Articles | Volume 15, issue 5
https://doi.org/10.5194/nhess-15-1061-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-15-1061-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
27 May 2015
Research article |
| 27 May 2015
On a report that the 2012 M 6.0 earthquake in Italy was predicted after seeing an unusual cloud formation
J. N. Thomas
CORRESPONDING AUTHOR
NorthWest Research Associates, Redmond, Washington, USA
Department of Electrical and Computer Engineering, DigiPen Institute of Technology, Redmond, Washington, USA
Department of Earth and Space Sciences, University of Washington, Seattle, Washington, USA
Istituto Nazionale di Geofisica e Vulcanologia, L'Aquila, Italy
J. J. Love
Geomagnetism Program, U.S. Geological Survey, Denver, Colorado, USA
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Cited
14 citations as recorded by crossref.
- Investigation of the application of geospatial artificial intelligence for integration of earthquake precursors extracted from remotely sensed SAR and thermal images for earthquake prediction Z. Alizadeh Zakaria et al. https://doi.org/10.1007/s11042-023-14611-x
- Detection and Identification of Preseismic Thermal Anomalies in Cloudy Conditions Associated With the 2022 Luding (China) Mw 6.6 Earthquake F. Jing et al. https://doi.org/10.1109/TGRS.2023.3304975
- Processes Leading to a Localized Decrease in Air Humidity Prior to the Earthquake A. Nikitin et al. https://doi.org/10.1134/S1990793126700302
- Application of Artificial Neural Network Methods to Anatolian Plate Earthquake Magnitude and Location Prediction M. Emeç & M. Özcanhan https://doi.org/10.30931/jetas.1377481
- On the Relation Between Anomalous Clouds and Earthquakes in Italian Land G. Guangmeng https://doi.org/10.3389/feart.2022.812540
- A Retrospective Analysis about the Italy Emilia M6.0 Earthquake Prediction G. Guo https://doi.org/10.4236/ojer.2021.102005
- Geosystemics View of Earthquakes A. De Santis et al. https://doi.org/10.3390/e21040412
- Investigating the relationship between earthquake occurrences and climate change using RNN-based deep learning approach B. Sadhukhan et al. https://doi.org/10.1007/s12517-021-09229-y
- Possibility of an earthquake prediction based on monitoring crustal deformation anomalies and thermal anomalies at the epicenter of earthquakes with oblique thrust faulting Z. Alizadeh Zakaria & F. Farnood Ahmadi https://doi.org/10.1007/s11600-019-00390-3
- Earthquake Prediction Based on Spatio-Temporal Data Mining: An LSTM Network Approach Q. Wang et al. https://doi.org/10.1109/TETC.2017.2699169
- Structural recurrent neural network models for earthquake prediction A. Doğan & E. Demir https://doi.org/10.1007/s00521-022-07030-w
- Impact of climate change on seismicity:a statistical approach C. Maji et al. https://doi.org/10.1007/s12517-021-08946-8
- A stress test to evaluate the usefulness of Akaike information criterion in short-term earthquake prediction R. Tozzi et al. https://doi.org/10.1038/s41598-020-77834-0
- Climatic and seismic data-driven deep learning model for earthquake magnitude prediction B. Sadhukhan et al. https://doi.org/10.3389/feart.2023.1082832
14 citations as recorded by crossref.
- Investigation of the application of geospatial artificial intelligence for integration of earthquake precursors extracted from remotely sensed SAR and thermal images for earthquake prediction Z. Alizadeh Zakaria et al. https://doi.org/10.1007/s11042-023-14611-x
- Detection and Identification of Preseismic Thermal Anomalies in Cloudy Conditions Associated With the 2022 Luding (China) Mw 6.6 Earthquake F. Jing et al. https://doi.org/10.1109/TGRS.2023.3304975
- Processes Leading to a Localized Decrease in Air Humidity Prior to the Earthquake A. Nikitin et al. https://doi.org/10.1134/S1990793126700302
- Application of Artificial Neural Network Methods to Anatolian Plate Earthquake Magnitude and Location Prediction M. Emeç & M. Özcanhan https://doi.org/10.30931/jetas.1377481
- On the Relation Between Anomalous Clouds and Earthquakes in Italian Land G. Guangmeng https://doi.org/10.3389/feart.2022.812540
- A Retrospective Analysis about the Italy Emilia M6.0 Earthquake Prediction G. Guo https://doi.org/10.4236/ojer.2021.102005
- Geosystemics View of Earthquakes A. De Santis et al. https://doi.org/10.3390/e21040412
- Investigating the relationship between earthquake occurrences and climate change using RNN-based deep learning approach B. Sadhukhan et al. https://doi.org/10.1007/s12517-021-09229-y
- Possibility of an earthquake prediction based on monitoring crustal deformation anomalies and thermal anomalies at the epicenter of earthquakes with oblique thrust faulting Z. Alizadeh Zakaria & F. Farnood Ahmadi https://doi.org/10.1007/s11600-019-00390-3
- Earthquake Prediction Based on Spatio-Temporal Data Mining: An LSTM Network Approach Q. Wang et al. https://doi.org/10.1109/TETC.2017.2699169
- Structural recurrent neural network models for earthquake prediction A. Doğan & E. Demir https://doi.org/10.1007/s00521-022-07030-w
- Impact of climate change on seismicity:a statistical approach C. Maji et al. https://doi.org/10.1007/s12517-021-08946-8
- A stress test to evaluate the usefulness of Akaike information criterion in short-term earthquake prediction R. Tozzi et al. https://doi.org/10.1038/s41598-020-77834-0
- Climatic and seismic data-driven deep learning model for earthquake magnitude prediction B. Sadhukhan et al. https://doi.org/10.3389/feart.2023.1082832
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