Feasibility study of using MODIS data to estimate thermal anomalies as earthquake precursor (Case study: Saravan earthquake April 2013)

Document Type : Research


Assistant Professor, Department of Space Physics, Institute of Geophysics, University of Tehran, Tehran, Iran


In this study, thermal infrared data from Moderate-resolution Imaging Spectroradiometer (MODIS) sensor with spatial resolution of 1000m are selected to investigate about the Land Surface Temperature (LST) anomalies before Saravan earthquake. Many studies have already documented an extensive elevated thermal anomaly near epicenters that appear within dozens of days before the earthquakes such as (Qiang, et al., 1991, 1999; Tronin, et al., 2002; Tronin, 2006; Saraf, et al., 2007; Huang, et al., 2008; Ma, et al., 2010; Yao and Qiang, 2012; Wu, et al., 2012; Tramutoli, et al., 2013; Akhoondzadeh, M., 2014; Lisi, et al., 2015; Lu, et al., 2016; Venkatanathan, et al., 2017; Zhang, et al., 2017). Satellite-based thermal infrared (TIR) data linked to the LST through the radiative transfer equation. The earthquake of Saravan in Sistan and Baluchistan province occured on April 16, 2013, at Iran Standard Time (local time) of 15:14 pm (Lat: 28.04°, Lon: 62.03°). In this paper, a practical split-window algorithm as named Sob Mao (Mao, et al., 2005) is used to retrieve LST from MODIS data which involves two essential transmittance and emissivity parameters. The general radiance transfer equation for remote sensing of LST is formulated as follows:
Bi (Ti)=τi (θ)[εi Bi (TS )+(1-εi ) Ii↓ ]+Ii↑                                                           (1)
Where Ts is the LST, Ti is the brightness temperature in channel i, ,τ_i (θ) is the atmosphere transmittance in band i at viewing direction θ (zenith angle from nadir), and ε_i is the ground emissivity. Bi (Ts) is the ground radiance, andI_(i↓) and I_(i↑) are the down. welling and upwelling path radiances, respectively. Time series of LST parameter (Eq2.) has been analyzed to examine about the probable LST fluctuations before and after these events.
LST=Ts=C32 (B31+D31 )-C31 (B32+D32 )/(C32 A31-C31 A32 )                                    (2)
The results show positive deviation of >10 °C four days before the main shock on April 12, 2013 (102 of day of year) and it disappears a few days after the main event. The time scale of the observed variations is a one week before the onset of the seismic event. The results confirmed the existence of an anomaly in LST data before for Saravan earthquakes. A comparison of the maps in Fig. 2 reveals that the thermal anomaly had been formed four days before the main shock on April 12, 2013 (i.e. the 102 day of the year) and two days before an aftershock of Mw 5 on April 18 (i.e. the 108 day of the year). The anomalies formed are usually of 50 to 500 km length. They are often of drastic fluctuations. To ensure that the reasons of these anomalies are well understood, the meteorological maps and the model outputs in the weekly time intervals around the time of the event were examined for the Saravan area. Time series of Saravan temperature and the pressure maps are also investigated, as it can be seen no significant meteorological phenomenon was observed that can cause such drastic changes. The LST map results illustrate that before the Saravan earthquake, a large anomaly of LST is created and that these anomalies follow the mentioned trend in other scientific papers, therefore it could be considered as an earthquake precursor.


Main Subjects

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