Preprints
https://doi.org/10.5194/angeo-2021-41
https://doi.org/10.5194/angeo-2021-41

  01 Sep 2021

01 Sep 2021

Review status: this preprint is currently under review for the journal ANGEO.

Estimation of date and magnitude of four major earthquakes using integration of precursors obtained from remote sensing data

Mohammad Mahdi Khoshgoftar and Mohammad Reza Saradjian Mohammad Mahdi Khoshgoftar and Mohammad Reza Saradjian
  • School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran

Abstract. A single precursor is not usually an accurate, precise and adequate measure to predict earthquake parameters. Therefore, it is more appropriate to exploit parameters extracted from several other single precursors, so that their simultaneous combinations may reduce the uncertainty of the prediction. In this study, remote sensing observations in different modalities acquired from several days before impending earthquakes have been investigated to extract earthquake parameters. They are observations in electron and ion density, electron temperature, Total Electron Content (TEC), Land Surface Temperature (LST), Sea Surface Temperature (SST), Aerosol Optical Depth (AOD), Surface Latent Heat Flux (SLHF), and Outgoing Longwave Radiation (OLR) clear sky. Regarding the ionospheric precursors, the geomagnetic indices Dst, Kp, Ap and F10.7 were used to detect pre-earthquake disturbances from frequent anomalies associated with geomagnetic activity. In this study, three methods of median, support vector regression (SVR) and random forest (RF) have been used to detect anomalies. When anomalies associated with impending earthquakes are detected, the number of prior days associated with the earthquake is estimated based on the type of precursor. Then, by estimation of the amount of anomaly deviation from the normal state, the magnitude of the impending earthquake is estimated. The final earthquake parameters (such as date and magnitude) can be obtained by integrating the earthquake parameters extracted from different earthquake precursors using mean square error (MSE) method.

Mohammad Mahdi Khoshgoftar and Mohammad Reza Saradjian

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on angeo-2021-41', Anonymous Referee #1, 29 Sep 2021
    • CC2: 'Reply on RC1', Mohammad Mahdi Khoshgoftar, 23 Oct 2021
      • AC1: 'Reply on RC1', Mohammad Mahdi Khoshgoftar, 23 Oct 2021
    • AC1: 'Reply on RC1', Mohammad Mahdi Khoshgoftar, 23 Oct 2021
  • CC1: 'Revision', Iman Khosravi, 15 Oct 2021
    • AC2: 'Reply on CC1', Mohammad Mahdi Khoshgoftar, 31 Oct 2021
  • RC2: 'Comment on angeo-2021-41', Anonymous Referee #2, 23 Oct 2021
    • AC3: 'Reply on RC2', Mohammad Mahdi Khoshgoftar, 02 Nov 2021

Mohammad Mahdi Khoshgoftar and Mohammad Reza Saradjian

Mohammad Mahdi Khoshgoftar and Mohammad Reza Saradjian

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Short summary
This article is about using remote sensing data to estimate the date and magnitude of the impending earthquakes. An earthquake can also affect the environment. Damage to the environment can destroy and lose lives and be more dangerous than earthquakes. The damage sustained by earthquakes is due to the secondary effects of man-made materials on the environment. Water pipes are broken and the ground is flooded, and gas, electricity and scattered fuel lines cause fires.