Special Topics in Seismology
| Title | Ειδικά Σεισμολογικά Θέματα / Special Topics in Seismology |
| Code | EGSO205 |
| Faculty | Sciences |
| School | Geology |
| Cycle / Level | 2nd / Postgraduate |
| Teaching Period | Winter/Spring |
| Coordinator | Emmanuel Scordilis |
| Common | No |
| Status | Active |
| Course ID | 600023277 |
Programme of Study: PMS Efarmosménī kai Perivallontikī Geōlogía kai Geōkíndynoi
Registered students: 0
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| Efarmosménī Geōfysikī kai Seismología | Elective Courses | 2 | 1 | 5 |
| Academic Year | 2026 – 2027 |
| Class Period | Spring |
| Faculty Instructors |
|
| Weekly Hours | 6 |
| Total Hours | 78 |
| Class ID | 600304345
|
Course Type 2021
Specialization / Direction
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600304345
Erasmus
The course is also offered to exchange programme students.
Learning Outcomes
This course aims to equip students with advanced skills in seismological research, emphasizing proficiency in interpreting and manipulating seismic data using innovative techniques and Python programming. Students will gain expertise in applying state-of-the-art seismic imaging methods, integrating machine learning for enhanced data analysis and event detection, and conducting seismic hazard assessments with a focus on mitigation strategies. The course also fosters effective communication and collaboration, guiding students in synthesizing and presenting findings, collaborating with international experts, and adhering to ethical standards in seismic research. By evaluating the socio-political and technical impact of their work, students will develop a holistic understanding of the broader implications of seismological studies.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Work autonomously
- Work in teams
- Work in an interdisciplinary team
- Advance free, creative and causative thinking
Course Content (Syllabus)
Introduction to Advanced Seismic Technique.
Content: Explore the cutting-edge methods in seismic data acquisition, processing, and interpretation, including Fiber Optic Seismology. Discuss advancements in seismic technology and their applications in understanding subsurface structures. Introduce Python applications for seismic data manipulation and visualization.
Machine Learning in Seismology: A Data-Driven Approach
Content: Delve into the intersection of seismology and machine learning. Discuss how ML algorithms enhance seismic signal processing, event detection, and earthquake prediction. Showcase Python implementations for applying machine learning to seismic datasets.
Seismic Imaging: Beyond the Basics
Content: Explore state-of-the-art seismic imaging technologies, including full-waveform inversion, seismic tomography, and ambient noise imaging. Demonstrate Python applications for implementing advanced seismic imaging algorithms.
Seismic Hazard Assessment and Mitigation Strategies
Content: Discuss the latest methodologies for seismic hazard assessment, emphasizing probabilistic seismic hazard models. Explore Python tools for seismic risk mapping and the development of mitigation strategies.
Real-time Seismic Monitoring and Early Warning Systems
Content: Examine state-of-the-art technologies for real-time seismic monitoring and early warning systems. Discuss Python applications for developing and implementing real-time seismic data processing algorithms and alert systems.
Each lecture combines theoretical knowledge with practical Python applications, offering students a comprehensive understanding of the latest advancements in special topics in seismology.
Educational Material Types
- Slide presentations
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Laboratory Teaching
- Use of ICT in Communication with Students
- Use of ICT in Student Assessment
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 70 | ✓ | |||
| Project | 50 | ✓ | |||
| Exams | 5 | ✓ | |||
| Total | 125 |
Student Assessment
Description
Quality management system of the Quality Assurance Unit (MO.DI.P.)
Student Assessment methods
- Written Exam with Extended Answer Questions (Formative, Summative)
- Written Assignment (Formative, Summative)
Bibliography
Course Bibliography (Eudoxus)
• Lecture notes (eclass)
• On-line resources
• GitHub repos
• Βιβλία
o Computational seismology: a practical introduction , Oxford University Press, Igel, Heiner
o Earthquake Seismology, by Peter M. Shearer
o Instrumentation in Earthquake Seismology, Springer International Publishing, Jens Havskov, Gerardo Alguacil (auth.)
o Lay, T., and Wallace, T. C. (1995) Modern Global Seismology. Academic Press
o Principles of Seismology, Cambridge University Press, Agustín Udías, Elisa Buforn
o Seth Stein, Michael Wysession (2013) An Introduction to Seismology, Earthquakes, and Earth Structure, Wiley, ISBN: 978-1-118-68745-1
Treatise on Geophysics: Earthquake Seismology, Elsevier, Hiroo Kanamori, Gerald Schubert (eds.)
Last Update
28-02-2025
