of that might be, is equally open. c) Licensing and attribution The issue of intellectual property and associated licensing policies for data, products and services is only recently gaining more attention in the community. Whether at all, and if yes then how to license, is still diversely discussed, while on national level more and more legislative requirements create boundary conditions that need to be respected. Attribution (of service use and of data/product origin) is only one related aspect, but of high importance the scientific world. In EPOS Seismology we attempt to find common approaches to address the above issues, also closely co-ordinated to the developments across the other EPOS domains. In this presentation we discuss the current strategies, potential solutions identified, and remaining open questions.
    Description: H2020 Project EPOS-IP, Cordis Project ID 676564
    Description: Published
    Description: Vienna, Austria
    Description: 4T. Sismologia, geofisica e geologia per l'ingegneria sismica
    Description: 4IT. Banche dati
    Keywords: seismology ; data dissemination ; 04. Solid Earth ; 04.06. Seismology ; 05.02. Data dissemination
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: Abstract
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  • 7
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    Earthquakes in Switzerland and surrounding regions during 2017 and 2018 (2021)
    Springer
    Details
    Publication Date: 2021-02-12
    Description: This report summarizes the seismicity in Switzerland and surrounding regions in the years 2017 and 2018. In 2017 and 2018, the Swiss Seismological Service detected and located 1227 and 955 earthquakes in the region under considera- tion, respectively. The strongest event in the analysed period was the ML 4.6 Urnerboden earthquake, which occurred in the border region of cantons Uri, Glarus and Schwyz on March 6, 2017. The event was the strongest earthquake within Switzerland since the ML 5.0 Vaz earthquake of 1991. Associated ground motions indicating intensity IV were reported in a radius up to about 50 km and locally approached intensity VI in the region close to the epicentre. Derived focal mechanisms and relative hypocentre relocations of the immediate aftershocks image a NNW–SSE striking sinistral strike-slip fault. Together with other past events in this region, the Urnerboden earthquake suggests the existence of a system of sub-parallel strike-slip faults, likely within in the uppermost crystalline basement of the eastern Aar Massif. A vigorous earthquake sequence occurred close to Château-d’Oex in the Préalpes-Romandes region in western Switzer- land. With a magnitude of ML 4.3, the strongest earthquake of the sequence occurred on July 1, 2017. Focal mechanism and relative relocations of fore- and aftershocks image a NNE dipping normal fault in about 4 km depth. Two similarly oriented shallow normal-fault events occurred between subalpine Molasse and Préalpes units close to Châtel-St-Denis and St. Silvester in 2017/18. Together, these events indicate a domain of NE–SW oriented extensional to transtensional deformation along the Alpine Front between Lake Geneva in the west and the Fribourg Fault in the east. The structural complexity of the Fribourg Fault is revealed by an ML 2.9 earthquake near Tafers in 2018. The event images a NW–SE striking fault segment within the crystalline basement, which might be related to the Fribourg Fault Zone. Finally, the ML 2.8 Grenchen earthquake of 2017 provides a rare example of shallow thrust faulting along the Jura fold-and-thrust belt, indicating contraction in the northwestern Alpine foreland of Switzerland.
    Description: Published
    Description: id 4
    Description: 4T. Sismicità dell'Italia
    Description: JCR Journal
    Keywords: Seismicity ; Focal mechanisms ; Seismotectonics ; Urnerboden ; Aar Massif ; Château-d’oex ; Préalpes ; Fribourg ; Jura fold-and-thrust belt ; 04.06. Seismology
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: article
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  • 8
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    D13.1 QUESTIONNAIRE TO ANALYSE THE ETHICAL AND SOCIAL ISSUES AND ASSESSMENT REPORT ON QUESTIONNAIRE ANSWERS (2018)
    Details
    Publication Date: 2018-03-01
    Description: This deliverable refers to the questionnaire implemented by WP13, addressed to all participating organizations in ENVRIplus, to investigate to what extent each RI involved in the project is aware of, and takes into consideration, ethical issues in relation to its scientific activities. The questionnaire, entitled “what do you know about ethics in geosciences?”, was developed following the collection and analysis of materials concerning ethical aspects already existing within scientific organizations and institutions all over the world (ethical codes, definitions, statements relative to ethics in the research activities). These documents consider different aspects of ethics, both theoretical and practical, which were then incorporated into our questionnaire. In particular these are: • principles of research integrity and professional ethics; • aspects related to the impact on the environment that research activity may have; • aspects related to the repercussions of the research activities on the different categories of society (such as citizens, decision makers, politicians, local authorities, professionals, etc.), which are the end-users of the research activity and are interested in scientific data and results in different ways, on different levels, with different purposes. The results of this questionnaire have been analyzed to identify common issues, recurring problems, aspects related to the stakeholders, to the data management, and to the societal impacts of the scientific activity. Moreover, the individual perception of ethical implications of the research activity for single participants in the project has been evaluated.
    Description: ENVRIplus: Horizon 2020 project bringing together Environmental and Earth System Research Infrastructures
    Description: Published
    Description: 1TM. Formazione
    Description: 3TM. Comunicazione
    Description: 1VV. Altro
    Keywords: questionnaire ; ethics ; social issues ; geosciences ; 05.03. Educational, History of Science, Public Issues ; 05.09. Miscellaneous
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: report
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  • 9
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    D13.2 Ethical Label Template (2019)
    Details
    Publication Date: 2019-06-10
    Description: The results of the survey through the online questionnaire “what do you know about ethics in geosciences?” described in the Deliverable 13.1 (http://www.envriplus.eu/wpcontent/uploads/2015/08/D13.1.pdf) has clearly shown the general recognition by interviewees on the importance of ethical and social aspects involved in own research and technological activities, but at the same time identified a general lack of awareness on what this concretely means. In addition, even if problems related to internal dynamics of the research working environment seem to be known or at least perceived, what one's own work can mean for the benefit of society seems not so clear, and ethical and social implications related to activities are perceived as quite difficult to be analyzed. ENVRIplus is aimed at providing shared solutions for science and society. The questionnaire developed not only helped to learn more about ethical matters with respect to scientific work, but also raised with its distribution recipients’ (ENVRIplus project participants) awareness for ethical and societal aspects of their research activities. The Ethical Label aims to continue these efforts by supporting researchers to clarify the potential ethical, societal, and scientific impact of their activities. Moreover, filling the Ethical Label can constitute a useful internal project training on developing a critical thinking in ethics in science and in science-society interactions. The Ethical provides information about the ethical, social and environmental implications and impact of a deliverable or other project results, thereby adding value to the usual technical-scientific focused description of any project outcome. The Ethical Label represents a schematic and simplified information, in tabular form, as a support of the introductory part of every outcome of the project, which orients the end-user to better identify concepts and aspects that describe the function of that product, with particular reference to its impact on the scientific community, society and the environment.
    Description: ENVRIplus project - www.envri.eu/envriplus
    Description: Published
    Description: 3TM. Comunicazione
    Keywords: ethics ; label ; geoethics ; end-users ; stakeholders ; 05.03. Educational, History of Science, Public Issues ; 05.09. Miscellaneous
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: report
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  • 10
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    D13.3 Ethical Guidelines for Research Infrastructures (2019)
    Details
    Publication Date: 2019-06-10
    Description: This deliverable refers to the “Ethical Guidelines” (EGs) for Research Infrastructures (RIs) developed and implemented by WP13. The EGs present a general framework of ethical values, to be used by each research infrastructure of the ENVRI community. They are a basis to design or to shape individual ethical guidelines taking into account RIs’ peculiarities with respect to their status, duties, activities, and goals. The EGs are structured in a main section, explaining general ethical values, and a subordinate section, where some delicate matters of interest for RIs are discussed from an ethical perspective. Ethical values included in the EGs refer to four ethical domains, affecting RI’s as a whole as well as individual scientists working at RIs. The domains mirror the ethical profile of each scientist/technician/administrator, his/her relationships with colleagues and their working environment, the interaction with society, and their obligations towards the Earth system. In addition to these four domains, the EGs discuss several issues which are considered to have a particular importance for the RIs: working environment, data life cycle, conflicts of interest, and relationship with decision-makers. Their balance is indispensable for a respectful and caring work environment and are needed to ensure a fair reflection of the institutional activities and results towards society. The EGs are the result of an extensive survey of relevant literature produced by scientific and professional organizations, institutions, and bodies focusing on applied ethics for research and other professional activities conducted at RIs.
    Description: ENVRIplus project - www.envri.eu/envriplus
    Description: Published
    Description: 3TM. Comunicazione
    Keywords: ethics ; guidelines ; geoethics ; geoscientists ; research integrity ; ethical domains ; 05.03. Educational, History of Science, Public Issues ; 05.09. Miscellaneous
    Repository Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Type: report
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