Application of Data Processing in Earthquake Science
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Physics General".
Deadline for manuscript submissions: 20 April 2026 | Viewed by 28
Special Issue Editor
Special Issue Information
Dear Colleagues,
Modern data processing techniques are reshaping various fields of Earthquake Science, including remote sensing, early warning and forecasting, and even data recovery and storage. Machine learning (ML) pipelines, hybrid models that combine crowdsourced smartphone triggers, satellite geodesy, acoustic sensing with well-established time-series analysis, and probabilistic decision-making have been reported to successfully address issues such as location and magnitude estimation, magnitude saturation, coseismic slip, and postseismic deformation.
We are pleased to invite researchers, experts, and scholars to submit their work to this Special Issue of Applied Sciences. We welcome original research, case studies and review articles that highlight advances in data processing models and techniques for addressing seismology and earthquake-related hazards. This Special Issue aims to bring together cutting-edge research that will advance both theory and practice in this field, fostering interdisciplinary collaboration and providing actionable insights for earthquake monitoring and mitigation. Contributions may address, but are not limited to, the following topics:
- Earthquake ground motion;
- Next-generation earthquake monitoring;
- Statistical methods in earthquake data analysis and interpretation;
- Case studies from recent large seismic events;
- Resilient and intelligent earthquake warning systems;
- Management of big data in earthquake monitoring;
- Real-time magnitude estimation and localization;
- Machine learning in earthquake early warning;
- Time domain analysis.
We look forward to receiving your contributions.
Dr. Konstantina Papadopoulou
Guest Editor
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Keywords
- time domain analysis
- earthquake ground motion
- next-generation earthquake monitoring
- statistical methods in earthquake data analysis and interpretation
- case studies from recent large seismic events
- resilient and intelligent earthquake warning systems
- big data management in earthquake monitoring
- real-time magnitude estimation and localization
- machine learning in earthquake early warning
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