Table of Contents
Overview
Definition of Seismology
Seismology is defined as the scientific study of earthquakes, their occurrence, and the propagation of seismic waves through the Earth's interior. This field of study has evolved significantly since its inception, with early investigations primarily focused on cataloging earthquake occurrences. One of the pioneers in this area was Irish engineer Robert Mallet, who not only compiled one of the earliest comprehensive catalogs of earthquakes but also coined the term "seismology" and developed an early design for an electromagnetic seismograph, which was later refined by Luigi Palmieri in Italy.[1.1] The discipline of seismology has since branched into two main areas: the determination of the Earth's internal structure based on the arrival times of seismic waves and the understanding of the mechanisms behind earthquakes and wave propagation.[1.1] Seismic waves, which are generated by various processes including earthquakes, volcanic activity, and human-induced activities such as mining, are analyzed to gain insights into the Earth's interior.[2.1] In addition to its fundamental scientific aspects, seismology has practical applications, particularly in engineering. Engineering seismology focuses on assessing the seismic hazard of specific sites or regions to inform earthquake engineering practices.[3.1] This application is crucial for ensuring the safety and resilience of structures in earthquake-prone areas. Overall, seismology encompasses both the theoretical study of seismic phenomena and its practical implications for society.[4.1]Importance of Seismology in Earth Sciences
Seismology plays a crucial role in Earth sciences by enhancing our understanding of seismic events and their implications for society. The integration of real-time seismic data into educational programs, such as those offered by the IRIS Education and Public Outreach (EPO) program, allows students to explore concepts like earthquakes and plate tectonics through engaging, real-world examples.[5.1] This hands-on approach is further exemplified by initiatives like Raspberry Shakes, which transform traditional earth science lessons into interactive experiences, enabling students to feel the effects of seismic activity.[6.1] Moreover, seismology provides valuable insights for urban planning and public safety. By incorporating seismological data, planners can identify high-risk areas and tailor emergency response strategies to address specific challenges posed by earthquakes.[9.1] The application of Geographic Information Systems (GIS) in urban planning enhances decision-making by offering a comprehensive view of a region's geographic and infrastructural distribution, which is essential for developing seismic-resistant infrastructure.[11.1] Additionally, retrofitting existing structures in high-risk areas is a proactive strategy that significantly reduces potential earthquake damage.[12.1] Advancements in technology, particularly in machine learning and remote sensing, have revolutionized the field of seismology. These innovations enable the detection of smaller seismic events and the creation of detailed 3D models of Earth's interior, thereby enhancing our understanding of seismic wave propagation and the Earth's dynamics.[14.1] Machine learning techniques, such as those used in automatic seismic event detection, streamline data processing and improve the identification of patterns that traditional methods may overlook.[17.1] Furthermore, understanding the differences between seismic wave types, such as P-waves and S-waves, is essential for assessing earthquake impacts. P-waves, which travel faster and can move through solids, liquids, and gases, typically cause less damage compared to S-waves, which are slower and can only travel through solids.[19.1] This knowledge is vital for developing effective earthquake preparedness and response strategies, underscoring the importance of seismology in safeguarding communities against seismic hazards.History
Early Theories and Contributions
The early theories of earthquakes were significantly influenced by ancient philosophical thought, particularly that of pre-Socratic philosophers such as Thales and Aristotle. Thales, often credited with initiating the tradition of natural philosophy, proposed that water was the fundamental substance of the earth, marking a pivotal shift from mythological explanations to a more rational understanding of nature.[51.1] Aristotle further advanced this inquiry by emphasizing systematic observation and reasoning, although his later authority paradoxically hindered scientific progress due to the synthesis of his ideas with Christian theology, which created a worldview resistant to change.[52.1] In the centuries that followed, particularly between 1665 and 1755, members of the Royal Society began to collect eyewitness accounts of earthquakes, which were published in the Philosophical Transactions. These observations were crucial for the development of early seismology, although their impact on the natural philosophy of earthquakes during the seventeenth and eighteenth centuries has not been extensively recognized.[53.1] The catastrophic Lisbon earthquake of 1755 served as a turning point, challenging the prevailing religious orthodoxy and prompting a reevaluation of naturalistic explanations for seismic events. This event inspired critical literary responses, such as Voltaire's satirical novel "Candide," which reflected the growing tension between Enlightenment science and religious interpretations of natural disasters.[72.1] Cultural factors also played a significant role in shaping early theories of earthquakes. Ancient scholars like Plato and Aristotle documented seismic activity in the Aegean region, indicating that earthquakes were integral to the cultural and intellectual landscape of ancient Greece.[73.1] Furthermore, early interpretations of earthquakes often straddled the line between divine influence and natural phenomena, laying the groundwork for future explorations into their causes.[74.1] The history of seismology can be traced back over four millennia, with a notable shift occurring after the Lisbon earthquake, which catalyzed pioneering studies by figures such as John Bevis and John Michell in the late 18th century.[75.1]Key Historical Events in Seismology
The history of seismology is marked by several key milestones that have shaped the understanding of earthquakes and the Earth's interior. Early speculations regarding the natural causes of earthquakes can be traced back to ancient philosophers such as Thales of Miletos, Anaximenes of Miletos, Aristotle, and Zhang Heng, whose writings date from as early as 585 B.C.E. to 132 C.E..[40.1] However, seismology as a distinct scientific discipline did not emerge until the late nineteenth century, with many branches of the field developing even more recently, particularly since the 1960s.[43.1] A significant advancement in the field occurred in 1676 when Robert Hooke published his paper titled "True Theory of Elasticity or Springness," which laid foundational concepts for understanding seismic waves.[41.1] The discovery of P-waves and S-waves in the 1830s further revolutionized the field by providing insights into how these seismic waves travel through different materials, thereby enhancing the understanding of the Earth's internal structure.[54.1] In 1936, Inge Lehmann made a groundbreaking contribution by identifying the existence of a solid inner core within the molten outer core of the Earth, a discovery that was pivotal in shaping modern seismology.[59.1] Lehmann's work led to the identification of the Lehmann discontinuity, a seismic boundary that marks the transition between the inner and outer core at a depth of approximately 5,100 kilometers.[59.1] Her contributions were recognized posthumously with the establishment of the Inge Lehmann Medal by the American Geophysical Union in 1997, awarded for outstanding contributions to the understanding of the Earth's structure and dynamics.[58.1] In the latter half of the twentieth century, particularly after World War II, the field of seismology experienced renewed vigor with advancements in seismic imaging techniques. These modern methods, including controlled source refraction and reflection seismology, have significantly improved the accuracy of imaging complex geological structures.[45.1] The introduction of high-performance computing and advanced algorithms has further enhanced the ability to create detailed 3D models of the Earth's interior, marking a renaissance in global seismology.[48.1]Seismic Waves
Types of Seismic Waves
Seismic waves are primarily classified into body waves and surface waves. Body waves include compressional waves (P-waves) and shear waves (S-waves), while surface waves consist of Love waves and Rayleigh waves. Each type exhibits unique characteristics that affect their propagation through the Earth and interaction with geological materials.[99.1] P-waves, or primary waves, are the fastest seismic waves, traveling at an average speed of approximately 6 km/s. They can move through solids, liquids, and gases, demonstrating versatility in traversing various materials within the Earth.[100.1] In contrast, S-waves, or secondary waves, are slower and can only propagate through solids, with their motion causing particles to move perpendicular to the wave's direction.[100.1] Surface waves, including Love and Rayleigh waves, travel along the Earth's surface and are generally slower than body waves. Despite their reduced speed, they often have larger amplitudes and are responsible for significant destruction during earthquakes.[87.1] Love waves induce horizontal shearing of the ground, while Rayleigh waves create an elliptical motion akin to ocean waves, leading to substantial ground displacement.[87.1] Studying these seismic waves is vital for understanding the Earth's internal structure. By analyzing their travel times and characteristics, seismologists can deduce information about the Earth's layers, such as the crust, mantle, and core.[103.1] Variations in seismic wave velocities can reveal differences in material properties like composition, temperature, and pressure within the Earth.[103.1] Thus, seismic waves are essential tools for monitoring seismic activity and exploring geological features beneath the Earth's surface.[89.1]Properties of Seismic Waves
Seismic waves are classified into two primary types: P-waves (primary waves) and S-waves (secondary waves), each exhibiting distinct properties in terms of speed and behavior. P-waves are compression waves that travel through the Earth by applying a force in the direction of propagation, moving at an average speed that is approximately 60% faster than S-waves.[119.1] This rapid movement allows P-waves to be the first to reach seismic stations following an earthquake.[120.1] In contrast, S-waves are shear waves that move perpendicular to their direction of propagation, causing the medium to shake sideways. They travel slower than P-waves and are unable to propagate through liquids or gases.[120.1] The behavior of these waves is crucial for understanding seismic events and developing early warning systems. Earthquake early warning (EEW) systems leverage the fact that information travels faster than seismic waves, allowing alerts to be sent seconds to minutes before the more destructive S-waves and surface waves arrive.[114.1] These systems detect the initial, less destructive P-waves, enabling timely warnings that can help mitigate damage and save lives.[112.1] Advancements in earthquake warning technology have significantly improved the effectiveness of these systems. Modern EEW systems utilize a network of sensors to monitor seismic waves and vibrations, facilitating real-time alerts through various communication channels, including cell phones, radio, and public address systems.[115.1] The ShakeAlert system, operational in California and expanding to Oregon and Washington, exemplifies these advancements by providing public alerts based on the detection of P-waves.[116.1] Understanding the propagation characteristics of seismic waves is essential for enhancing community preparedness and resilience against earthquakes. Continuous research and technological advancements in this field are paving the way for improved detection systems and proactive measures that can significantly reduce the risks associated with seismic activities.[118.1]In this section:
Earthquake Mechanics
Causes of Earthquakes
Earthquakes are primarily caused by the sudden slip of blocks of the Earth along faults, which are fractures in the Earth's crust where movement occurs. The surface where this slip happens is referred to as the fault plane, while the point beneath the Earth's surface where the earthquake initiates is known as the hypocenter, and the point directly above it on the surface is called the epicenter.[132.1] The mechanics of earthquakes are closely tied to the concept of elastic strain energy, which accumulates in the rocks surrounding a fault due to tectonic forces. When this accumulated energy exceeds the frictional resistance of the fault, a sudden release occurs, resulting in an earthquake.[169.1] The elastic rebound theory, developed by geophysicist Harry Fielding Reid after the 1906 San Francisco earthquake, explains this process. According to this theory, as tectonic plates move, they can become stuck at their edges due to friction. Over time, stress builds up in the rocks along the fault line until it surpasses the strength of the rocks, leading to a sudden slip that releases the stored energy as seismic waves.[151.1] This theory illustrates how the gradual accumulation of elastic strain energy can lead to the abrupt release of energy during an earthquake, akin to a compressed spring that suddenly snaps back to its original shape.[170.1] In addition to the primary slip along faults, earthquakes can also occur due to complex interactions in subduction zones, where one tectonic plate is forced beneath another. This process generates strong earthquakes not only at the plate interface but also away from it, as bending stresses develop when the down-going plate approaches a subduction trench.[131.1] Furthermore, the stick-slip behavior observed in laboratory experiments has provided insights into earthquake mechanics, suggesting that the dynamics of fault movement can be modeled to better understand and predict earthquake occurrences.[139.1]Recent Advancements
Machine Learning in Seismology
Recent advancements in machine learning (ML) and deep learning (DL) have significantly transformed the field of seismology, particularly in earthquake detection, prediction, and analysis. Various ML-based packages have been developed to streamline the entire catalog development process, which includes event detection from continuous waveform records, arrival time picking, phase associations, and hypocenter locations.[190.1] These advancements have led to a surge in research findings, showcasing the potential of ML in earthquake seismology.[191.1] One notable application is the SafeNet model, a multimodal deep learning-based earthquake forecasting system that can rapidly predict earthquake magnitudes for specific regions within seconds. This model integrates diverse geologic and seismic data to analyze spatio-temporal correlations, demonstrating a significant predictive advantage across multiple regions that have previously experienced significant earthquakes.[193.1] Additionally, studies have explored the use of ML techniques, such as random forest and long short-term memory (LSTM) neural networks, to predict large earthquakes and detect precursors through the analysis of seismic multi-parameter data.[215.1] The integration of AI approaches, including ML, has also enhanced the classification of seismic events, allowing for the differentiation between earthquakes, explosions, and volcanic eruptions based on the characteristics of the seismic waves produced.[214.1] Furthermore, the application of ML in seismic wave discrimination has been pivotal for earthquake early warning systems, showcasing its practical implications in real-time risk assessment.[192.1] As the field continues to evolve, the future direction of AI methods in earthquake engineering is expected to involve deep learning-enhanced seismology within an internet-of-things (IoT) framework, which could further improve the understanding of earthquake patterns and behaviors.[213.1] Overall, the incorporation of ML and DL techniques in seismic data analysis not only addresses existing challenges but also opens new avenues for interdisciplinary research that bridges seismology and machine learning.[212.1]Innovations in Seismic Data Analysis
Recent innovations in seismic data analysis have significantly transformed the field of seismology, particularly in the realms of earthquake monitoring and risk assessment. The late 1800s and early 1900s marked a pivotal period in seismology, during which foundational advances were made, including the invention of sensitive seismic instruments by English professors in Japan, which enabled scientific studies of seismic activity.[174.1] This laid the groundwork for the development of seismographs, which have since evolved to provide tangible data on seismic events, enhancing our understanding of earthquake patterns and improving prediction models.[175.1] The advent of computer technology has further revolutionized seismic data analysis. New techniques for interpreting reflection profiles in exploration seismology have emerged, allowing for extensive data processing that was previously unfeasible. This shift has led to a focus on simulating complete seismograms, which are then compared with observed records to derive insights about Earth's internal structure.[176.1] The integration of geographical information systems (GIS) has also played a crucial role in the qualitative and quantitative assessment of seismic hazards, utilizing a variety of data types, including geophysical and geological information.[182.1] Recent advancements in seismic instrumentation, particularly ultra-dense sensors and fiber-optic sensing technologies, have provided unprecedented high-resolution data for both regional and local earthquake monitoring. These innovations enable real-time operation and have the potential to establish next-generation permanent monitoring networks.[183.1] Additionally, the application of machine learning techniques in seismic wave discrimination and earthquake forecasting has shown promise in enhancing predictive capabilities.[184.1] Moreover, the ongoing collaboration among international researchers and organizations is expected to further enhance the sharing of seismic data and the development of artificial intelligence models, which will contribute to improved earthquake prediction and risk assessment methodologies.[185.1] As these technologies continue to evolve, they hold the potential to significantly mitigate the impacts of seismic events on urban planning and public safety.Applications Of Seismology
Earthquake Prediction and Risk Assessment
Seismology plays a crucial role in earthquake prediction and risk assessment, utilizing various methodologies and data sources to enhance the understanding of seismic hazards. One significant aspect of this field is the integration of seismic hazard data, which is essential for defining probable earthquake emergency scenarios. This integration allows for the adoption of hazard values that leverage statistical data concerning historical seismic events at specific sites, often described in terms of macroseismic intensity (MCS).[223.1] In earthquake-prone areas, building codes are developed based on seismic design parameters that include ground acceleration, the structure's fundamental period, and a response modification factor.[221.1] The 2009 National Earthquake Hazards Reduction Program (NEHRP) Recommended Seismic Provisions and the 2010 American Society of Civil Engineers, Structural Engineering Institute (ASCE/SEI) 7 Standard provide critical maps of Risk-Targeted Maximum Considered Earthquake (MCER) spectral response accelerations, which are vital for designing structures that can withstand seismic forces.[222.1] Challenges in integrating seismic data with geological information are prevalent, particularly due to the differences in resolution and scale between well data and seismic measurements. Addressing these challenges involves aligning and fusing seismic attributes with well log data, which are often stored in varying formats.[242.1] Furthermore, the integration of seismic data with other geological information, such as well logs and core samples, significantly enhances the accuracy of subsurface interpretations, thereby improving risk assessments.[243.1] Real-time seismic monitoring systems are also integral to earthquake prediction and risk assessment. These systems, particularly those deployed in urban areas, face challenges related to data handling, dissemination, storage, and archiving. Protocols such as QuakeLink facilitate the real-time exchange of earthquake information, including station metadata and "Did-you-feel-it" (DYFI) reports, ensuring that emergency responders and the public receive timely updates during seismic events.[253.1] The reliability and accuracy of data collected by seismic networks are paramount, and established protocols are in place to maintain these standards during critical situations.Monitoring Volcanic Activity
The development of a low-cost instrumentation system for seismic hazard assessment plays a crucial role in monitoring volcanic activity in urban areas. This system includes a series of autonomous triaxial accelerographs, which are designed and manufactured in-house, along with dedicated software for device configuration, data collection, and post-processing. The primary objective of this system is to enhance the reliability and accuracy of seismic data collection, which is essential for effective monitoring of volcanic activity and its potential impacts on urban populations.[250.1] In addition to the instrumentation, protocols for real-time data dissemination are vital during seismic events, particularly for emergency responders and the public. These protocols ensure that timely and accurate information is available, which can significantly aid in disaster preparedness and response efforts related to volcanic eruptions.[250.1] The integration of such systems and protocols not only improves the understanding of volcanic behavior but also enhances community resilience against seismic hazards.In this section:
Challenges In Seismology
Data Quality and Coverage
Recent advancements in seismology have highlighted significant challenges related to data quality and coverage. One of the primary issues is the effective management of vast amounts of data generated by modern seismic instruments. As the field witnesses a surge in technological innovations, including ultra-dense seismic instruments and fiber-optic sensing technologies, the volume of data collected has increased dramatically. These advancements provide unprecedented high-resolution data for regional and local earthquake monitoring, yet they also necessitate enhanced software infrastructures and suitable data processing techniques to manage this influx effectively.[280.1] Moreover, while remote sensing technologies have revolutionized the study of earthquakes by enabling the collection of valuable data through satellite imagery and other methods, they face challenges such as limited pre-event imagery and restricted access to post-earthquake sites. These limitations can hinder comprehensive assessments of seismic activity and its impacts on the Earth's surface.[264.1] The integration of remote sensing with advanced data analysis methods holds promise for improving our understanding of earthquakes, but the challenges of data quality and coverage remain significant obstacles.[264.1] In addition, the deployment of machine learning techniques in seismology aims to enhance data interpretation and feature extraction, yet the effectiveness of these methods is contingent upon the quality of the input data. As machine learning applications become more widespread, ensuring the reliability and accuracy of seismic data is crucial for improving predictive capabilities and understanding fault dynamics.[266.1]Limitations of Current Seismological Methods
Current seismological methods encounter several critical limitations that impede the precise prediction and understanding of seismic events. A primary challenge is the incomplete coverage of seismic monitoring systems, such as the Advanced National Seismic System (ANSS) in the United States, which requires expansion to effectively monitor earthquakes in vast, sparsely instrumented areas, including unexplored ocean floors.[254.1] Furthermore, the complex relationship between fault behavior and earthquakes remains insufficiently understood, highlighting the need for enhanced interdisciplinary collaboration and advanced data analysis techniques to bridge this knowledge gap.[255.1] Despite significant advancements in data collection and analysis since the late 19th century, the field of earthquake seismology still heavily relies on field observations. The variability in data quality and availability continues to affect the reliability of seismic interpretations.[256.1] While technological innovations offer potential improvements in understanding seismic activity, they also introduce complexities, particularly in earthquake prediction, fault line mapping, and ground motion analysis.[257.1] Data uncertainty is another critical limitation, as the impact of data-driven uncertainty on fault dynamics and predictive models remains underexplored.[258.1] This uncertainty can significantly affect the performance of machine learning algorithms, which are increasingly applied to seismic data analysis. Although machine learning shows promise in identifying patterns within historical seismic data, challenges persist in enhancing the accuracy of earthquake prediction models.[270.1] Moreover, geological variations across different regions complicate fault behavior and earthquake prediction. Factors such as fault stress heterogeneity, material heterogeneity, and geologic characteristics along tectonic faults influence the spatial distribution of ruptures and fault slip localization.[290.1] Dynamic models that incorporate complex geological data and prestress loading are essential for accurately simulating rupture dynamics and ground motion patterns, yet these models are still in development and require further refinement.[291.1]In this section:
References
[1] Seismology - an overview | ScienceDirect Topics — Seismology is defined as the scientific study of earthquakes, their occurrence, and the propagation of seismic waves through the Earth's interior. Early seismic investigations focussed primarily on earthquake occurrences; one of the earliest comprehensive catalogs was compiled by Irish engineer, Robert Mallet (1810–1881), who also coined the term seismology and developed an early design for an electromagnetic seismograph, later developed in Italy by Luigi Palmieri (1867–1896). Seismology now began to develop along two distinct lines: determining the internal structure of the earth based on arrival times, and understanding the mechanism of earthquakes and wave propagation. This introductory chapter covers the science of earthquake seismology: the study of earthquakes using seismic waves.
[2] What is seismology? - Definition, Purpose and Types of Seismology — This type of seismology is commonly used in the oil and gas industry to identify potential reserves. How seismology works. Seismology works by analyzing the vibrations caused by seismic waves. Seismic waves are generated by various processes, including earthquakes, volcanic activity, and human-induced activities such as mining.
[3] Seismology - Wikipedia — In 1926, Harold Jeffreys was the first to claim, based on his study of earthquake waves, that below the mantle, the core of the Earth is liquid. Because seismic waves commonly propagate efficiently as they interact with the internal structure of the Earth, they provide high-resolution noninvasive methods for studying the planet's interior. Engineering seismology is the study and application of seismology for engineering purposes. It generally applied to the branch of seismology that deals with the assessment of the seismic hazard of a site or region for the purposes of earthquake engineering. (eds.), "3.01 – Composition of the Continental Crust", Treatise on Geochemistry, 3, Pergamon: 659, Bibcode:2003TrGeo...3....1R, doi:10.1016/b0-08-043751-6/03016-4, ISBN 978-0-08-043751-4, retrieved 2019-11-21 An Introduction to Seismology, Earthquakes and Earth Structure.
[4] Seismology | UPSeis | Michigan Tech - Michigan Technological University — Seismology | UPSeis | Michigan Tech What Should I Do Before, During, and After an Earthquake? What Should I Do Before, During, and After an Earthquake? Geological and Mining Engineering and Sciences What Should I Do Before, During, and After an Earthquake? Seismology is the study of earthquakes and seismic waves that move through and around the Earth. A seismologist is a scientist who studies earthquakes and seismic waves. What are Seismic Waves? Seismic waves are caused by the sudden movement of materials within the Earth, such as slip along a fault during an earthquake. Earthquakes send out seismic energy as body waves (P and S). Campus and Beyond Campus Info About Michigan Tech Campus Safety Information Geological and Mining Engineering and Sciences
[5] Engaging Students in the Analysis and Interpretation of Seismic Data — IRIS's Education and Public Outreach (EPO) program works to enhance seismology and Earth Science education in K-12 schools, colleges, universities, and the general public. ... Earthquakes provide engaging real-world examples of scientific concepts. Real-time seismic data can be used to explore earthquakes, plate tectonics and its driving forces
[6] Bringing Real Science, Seismology and STEM to the Classroom — Bringing Real Science, Seismology and STEM to the Classroom In the dynamic world of science education, hands-on experiences have proven invaluable. Imagine a classroom where students don't just read about earthquakes—they feel them. Enter Raspberry Shakes, a groundbreaking solution that transforms traditional earth science (and STEM) lessons into interactive, real-world explorations.
[9] The Importance of Seismology in Urban Planning and Development — Incorporating seismological data into urban planning also significantly impacts public safety and emergency preparedness. By identifying high-risk areas and potential impacts of earthquakes, emergency response plans can be tailored to address specific challenges. ... Ultimately, the integration of seismology into urban planning and development
[11] PDF — The application of GIS in urban and regional planning provides decision-makers with a comprehensive view of the geographic, societal, and infrastructural distribution of a city or region. This aids in the planning of safer communities and the identification of critical areas for seismic-resistant infrastructure protection.
[12] Liquefaction and Infrastructure Resilience: Building for Seismic Events ... — Retrofitting existing infrastructure is a proactive approach to enhancing resilience in high-risk areas prone to seismic events. By reinforcing foundations, retrofitting buildings, and implementing comprehensive retrofitting strategies, we can significantly reduce the potential damage caused by earthquakes and liquefaction.
[14] The New Age of Seismology: Breakthroughs in Technology and Data-Driven ... — The New Age of Seismology: Breakthroughs in Technology and Data-Driven Insights – Earth Inversion These innovations are enabling the detection of smaller seismic events, mapping hidden fault structures, and creating detailed 3D models of Earth's interior, opening new frontiers in understanding our planet's dynamics. The field of global seismology is experiencing a renaissance, with major advances driven by new sensing technologies, big data, high-performance computing, and innovative algorithms. With increased computational power, researchers can now create detailed 3D models of Earth’s interior using seismic data . # big data# Earth’s interior# earthquake detection# fault mapping# global seismology# high-performance computing# machine learning# seismic sensing# seismic tomography# seismology My research focuses on seismic data analysis, structural health monitoring, and understanding deep Earth structures.
[17] Machine Learning Applications in Seismology - MDPI — Recent progress in seismic data acquisition and processing, particularly through the application of machine learning techniques, has proven beneficial for seismologists in identifying signals or patterns that traditional methodologies may overlook .For instance, the automatic detection of seismic events via models such as PhaseNet [] streamlines the processing of seismic data [16,17,18
[19] What Are Some Differences Between P & S Waves? - Sciencing — The major differences between P waves and S waves include wave speeds, wave types, travel capabilities, and wave sizes. Primary waves travel faster, move in a push-pull pattern, travel through solids, liquids and gases, and cause less damage due to their smaller size. Secondary waves travel slower, move in an up-and-down pattern, travel only
[40] Seismologists - Highlights of The History of Seismology — Highlights of The History of Seismology Some milestones in the development of seismology are: Early speculations on the natural causes of earthquakes in the writings of Thales of Miletos (ca. 585 B.C.E.), Anaximenes of Miletos (ca. 550 B.C.E.), Aristotle (ca. 340 B.C.E.) and Zhang Heng (132 C.E.).
[41] History of Seismology - IRIS — Depicting original sketches, photographs and colorful new imagery, this poster captures the major milestones of the development in the field of seismology. Seismology's rich history begins with Robert Hooke's 1676 paper titled "True Theory of Elasticity or Springness" and continues through the 1830 discovery of P and S waves, the 1930's discovery of the inner core by Inge Lehman, and includes
[43] Seismology: History - SpringerLink — Although the scholarly study of the causes and effects of earthquakes can be traced into antiquity (Needham, 1959; Adams, 1938), seismology did not emerge as a separate science until the late nineteenth century; many of the most heavily studied branches of the subject began even more recently, in some cases only since the 1960s.This article reviews the growth of these different branches, and
[45] Research progress on seismic imaging technology - ScienceDirect — Imaging on complex media such as subsalt, small-scale, steeply dipping and surface topography structures brings a great challenge to imaging techniques. Therefore, the seismic imaging methods range from stacking-to migration-to inversion-based imaging, and the imaging accuracy is becoming increasingly high.
[48] The New Age of Seismology: Breakthroughs in Technology and Data-Driven ... — The New Age of Seismology: Breakthroughs in Technology and Data-Driven Insights – Earth Inversion These innovations are enabling the detection of smaller seismic events, mapping hidden fault structures, and creating detailed 3D models of Earth's interior, opening new frontiers in understanding our planet's dynamics. The field of global seismology is experiencing a renaissance, with major advances driven by new sensing technologies, big data, high-performance computing, and innovative algorithms. With increased computational power, researchers can now create detailed 3D models of Earth’s interior using seismic data . # big data# Earth’s interior# earthquake detection# fault mapping# global seismology# high-performance computing# machine learning# seismic sensing# seismic tomography# seismology My research focuses on seismic data analysis, structural health monitoring, and understanding deep Earth structures.
[51] Pre-Socratic natural philosophy and Thales: The shift from myth to ... — Pre-Socratic natural philosophy and Thales: The shift from myth to logos - Fabrizio Musacchio Pre-Socratic natural philosophy and Thales: The shift from myth to logos Pre-Socratic natural philosophy and Thales: The shift from myth to logos Although no writings by Thales survive, his ideas are preserved in the works of later philosophers such as Aristotle, who credited him with initiating the tradition of natural philosophy. His identification of water as the arche and his emphasis on natural causality exemplify the shift from mythos to logos, a foundational moment in the history of Western philosophy. Next: Anaximander: Pioneer of cosmology and natural philosophy Previous: Greek philosophy and the foundations of Western thought 610–546 BCE), a successor of Thales and a pivotal figure in early Greek philosophy, stands out ...
[52] Rational Patterns: The Greek Origins of Science — However, Aristotle's influence became paradoxical. While his methods advanced the systematic study of nature, his authority eventually impeded scientific progress. The medieval synthesis of Aristotelian natural philosophy with Christian theology created a comprehensive worldview that proved resistant to change.
[53] Earthquake observations in the age before Lisbon: eyewitness ... — Between 1665 and 1755 several members of the Royal Society collected eyewitness accounts of earthquakes, some of which were published in the Philosophical Transactions.While such observations have been recognized as crucial to early seismology in the nineteenth century, their impact on the seventeenth- and eighteenth-century natural philosophy of earthquakes has received limited attention.
[54] Inge Lehmann: Discoverer of the Earth's Inner Core | AMNH — Those important for understanding the Earth's interior are P-waves, (primary, or compressional waves), and S-waves (secondary, or shear waves), which travel through solid and liquid material in different ways. The seismic waves called S-waves do not travel through liquid. We know that the outer core is liquid because of the shadow it casts in
[58] Inge Lehmann Biography - Facts, Childhood, Family Life & Achievements — Posthumously, to mark the contribution made by Lehmann in the field of seismology, the American Geophysical Union established the Inge Lehmann Medal in 1997. The medal is awarded for outstanding contributions to the understanding of the structure, composition, and dynamics of the Earth's mantle and core, every year.
[59] Inge Lehmann | Danish Seismologist & Earthquake Discoverer | Britannica — Inge Lehmann (born May 13, 1888, Copenhagen, Denmark—died February 21, 1993, Copenhagen) was a Danish seismologist best known for her discovery of the inner core of Earth in 1936 by using seismic wave data.Two boundary regions, or discontinuities, are named for her: one Lehmann discontinuity occurs between Earth's inner and outer core at a depth of roughly 5,100 km (about 3,200 miles), and
[72] Earthquakes in Political, Economic, and Cultural History — The catastrophic Lisbon earthquake of 1755—as well known in the early 19th century as the 1945 atomic bombings are today—was a pivotal factor in the freeing of Enlightenment science from Catholic religious orthodoxy, as epitomized by Voltaire's satirical novel Candide, written in response to the earthquake. Even the minor earthquakes in
[73] Earthquakes shaped ancient Greek culture - EARTH Magazine — Earthquakes occurred often in the carbonate-dominated karstic landscape of the Aegean region, and were well documented from the sixth through the fourth centuries B.C. by ancient scholars like Plato and Aristotle. ... that earthquakes and associated ground ruptures had a prominent role in ancient Greek culture, and participated in structuring
[74] The History of Seismology: Studying Earthquakes and Their Impact — The History of Seismology: Studying Earthquakes and Their Impact | Did You Know Science The History of Seismology: Studying Earthquakes and Their Impact Despite their limitations, these early interpretations laid the groundwork for future explorations into the causes of earthquakes, as societies sought to understand the balance between divine influence and natural phenomena. Seismographs transformed the study of earthquakes by providing tangible data on seismic activity. Earthquake Patterns Analysis: By studying seismic data, you could identify recurring earthquake patterns and understanding these patterns enabled better prediction models and risk assessments, enhancing public safety. Building on the foundation laid by the plate tectonics revolution, advances in earthquake prediction have come a long way, offering hope for minimizing disaster impacts.
[75] A concise history of mainstream seismology: Origins, legacy, and ... — The history of seismology has been traced since man first reacted literarily to the phenomena of earthquakes and volcanoes, some 4000 yr ago. Twenty-six centuries ago man began the quest for natural causes of earthquakes.. The dawn of modern seismology broke immediately after the Lisbon earthquake of 1755 with the pioneering studies of John Bevis (1757) and John Michell (1761).
[87] Seismic Waves: Definition, Types, Examples, and Diagram - Science Facts — Seismic Waves Seismic waves are energy waves that are generated by an earthquake or explosion and propagate within the Earth or on its surface. Types of Seismic Waves There are two different types of seismic waves: body waves and surface waves. Seismic Waves Which seismic waves are the most destructive?*Ans. Surface waves are the most dangerous as they travel through the surface of the Earth. What distinguishes surface and body seismic waves?*Ans. Body waves travel through the interior of the Earth. What do seismic waves and sound waves have in common?*Ans. Seismic waves and sound waves are both a type of mechanical wave and require a medium for propagation. What medium do seismic waves travel through?*Ans. Seismic waves travel through Earth’s interior and surface.
[89] What are Seismic Waves? | Earthquake Glossary | Perlan — Seismic waves are not just phenomena that occur during earthquakes; they are tools scientists use to uncover the mysteries beneath the Earth's surface. In places like Iceland, the constant interaction between seismic activity and geological structures offers invaluable insights into our planet's dynamic processes. Understanding seismic waves
[99] SED | What are P, S, Love and Rayleigh waves? — Seismic waves can be divided into two main types: body waves (P and S waves) and surface waves (Love and Rayleigh waves). ... Being the fastest seismic waves, P waves are the first to reach seismic stations. S waves. S waves (secondary waves) also propagated spherically from the hypocentre in the form of body waves and spread by moving the
[100] Types of seismic waves - GeoQuake — Body waves are divided into two types: shear waves (S-waves) and compressional waves (P-waves); surface waves (Love and Rayleigh waves). They propagate along the surface layers of the Earth. ... P-waves are the fastest seismic waves, with an average speed of 6 km/s. They can propagate through solids, liquids, and gases. Therefore, P-waves are
[103] Seismic Evidence for Internal Earth Structure - Columbia University — Seismic stations located at increasing distances from the earthquake epicenter will record seismic waves that have traveled through increasing depths in the Earth. Seismic velocities depend on the material properties such as composition, mineral phase and packing structure, temperature, and pressure of the media through which seismic waves pass.
[112] The Science of Earthquake Early Warning Systems - Canonica — An Earthquake Early Warning (EEW) system is a type of system that provides a warning of seismic events seconds to minutes before the ground shaking begins. These systems are designed to detect the initial, less destructive P-waves of an earthquake, allowing for a warning to be issued before the more destructive S-waves and surface waves arrive
[114] Earthquake early warning: Recent advances and perspectives — Earthquake early warning (EEW) systems are primarily based on two concepts that enable alerts to be sent ahead of the occurrence of earthquake-induced ground shaking at target locations (on the order of seconds to minutes): (1) Information travels faster than seismic (i.e., mechanical) waves; and (2) most of the energy of an earthquake is carried by the S- and surface waves, which arrive after
[115] Earthquake early warning system - Wikipedia — An animation detailing how earthquake warning systems work: When P waves are detected, the readings are analyzed immediately, and, if needed, the warning information is distributed to advanced users and cell phones, radio, television, sirens, and PA systems/fire alarm systems before the arrival of S waves.. An earthquake warning system or earthquake alarm system is a system of accelerometers
[116] Earthquake Early Warning - Overview | U.S. Geological Survey - USGS.gov — The ShakeAlert earthquake early warning (EEW) system issues public alerts in California and will soon extend to Oregon and Washington. ShakeAlert, the U.S. Geological Survey (USGS) ShakeAlert public Earthquake Early Warning (EEW) system being developed for the U.S. West Coast, was operational during this time, though public alerting was only available within LA County. The ShakeAlert earthquake early warning (EEW) system issues public alerts in California and will soon extend to Oregon and Washington. ShakeAlert, the U.S. Geological Survey (USGS) ShakeAlert public Earthquake Early Warning (EEW) system being developed for the U.S. West Coast, was operational during this time, though public alerting was only available within LA County.
[118] How are advancements in technology improving earthquake prediction and ... — In conclusion, the continuous advancements in earthquake prediction technology are integral to mitigating the risks associated with seismic activities. From enhanced detection systems to improved community preparedness, these innovations hold the potential to safeguard lives and build resilient communities.
[119] What is the difference of P wave and S wave? - Our Planet Today — What is the difference between P waves and S waves based on their movement speed and capacity to move through a medium? P-waves and S-waves are body waves that propagate through the planet. P-waves travel 60% faster than S-waves on average because the interior of the Earth does not react the same way to both of them. P-waves are compression waves that apply a force in the direction of propagation.
[120] P Waves | Speed, Properties, and Real-World Applications — They move perpendicular to their direction of propagation, causing the medium to shake sideways. S-waves travel slower than P-waves and cannot move through liquids or gases. Velocity and Arrival Time P-Waves P-waves travel faster than S-waves, making them the first to reach seismic stations after an earthquake.
[131] Earthquake Mechanisms and Tectonics | SpringerLink — The complex mechanics of subduction, though, generates strong earthquakes also away from the plate interface: (i) As the down-going plate approaches a subduction trench, the plate has to bend from a horizontal to an inclined direction generating bending stresses. ... Schematic overview of some earthquake types observed in subduction zones. Not
[132] The Science of Earthquakes | U.S. Geological Survey - USGS.gov — An earthquake is what happens when two blocks of the earth suddenly slip past one another. The surface where they slip is called the fault or fault plane. The location below the earth’s surface where the earthquake starts is called the hypocenter, and the location directly above it on the surface of the earth is called the epicenter. The earth has four major layers: the inner core, outer core, mantle and crust. The plate boundaries are made up of many faults, and most of the earthquakes around the world occur on these faults.
[139] Predicting Stick-Slips in Sheared Granular Fault Using Machine ... - MDPI — Predicting earthquakes through reasonable methods can significantly reduce the damage caused by secondary disasters such as tsunamis. Recently, machine learning (ML) approaches have been employed to predict laboratory earthquakes using stick-slip dynamics data obtained from sheared granular fault experiments.
[151] Reid's Elastic Rebound Theory - USGS Earthquake Hazards Program — Similarly, the crust of the earth can gradually store elastic stress that is released suddenly during an earthquake. This gradual accumulation and release of stress and strain is now referred to as the "elastic rebound theory" of earthquakes. Most earthquakes are the result of the sudden elastic rebound of previously stored energy.
[169] Elastic-rebound theory - Wikipedia — Elastic-rebound theory - Wikipedia In geology, the elastic-rebound theory is an explanation for how energy is released during an earthquake. After the great 1906 San Francisco earthquake, geophysicist Harry Fielding Reid examined the displacement of the ground surface along the San Andreas Fault in the 50 years before the earthquake. He found evidence for 3.2 m of bending during that period. He concluded that the quake must have been the result of the elastic rebound of the strain energy stored in the rocks on either side of the fault. The two sides of an active but locked fault are slowly moving in different directions, where elastic strain energy builds up in any rock mass that adjoins them.
[170] PDF — The elastic rebound theory is an explanation for how energy is spread during earthquakes. As rocks on oppo-site sides of a fault are subjected to force and shift, they accumulate energy and slowly deform until their inter-nal strength is exceeded. At that time, a sudden move-ment occurs along the fault, releasing the accumulated energy, and the rocks snap back to their original unde-formed shape.
[174] A Brief History of Seismology to 1910 - UC Santa Barbara — The foregoing work set the stage for the late 1800s and early 1900s, when many fundamental advances in seismology would be made. In Japan, three English professors, John Milne, James Ewing, and Thomas Gray, working at the Imperial College of Tokyo, invented the first seismic instruments sensitive enough to be used in the scientific study of
[175] The History of Seismology: Studying Earthquakes and Their Impact — The History of Seismology: Studying Earthquakes and Their Impact | Did You Know Science The History of Seismology: Studying Earthquakes and Their Impact Despite their limitations, these early interpretations laid the groundwork for future explorations into the causes of earthquakes, as societies sought to understand the balance between divine influence and natural phenomena. Seismographs transformed the study of earthquakes by providing tangible data on seismic activity. Earthquake Patterns Analysis: By studying seismic data, you could identify recurring earthquake patterns and understanding these patterns enabled better prediction models and risk assessments, enhancing public safety. Building on the foundation laid by the plate tectonics revolution, advances in earthquake prediction have come a long way, offering hope for minimizing disaster impacts.
[176] Seismology - an overview | ScienceDirect Topics — At the same time, new techniques were developed for the interpretation of reflection profiles in exploration seismology, where the large amount of data obtained require extensive computer processing. The widespread availability of computers has changed the emphasis in theoretical seismology from the study of simplified kinematical models of wave propagation to the simulation of complete seismograms that are then compared with observed records to invert for earth structure. Earthquake seismology is caused by natural shock waves of earthquakes and derives information on physical properties, composition, and the gross internal structure of Earth. The high demand for the MSOP manual and the rapid development of national and international seismological monitoring systems in the 1970s prompted the IASPEI Commission on Practice in 1975 to recommend the preparation of a second edition.
[182] Seismic hazard and risk assessment: a review of state-of-the-art ... — The historical records of earthquakes play a vital role in seismic hazard and risk assessment. During the last decade, geophysical, geotechnical, geochemical, topographical, geomorphological, geological data, and various satellite images have been collected, processed, and well-integrated into qualitative and quantitative spatial databases using geographical information systems (GIS). Various
[183] Recent advances in earthquake monitoring I: Ongoing revolution of ... — Recent advances in earthquake monitoring I: Ongoing revolution of seismic instrumentation - ScienceDirect Recent advances in earthquake monitoring I: Ongoing revolution of seismic instrumentation Moreover, revolutionary advances in ultra-dense seismic instruments, such as nodes and fiber-optic sensing technologies, have recently provided unprecedented high-resolution data for regional and local earthquake monitoring. Fiber-optic sensing techniques, including distributed acoustic sensing, can be operated in real time with an in-house power supply and connected data storage, thereby exhibiting the potential of becoming next-generation permanent networks. With improved knowledge about data characteristics, enhanced software infrastructures, and suitable data processing techniques, these innovations in seismic instrumentation could profoundly impact observational seismology. Recent advances in earthquake monitoring I: Ongoing revolution of seismic instrumentation. For all open access content, the relevant licensing terms apply.
[184] The Role of Machine Learning in Earthquake Seismology: A Review - Springer — Machine learning for earthquake prediction: a review (2017–2021) Xiong P, Tong L, Zhang K, Shen X, Battiston R, Ouzounov D, Iuppa R, Crookes D, Long C, Zhou H (2021) Towards advancing the earthquake forecasting by machine learning of satellite data. Li Z, Meier M, Hauksson E, Zhan Z, Andrews J (2018) Machine learning seismic wave discrimination: application to earthquake early warning. Xiong P, Tong L, Zhang K, Shen X, Battiston R, Ouzounov D, Iuppa R, Crookes D, Long C, Zhou H (2021) Towards advancing the earthquake forecasting by machine learning of satellite data. Li Z, Meier M, Hauksson E, Zhan Z, Andrews J (2018) Machine learning seismic wave discrimination: application to earthquake early warning.
[185] AI in Seismology: Earthquake Detection and Prediction — Continued advancements in sensor technology, including miniaturized and networked sensors, will improve data collection and earthquake monitoring. 9.2 Global Collaboration International collaboration among researchers, governments, and organizations will enhance the sharing of seismic data and the development of AI models.
[190] Recent advances in earthquake seismology using machine learning — Many studies have published ML-based packages that handle the entire catalog development procedure throughout the event detection from continuous waveform records, arrival time picking, phase associations, and hypocenter locations (Walter et al. Xiao Z, Wang J, Liu C et al (2021) Siamese earthquake transformer: a pair-input deep-learning model for earthquake detection and phase picking on a seismic array. Zhang X, Zhang J, Yuan C et al (2020b) Locating induced earthquakes with a network of seismic stations in Oklahoma via a deep learning method. Zhu L, Peng Z, McClellan J et al (2019a) Deep learning for seismic phase detection and picking in the aftershock zone of 2008 M7.9 Wenchuan earthquake.
[191] PDF — Recently, machine learning (ML) technology, including deep learning (DL), has made remarkable progress in various scientic elds, including earthquake seismology, producing vast research ndings. Here, we review the applications of ML in several elds of earthquake seis-mology and discuss the strengths and diculties of using ML.
[192] The Role of Machine Learning in Earthquake Seismology: A Review - Springer — Machine learning for earthquake prediction: a review (2017–2021) Xiong P, Tong L, Zhang K, Shen X, Battiston R, Ouzounov D, Iuppa R, Crookes D, Long C, Zhou H (2021) Towards advancing the earthquake forecasting by machine learning of satellite data. Li Z, Meier M, Hauksson E, Zhan Z, Andrews J (2018) Machine learning seismic wave discrimination: application to earthquake early warning. Xiong P, Tong L, Zhang K, Shen X, Battiston R, Ouzounov D, Iuppa R, Crookes D, Long C, Zhou H (2021) Towards advancing the earthquake forecasting by machine learning of satellite data. Li Z, Meier M, Hauksson E, Zhan Z, Andrews J (2018) Machine learning seismic wave discrimination: application to earthquake early warning.
[193] Scalable intermediate-term earthquake forecasting with multimodal ... — In this study, we introduce SafeNet, a powerful multimodal deep learning-based earthquake forecasting model that can swiftly generate predictions for earthquake magnitudes in a specific region for the upcoming year within seconds. Figure 1 illustrates the SafeNet model, which predicts earthquake magnitudes by fusing multimodal geologic and seismic data to analyze spatio-temporal correlations in diverse seismic regions. Furthermore, the paired t-tests and Wilcoxon tests results, as shown in Table S4, reveal that our model consistently provides a significant predictive advantage across 57 regions have previously experienced \(M \ge 5\) earthquakes for each baseline method. where \(CE(\cdot )\) means catalogs embedding, \(c_{i,j}\) denotes earthquake catalog features in the region of corresponding maps, \((d_{i,j}, m_{i,j,1},m_{i,j,2},\dots )\).
[212] (PDF) Artificial intelligence in seismology: Advent, performance and ... — This study delves into the application of machine learning (ML) and deep learning (DL) techniques for the analysis of seismic data, aiming to identify and categorize patterns and anomalies within
[213] Artificial intelligence in seismology: Advent, performance and future ... — In this focus paper, we provide an overview of the recent AI studies in seismology and evaluate the performance of the major AI techniques including machine learning and deep learning in seismic data analysis. Furthermore, we envision the future direction of the AI methods in earthquake engineering which will involve deep learning-enhanced seismology in an internet-of-things (IoT) platform. Dr. Jiao’s research interests include advanced metastructures, mechanical metamaterials, multiscale structural stability analysis, artificial intelligence in engineering, structural health monitoring and energy harvesting. At the University of Pittsburgh, his Intelligent Structural Monitoring and Response Testing (iSMaRT) Lab focuses on advancing the knowledge and technology required to create self-sustained and multifunctional sensing and monitoring systems that are enhanced by engineering system informatics.
[214] Overview of Artificial Intelligence (AI) and Machine Learning (ML) in ... — There are several ways in which artificial intelligence (AI) approaches, including machine learning, can be used in seismic analysis: Classification of seismic events: Machine learning algorithms can be used to classify different types of seismic events, such as earthquakes, explosions, and volcanic eruptions, based on the characteristics of the seismic waves they produce.
[215] Machine Learning Applications in Seismology - MDPI — (Contribution 7) explore the potential of machine learning techniques, specifically random forest and long short-term memory (LSTM) neural networks, to predict large earthquakes utilizing seismic catalog data from the Sichuan–Yunnan region. (Contribution 15) investigate the application of machine learning for detecting earthquake precursors through the analysis of seismic multi-parameter data across twelve tectonic regions in western China. The topics covered in these articles include seismic inversion, earthquake detection, focal mechanism analysis, ground motion simulation, earthquake early warning systems, and earthquake forecasting, utilizing a diverse array of machine learning methods. Moreover, these articles highlight interdisciplinary research that bridges seismology and machine learning, offering innovative solutions to challenges associated with seismic data and advancements in model interpretability.
[221] PDF — building codes in well known earthquake prone areas contain design parameters based upon ground acceleration, the structure's fundamental period, a response modification factor and the foundation ... Code for Seismic Design of Buildings, China Architecture and Building Press , Baiwanzhuang, Beijing, China IS:1893 .
[222] Maps of earthquake ground motions for the 2009 NEHRP Recommended ... — For designing buildings and other structures to safely resist earthquakes, the 2009 National Earthquake Hazards Reduction Program (NEHRP) Recommended Seismic Provisions and the 2010 American Society of Civil Engineers, Structural Engineering Institute (ASCE/SEI) 7 Standard contain maps of Risk-Targeted Maximum Considered Earthquake (MCER) spectral response accelerations, Maximum Considered Earthqu
[223] How to create seismic risk scenarios in historic built environment ... — Seismic Hazard data should be chosen to define probable earthquake emergency scenarios. According to this standpoint, the adoption of hazard values can take advantage of statistical data concerning historic seismic events that occurred in the considered site. In this term, they can be easily described in terms of macroseismic intensity (MCS).
[242] (PDF) Conceptual integration of seismic attributes and well log data ... — primary technical challenges in data integration is the a lignment and fusion of seismic attributes a nd well log data, which are often collected and stor ed in diff erent formats and scales.
[243] The Importance of Geological Data Libraries in Seismic Studies — Integrating seismic data with other geological information stored in a geological data library significantly improves the accuracy of subsurface interpretations. By accessing well logs, core samples, and historical seismic data from a geological data library, geophysicists can better understand the subsurface environment.
[250] A Low-Cost Instrumentation System for Seismic Hazard Assessment in ... — The development and application of a low-cost instrumentation system for seismic hazard assessment in urban areas are described in the present study. The system comprises a number of autonomous triaxial accelerographs, designed and manufactured in house and together with dedicated software for device configuration, data collection and further postprocessing. The main objective is to produce a
[253] gempa GmbH - SeisComP — De-facto standard. SeisComP is a seismological software for data acquisition, processing, distribution and interactive analysis that has been developed by the GEOFON Program at Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences and gempa GmbH.. SeisComP is likely the most widely distributed software package for seismological data acquisition and real-time data exchange over
[254] PDF — the Grand Challenges. The Advanced National Seismic System (ANSS), the primary earthquake monitoring system in the United States, must be completed. The currently sparse instrumental coverage of the vast areas of unexplored ocean floor needs to be expanded. Source facilities for controlled-source seismic data acquisition are essential
[255] (PDF) Grand challenges for seismology - Academia.edu — Seismology is a crucial field for understanding Earth's dynamics and has broad societal applications, from resource exploration to natural hazard assessment. This work identifies ten grand challenges currently facing seismology, particularly emphasizing the relationship between fault behavior and earthquakes, as well as the need for improved interdisciplinary collaboration and advanced data
[256] Challenges in observational seismology - USGS Publications Warehouse — Earthquake seismology became a quantitative scientific discipline after instruments were developed to record seismic waves in the late 19th century (Dewey and Byerly, 1969; Chapter 1 by Agnew). Earthquake seismology is essentially based on field observations. The great progress made in the past several decades was primarily due to increasingly plentiful and high-quality data that are readily
[257] Seismology Research: Key Areas and Innovations — With ongoing innovations in technology and data analysis, the future of seismology research holds great promise for understanding and mitigating earthquake hazards. The areas of earthquake prediction, fault line mapping, and ground motion analysis are crucial for understanding seismic activity. Technological advancements in seismology research have transformed our understanding of earthquakes. Together, these innovations empower researchers to study seismic activity more effectively and develop strategies to mitigate earthquake risks. Seismology research is essential for advancing our understanding of seismic activity. By continuing to invest in seismology research, we can improve our understanding of earthquakes and develop better strategies for risk reduction. Seismology research is crucial for advancing our understanding of earthquakes. Researchers use advanced technology to monitor seismic activity and analyze data from seismic networks.
[258] Impacts of data uncertainty on the performance of data-driven-based ... — Data uncertainty analysis method has been widely applied and becomes the mainstream approach in above mentioned research fields. However, there has been limited investigation on the uncertainty analysis of data-driven-based building FDD model. Little is known about impact of data uncertainty on FDD model.
[264] Advancements in Remote Sensing Techniques for Earthquake Engineering: A ... — Advancements in Remote Sensing Techniques for Earthquake Engineering: A Review - ScienceDirect Advancements in Remote Sensing Techniques for Earthquake Engineering: A Review Remote sensing technologies play a vital role in our understanding of earthquakes and their impact on the Earth's surface. This review highlights the advancements in the integration of remote sensing technologies into earthquake studies. However, remote sensing encounters challenges due to limited pre-event imagery and restricted post-earthquake site access. Overall, the utilization of remote sensing technologies has greatly enhanced our comprehension of earthquakes and their effects on the Earth's surface. The fusion of remote sensing technology with advanced data analysis methods holds tremendous potential for driving progress in earthquake studies and damage assessment. For all open access content, the Creative Commons licensing terms apply.
[266] Machine Learning in Seismology: Turning Data into Insights — This article provides an overview of current applications of machine learning (ML) in seismology. ML techniques are becoming increasingly widespread in seismology, with applications ranging from identifying unseen signals and patterns to extracting features that might improve our physical understanding. The survey of the applications in seismology presented here serves as a catalyst for
[270] Earthquake Prediction Model Using Random Forest and Gradient Boosting ... — Accurate earthquake prediction remains a significant challenge in geosciences. This research investigates the application of machine learning algorithms, specifically Random Forest and Gradient Boosting Algorithms, for earthquake prediction. By analyzing historical seismic data, these models aim to identify patterns and predict the likelihood of future earthquake occurrences. This study
[280] Recent advances in earthquake monitoring I: Ongoing revolution of ... — Recent advances in earthquake monitoring I: Ongoing revolution of seismic instrumentation - ScienceDirect Recent advances in earthquake monitoring I: Ongoing revolution of seismic instrumentation Moreover, revolutionary advances in ultra-dense seismic instruments, such as nodes and fiber-optic sensing technologies, have recently provided unprecedented high-resolution data for regional and local earthquake monitoring. Fiber-optic sensing techniques, including distributed acoustic sensing, can be operated in real time with an in-house power supply and connected data storage, thereby exhibiting the potential of becoming next-generation permanent networks. With improved knowledge about data characteristics, enhanced software infrastructures, and suitable data processing techniques, these innovations in seismic instrumentation could profoundly impact observational seismology. Recent advances in earthquake monitoring I: Ongoing revolution of seismic instrumentation. For all open access content, the relevant licensing terms apply.
[290] Tectonic Landform and Lithologic Age Impact Uncertainties in Fault ... — Geologic characteristics along tectonic faults such as rock type and age and fault maturity impact the spatial distribution of ruptures and the localization of fault slip at the Earth's surface and therefore have implications for geologic research and fault displacement hazard assessment (e.g., Dolan & Haravitch, 2014; Johnson et al., 1997
[291] Rupture dynamics and velocity structure effects on ground motion during ... — Our dynamic models, using data-constrained complex geometry and prestress loading, produce complex ground motion patterns and heterogeneous distribution along, across, and off the ruptured fault segments (Fig. 3). Spontaneous dynamic rupture models, accounting for local/regional velocity structure, topo-bathymetry, off-fault plasticity (see details in Methods), and prestressed under complex regional stress, provide self-consistent scenarios of rupture dynamics evolution, wave propagation and their coupled effect on the resulting ground motions35,51,52. Our dynamic rupture models for the 2023 Kahramanmaraş earthquake doublet, with data-constrained fault geometry and prestress loading complexity, reproduces the geodetic and seismic observations. M. Fault geometry, rupture dynamics and ground motion from potential earthquakes on the North Anatolian fault under the sea of Marmara.