Atmospheric precursors associated with two Mw > 6.0 earthquakes using machine learning methods

The advancements in remote sensing (RS) satellite applications have revolutionized natural disaster surveillance and prediction in the earthquake monitoring by delineating various precursors at the Earth’s surface and in atmosphere. In this paper, the earthquake precursors comprising land surface te...

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Bibliographic Details
Published in:Natural hazards (Dordrecht) 2024-06, Vol.120 (8), p.7871-7895
Main Authors: Khalid, Zaid, Shah, Munawar, Riaz, Salma, Ghaffar, Bushra, Jamjareegulgarn, Punyawi
Format: Article
Language:English
Subjects:
Air temperature
Atmosphere
Civil Engineering
Earth and Environmental Science
Earth Sciences
Earth surface
Earthquake prediction
Earthquakes
Environmental Management
Geophysics/Geodesy
Geotechnical Engineering & Applied Earth Sciences
Hydrogeology
Land surface temperature
Lithosphere
Long short-term memory
Machine learning
Natural disasters
Natural Hazards
Neural networks
Neural stem cells
Original Paper
Precursors
Recurrent neural networks
Relative humidity
Remote sensing
Seismic activity
Surface temperature
Surveillance
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Summary:The advancements in remote sensing (RS) satellite applications have revolutionized natural disaster surveillance and prediction in the earthquake monitoring by delineating various precursors at the Earth’s surface and in atmosphere. In this paper, the earthquake precursors comprising land surface temperature, outgoing longwave radiations, relative humidity, and air temperature for both the daytime and nighttime are investigated for two Mw > 6.0 events in USA. Interestingly, we noticed surface and atmospheric parameters anomalies in 6–8 days window prior to both the events by using standard deviation method. Moreover, these abrupt deviations are also validated by the recurrent neural networks like autoregressive network with exogenous inputs and long short-term memory inputs. The findings of this study demonstrate the potential of using modern analysis tools to further develop our knowledge of the linked dynamics of the lithosphere and atmosphere preceding seismic occurrences. This study implements substantially the developing of natural hazard surveillance and earthquake prediction capabilities for future researches as a valuable addition of reference in the field of RS.
ISSN:0921-030X
1573-0840
DOI:10.1007/s11069-024-06562-9