Analysis of helio-geo-ionospheric proxies for short-term earthquake forecasting
(English) Earthquakes are among the most destructive natural disasters, causing significant infrastructure damage and casualties. Between 1998 and 2018, seismic events resulted in approximately 846000 fatalities and caused economic losses totaling US$661 billion, emphasizing their profound socioecon...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/696017 |
| Acceso en línea: | http://hdl.handle.net/10803/696017 https://dx.doi.org/10.5821/dissertation-2117-448532 |
| Access Level: | acceso abierto |
| Palabra clave: | Earthquake precursors Remote sensing Lithospheric-Atmospheric-Ionospheric Coupling Statistical analysis Data processing Àrees temàtiques de la UPC::Enginyeria de la telecomunicació Àrees temàtiques de la UPC::Enginyeria civil 621.3 - Enginyeria elèctrica. Electrotècnia. Telecomunicacions 624 - Enginyeria civil i de la construcció en general |
| Sumario: | (English) Earthquakes are among the most destructive natural disasters, causing significant infrastructure damage and casualties. Between 1998 and 2018, seismic events resulted in approximately 846000 fatalities and caused economic losses totaling US$661 billion, emphasizing their profound socioeconomic impact. While thousands of earthquakes occur each year globally, only a small number are significant enough to be detected by monitoring systems or felt by people. Although earthquakes cannot be prevented, efforts have been made to reduce their consequences through risk assessment and public preparedness initiatives. Despite these advances, a reliable early warning system for earthquakes remains insufficient. The absence of consistent, deterministic precursors to seismic events is a critical challenge in developing such systems. However, research has identified small detectable geophysical signal anomalies that may appear days to weeks before major earthquakes. These anomalies involve changes in thermal infrared emissions, ionospheric scintillation, disturbances in magnetic fields, etc. While these signals are not usually present, their detection could enhance forecasting capabilities. Remote Sensing (RS) is a promising technique that provides broad spatial coverage, high temporal resolution, and the capability to observe otherwise inaccessible areas, such as oceans, deserts, and mountains. RS systems allow for continuous monitoring of the Earth's surface and atmosphere, enabling the detection of potentially earthquake-related anomalies across the lithosphere, atmosphere, and ionosphere. This Ph.D. thesis studies the use of RS techniques for earthquake precursor detection and their recent advancements. It explores Lithosphere-Atmosphere-Ionosphere Coupling (LAIC), a multidisciplinary framework that explains how seismic stress and rock deformation in the lithosphere can trigger cascading effects in the atmosphere and ionosphere. The thesis also presents results from ongoing research into short- and medium-term earthquake forecasting using Earth observation data. The Ph.D. thesis examines several satellite-derived parameters: Land Surface Temperature (LST) anomalies, Ionospheric Scintillation (IS) indices, geomagnetic field variations, and space weather data. This work aims to contribute to understanding earthquake precursors and seeks to develop practical tools for better predicting seismic events, enhancing mitigation and early warning efforts. |
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