Skip to main content

Advertisement

SpringerLink
Log in

Possibility of an earthquake prediction based on monitoring crustal deformation anomalies and thermal anomalies at the epicenter of earthquakes with oblique thrust faulting

  • Research Article - Solid Earth Sciences
  • Published:
Acta Geophysica Aims and scope Submit manuscript

Abstract

Is it possible to predict location, time and magnitude of earthquakes through identifying their precursors based on remotely sensed data? Earthquakes are usually preceded by unusual natural incidents that are considered as earthquake precursors. With the recent advances in remote sensing techniques which have made it possible monitoring the earth’s surface with different sensors, scientists are now able to better study earthquake precursors. Thus, the present study aims at developing the algorithm of classic PS-InSAR processing for obtaining crustal deformation values at the epicenter of earthquakes with magnitude larger than 5.0 on the Richter scale and with oblique thrust faulting and then after calculating temperature values using remotely sensed thermal imagery at the epicenter of same earthquakes; thermal and crustal deformation anomalies were calculated using data mining techniques before earthquake occurrence. In the next stage, taking the correlation between thermal anomalies and crustal deformation anomalies at the epicenter of the study earthquakes into account, an integrated technique was proposed to predict probable magnitude and time of oblique thrust earthquakes occurrence over the earthquake-prone areas. Eventually, the validity of the proposed algorithm was evaluated for an earthquake with a different focal mechanism. The analysis results of the thermal anomalies and crustal deformation anomalies at the epicenter of April 16, 2016, Japan-Kumamoto earthquake of magnitude 7.0 with strike-slip faulting, showed completely different trends than the suggested patterns by the proposed algorithm.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Akhoondzadeh M, Parrot M, Saradjian M (2010) Electron and ion density variations before strong earthquakes (M%3e 6.0) using DEMETER and GPS data. Nat Hazards Earth Syst Sci 10:7–18

    Google Scholar 

  • Bamler R, Hartl P (1998) Synthetic aperture radar interferometry. Inverse Prob 14(4):R1

    Google Scholar 

  • Brockwell PJ, Davis RA, Fienberg SE (1991) Time-series: theory and methods. Springer, Berlin

    Google Scholar 

  • Bürgmann R, Rosen PA, Fielding EJ (2000) Synthetic aperture radar interferometry to measure Earth’s surface topography and its deformation. Annu Rev Earth Planet Sci 28(1):169–209

    Google Scholar 

  • Calais E, Vergnolle M, San'Kov V et al (2003) GPS measurements of crustal deformation in the Baikal-Mongolia area (1994–2002): implications for current kinematics of Asia. J Geophys Res Solid Earth 108:2501

    Google Scholar 

  • Gabriel AK, Goldstein RM, Zebker HA (1989) Mapping small elevation changes over large areas: differential radar interferometry. J Geophys Res Solid Earth 94(B7):9183–9191

    Google Scholar 

  • Graham LC (1974) Synthetic interferometer radar for topographic mapping. Proc IEEE 62(6):763–768

    Google Scholar 

  • Grant RA, Raulin JP, Freund FT (2015) Changes in animal activity prior to a major (M= 7) earthquake in the Peruvian Andes. Phys Chem Earth Parts A/B/C 85:69–77

    Google Scholar 

  • Guo G, Wang B (2008) Cloud anomaly before Iran earthquake. Int J Remote Sens 29:1921–1928

    Google Scholar 

  • Han P, Hattori K, Huang Q et al (2011) Evaluation of ULF electromagnetic phenomena associated with the 2000 Izu Islands earthquake swarm by wavelet transform analysis. Nat Hazards Earth Syst Sci 11:965–970

    Google Scholar 

  • Hand DJ (2007) Principles of data mining. Drug Saf 30:621–622

    Google Scholar 

  • Hayakawa M (2013) Possible electromagnetic effects on abnormal animal behavior before an earthquake. Animals 3:19–32

    Google Scholar 

  • Hooper A (2008) A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches. Geophys Res Lett 35(16):16302

    Google Scholar 

  • Huang J, Mao F, Zhou W, Zhu X (2008) Satellite thermal IR associated with Wenchuan earthquake in China using MODIS data. In: Paper presented at the proceeding of the 14th world conference on earthquake engineering.

  • Huang F, Li M, Ma Y et al (2017) Studies on earthquake precursors in China: a review for recent 50 years. Geod Geodyn 8:1–12

    Google Scholar 

  • Ingebritsen SE, Manga M (2014) Earthquakes: hydrogeochemical precursors. Nat Geosci 7:697

    Google Scholar 

  • Li J, Heap AD (2014) Spatial interpolation methods applied in the environmental sciences: a review. Environ Modell Softw 53:173–189

    Google Scholar 

  • Lippiello E, Marzocchi W, de Arcangelis L, Godano C (2012) Spatial organization of foreshocks as a tool to forecast large earthquakes. Sci Rep 2:846

    Google Scholar 

  • Lu X, Meng Q, Gu X et al (2016) Thermal infrared anomalies associated with multi-year earthquakes in the Tibet region based on China’s FY-2E satellite data. Adv Space Res 58:989–1001

    Google Scholar 

  • Massonnet D, Feigl KL (1998) Radar interferometry and its application to changes in the Earth's surface. Rev Geophys 36:441–500

    Google Scholar 

  • Massonnet D, Rossi M, Carmona C, Adragna F, Peltzer G, Feigl K, Rabaute T (1993) The displacement field of the Landers earthquake mapped by radar interferometry. Nature 364(6433):138

    Google Scholar 

  • Mohankumar K, Sangeetha K (2018) A study on earthquake prediction using neural network algorithms

  • Molchanov O, Rozhnoi A, Solovieva M et al (2006) Global diagnostics of the ionospheric perturbations related to the seismic activity using the VLF radio signals collected on the DEMETER satellite. Nat Hazards Earth Syst Sci 6:745–753

    Google Scholar 

  • Moreno M, Rosenau M, Oncken O (2010) 2010 Maule earthquake slip correlates with pre-seismic locking of Andean subduction zone. Nature 467:198

    Google Scholar 

  • Moro M, Saroli M, Stramondo S et al (2017) New insights into earthquake precursors from InSAR. Sci Rep 7:12035

    Google Scholar 

  • Ogata Y, Katsura K (2012) Prospective foreshock forecast experiment during the last 17 years. Geophys J Int 191:1237–1244

    Google Scholar 

  • Parsons, B. (2017) From geodesy to tectonics: observing earthquake processes from space (Augustus Love Medal Lecture). In: Paper presented at the EGU general assembly conference abstracts.

  • Peacock S, Crampin S, Booth DC, Fletcher JB (1988) Shear wave splitting in the Anza seismic gap, southern California: temporal variations as possible precursors. J Geophys Res Solid Earth 93:3339–3356

    Google Scholar 

  • Peltzer G, Rosen P (1995) Surface displacement of the 17 May 1993 Eureka Valley, California, earthquake observed by SAR interferometry. Science 268(5215):1333–1336

    Google Scholar 

  • Pio Lucente F, De Gori P, Margheriti L et al (2010) Temporal variation of seismic velocity and anisotropy before the 2009 MW 6.3 L'Aquila earthquake Italy. Geology 38:1015–1018

    Google Scholar 

  • Pohn H, Offield T, Watson K (1974) Thermal inertia mapping from satellite-discrimination of geologic units in Oman. J Res US Geol Surv 2:147–158

    Google Scholar 

  • Pulinets S, Davidenko D (2014) Ionospheric precursors of earthquakes and global electric circuit. Adv Space Res 53:709–723

    Google Scholar 

  • Pulinets S, Ouzounov D, Karelin A, Boyarchuk K, Pokhmelnykh L (2006) The physical nature of thermal anomalies observed before strong earthquakes. Phys Chem Earth Parts A/B/C 31:143–153

    Google Scholar 

  • Qiang Z-J, Kong L-C, Zheng L-Z et al (1997) An experimental study on temperature increasing mechanism of satellitic thermo-infrared. Acta Seismol Sin 10:247–252

    Google Scholar 

  • Rikitake T (1968) Earthquake prediction. Earth Sci Rev 4:245–282

    Google Scholar 

  • Rikitake T (1975) Earthquake precursors. Bull Seismol Soc Am 65:1133–1162

    Google Scholar 

  • Rosen PA, Hensley S, Joughin IR, Li F, Madsen SN, Rodriguez E, Goldstein RM (1998) Synthetic aperture radar interferometry. Proceed IEEE 88(3):333–382

    Google Scholar 

  • Saradjian M, Akhoondzadeh M (2011) Thermal anomalies detection before strong earthquakes (M%3e 6.0) using interquartile, wavelet and Kalman filter methods. Nat Hazards Earth Syst Sci 11:1099–1108

    Google Scholar 

  • Saraf AK, Rawat V, Choudhury S, Dasgupta S, Das J (2009) Advances in understanding of the mechanism for generation of earthquake thermal precursors detected by satellites. Int J Appl Earth Obs Geoinf 11:373–379

    Google Scholar 

  • Spencer JR, Tamppari LK, Martin TZ, Travis LD (1999) Temperatures on Europa from Galileo photopolarimeter-radiometer: nighttime thermal anomalies. Science 284(5419):1514–1516

    Google Scholar 

  • Thomas D (1988) Geochemical precursors to seismic activity. Pure Appl Geophys 126:241–266

    Google Scholar 

  • Thomas J, Masci F, Love JJ (2015) On a report that the 2012 M6: 0 earthquake in Italy was predicted after seeing an unusual cloud formation. Nat Hazards Earth Syst Sci 15:1061–1068

    Google Scholar 

  • Tomás R, Romero R, Mulas J et al (2014) Radar interferometry techniques for the study of ground subsidence phenomena: a review of practical issues through cases in Spain. Environ Earth Sci 71:163–181

    Google Scholar 

  • Tronin A (2000) Thermal IR satellite sensor data application for earthquake research in China. Int J Remote Sens 21(16):3169–3177

    Google Scholar 

  • Tsai C-H, Chen C-W (2010) An earthquake disaster management mechanism based on risk assessment information for the tourism industry-a case study from the island of Taiwan. Tour Manag 31:470–481

    Google Scholar 

  • Tu PF, Xia L, Li HT, Wu SC (2012) PSInSAR technology research and its application on landslide monitoring. In: Paper presented at the applied mechanics and materials

  • Wang T, Zhuang J, Kato T, Bebbington M (2013) Assessing the potential improvement in short-term earthquake forecasts from incorporation of GPS data. Geophys Res Lett 40:2631–2635

    Google Scholar 

  • Yang C-S, Kao S-P, Lee F-B, Hung P-S (2004) Twelve different interpolation methods: a case study of Surfer 8.0. In: Paper presented at the Proceedings of the XXth ISPRS congress

  • Yao Y, Chen P, Wu H, Zhang S, Peng W (2012) Analysis of ionospheric anomalies before the 2011 M w 9.0 Japan earthquake. Chin Sci Bull 57:500–510

    Google Scholar 

  • Yue H, Lay T (2011) Inversion of high-rate (1 sps) GPS data for rupture process of the 11 March 2011 Tohoku earthquake (Mw 9.1). Geophys Res Lett 38:142

    Google Scholar 

  • Zhang Y, Jiang Z, Huang H et al (2014) Thermal anomalies detection before 2013 Songyuan earthquake using MODIS LST data. In: Paper presented at the 2014 IEEE international geoscience and remote sensing symposium (IGARSS)

Download references

Author information

Authors and Affiliations

  1. Department of Geomatics Engineering, University of Tabriz, 29 Bahman Boulevard, Tabriz, Iran

    Zahra Alizadeh Zakaria & Farshid Farnood Ahmadi

Authors
  1. Zahra Alizadeh Zakaria
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Farshid Farnood Ahmadi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Farshid Farnood Ahmadi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Alizadeh Zakaria, Z., Farnood Ahmadi, F. Possibility of an earthquake prediction based on monitoring crustal deformation anomalies and thermal anomalies at the epicenter of earthquakes with oblique thrust faulting. Acta Geophys. 68, 51–73 (2020). https://doi.org/10.1007/s11600-019-00390-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11600-019-00390-3

Keywords

Search

Navigation