Geodesy
Lida Koshki; Behzad Voosoghi; Seyyed Reza Ghaffari-Razin
Abstract
Extended Abstract IntroductionEarthquake every year in the world, especially in a seismic country like Iran, causes huge human and financial losses. Earthquake prediction has become one of the great challenges of scientists in recent decades. One of the new methods is the evaluation of anomalies ...
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Extended Abstract IntroductionEarthquake every year in the world, especially in a seismic country like Iran, causes huge human and financial losses. Earthquake prediction has become one of the great challenges of scientists in recent decades. One of the new methods is the evaluation of anomalies in the ionospheric parameters before the earthquake. The parameter investigated in this method is the total electron content (TEC). The study areas in this paper are the Ahar-Varzaghan earthquake with a magnitude of 6.5 and 6.3, the Sarpol Zahab earthquake with a magnitude of 6.3. In the Ahar-Varzaghan earthquake, the observations of 6 GPS stations and in the Sarpol Zahab earthquake, the observations of 5 GPS stations of the IGS network were used to calculate the ionosphere TEC. Short time Fourier transform (STFT) along with statistical parameters of mean and standard deviation have been used to detect of ionosphere time series anomalies. Also, geomagnetic and weather indicators KP, Dst, F10.7, Vsw (plasma velocity), Ey (magnetic field) and IMFBz (interplanetary magnetic field) have been investigated and analyzed to know the conditions of the days before the earthquake.Materials & Methods In recent years, the spectral analysis of ionospheric anomalies using the STFT method and its application in earthquake forecasting has become popular. The research results show that spectral methods can be a useful and reliable tool in further analysis, and the STFT method can be evaluated as a successful method for detecting ionosphere anomalies, which is also compatible with classical methods. Also, STFT is a powerful tool for processing a time series without the need for average and median values, so it can be used for other studies such as navigation, geophysics, geology and climatology. STFT is used as a modified version of the classical Fourier transform to obtain the frequency information of a signal in the time domain. This method provides the analysis of a small part of the signal at a certain time through windowing the signal. In STFT, the signal with a constant time-frequency resolution and with the same window length in all frequencies is divided into smaller parts, Fourier transform is applied on it and finally the output will be presented in two time-frequency dimensions. As a result, it is possible to obtain information about when and with what frequency each signal occurred.Results & Discussion In the Sarpol Zahab earthquake and in both classic and STFT methods, anomalies were observed on 309, 314 and 323 DOY, before the earthquake. The amount of these anomalies in the ionosphere time series was in the 0.058 to 5.44 TECU. The parameters related to solar and geomagnetic activities were also investigated in the days before and after the earthquake. Considering that the solar and geomagnetic activities (as an important factor in creating anomalies in the ionosphere time series) were calm in the days before the earthquake, these detected anomalies can be attributed to the earthquake. However, in the Ahar-Varzaghan earthquake and using both methods, in 5 to 15 days before the earthquake, anomalies of about 0.13 to 1.4 TECU were observed. In the days before the Ahar-Varzaghan earthquake, there were almost undisturbed conditions on most days, and therefore it cannot be said with certainty that the observed anomalies are completely related to the earthquake. The results of this paper showed that the STFT method is a powerful tool for spectral analysis without the need for values such as average or median. This feature of STFT is its strength compared to classical methods; because independence from these values minimizes the sources of error related to them (abnormalities, sudden variations in the ionosphere such as annual, semi-annual and seasonal variations). It is important to mention that the STFT method is more accurate in calm solar and geomagnetic conditions and provides high accuracy results.ConclusionThe results show that for the Ahar-Varzaghan earthquake, there are anomalies on the 11, 12, 13 and 5 days before the earthquake. But for the Sarpol Zahab earthquake, anomalies can be seen 6, 7, 13 and 21 days before the earthquake. The analyzes of this paper show that if all the geomagnetic and weather parameters before the earthquake are investigated, the existing anomalies can be directly observed by analyzing the time series of the ionosphere with the STFT method. It is important that on days when geomagnetic conditions and calm weather are not prevailing, the occurrence of earthquake cannot be considered as the cause of anomalies detected in the ionosphere time series.
sina saber mahani; Mohammadreza Sepahvand
Abstract
Extended Abstract
Since Iran is located on the Alpine-Himalayan seismicbelt and it has high seismicity, study of earthquake seismologyis necessary. Part of alpine-Himalayan seismic belt is Iranplateau that demonstrates high seismicity behavior and it has uniquedeformation.
Seismotectonic studies indicate ...
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Extended Abstract
Since Iran is located on the Alpine-Himalayan seismicbelt and it has high seismicity, study of earthquake seismologyis necessary. Part of alpine-Himalayan seismic belt is Iranplateau that demonstrates high seismicity behavior and it has uniquedeformation.
Seismotectonic studies indicate a high density of active fault existencein this plateau. In all of Iran seismotectonic regime, eastof Iran seismotectonic zone due to the presence of strike slipfault system and occurrence of large earthquakes has a greatimportance. Destructive earthquakes such as 6.6Mw Bam (2006)and 6.7 MwRigan (2010) revealed high potential of earthquakeoccurrence. Intended area in this study is Rigan that is located in Kerman province in Iran. This area has important faults such as Kahurak, Bam, Nosratabad, Shahdad, Guk, Golbaf, Sirch and Sabzevaran which have high seismicity.
In this paper, we consideredcloud formation as earthquake precursor for Mohammad Abad-Rigan’s earthquake (2011) that is known less. Thermal precursor was also consideredin this study. According to the existing theories, Rises in stresscan produce initial fracture in the region. Therefore, with the rise intemperature, water evaporation in the pores of stone is created. Whenvapor has appropriate condition (for example; lower temperature and existingenough water), it convert to clouds. One of the fantastic features of this phenomenon is that, these clouds cannot move in the presence of wind, Because of the steady source of their generations. This fact is a distinguishable thing for recognizing thiscloud among other clouds. In the first part, panchromatic images of62days before the event were taken and then theserow images were geo-referenced. Thus, earthquake clouds were digitally extracted andthe results were superposed on the topographic map of the intended region. It should also be mentioned that earthquake clouds were detected 10 days priorto the earthquake (January 17th).A period of 10 days is a suitabletime for making decisions in decision making organizations such as, Governorates, Municipalities, etc. Verdict basedon earthquake clouds is not enough for a good conclusion about earthquake occurring, and it is necessarythat we apply other precursors and pre-indicators, one of which is thermalinfrared that has great results.
In another part of the study, temperature content of thermal bands (bands 31 and 32) ofMODIS is extracted and Land Surface Temperature (LST) time serieswere created. Temperature variations are always considered as animportant and effective factor in earthquake phenomenon studying. Thermal anomalycan be seen within 1-24 days before earthquake and thetemperature increases 5 to12 degrees and then return to the previousmode after the earthquake. Some other researchers presented the increaseof 2 to 10 degrees. The idea that earthquake may be interrelated withtemperature was proved by applying it in Russia, China and Japan. However, notice that thermal anomaly may occur due to otherreasons except earthquake. When it is because of earthquake, actuallyit is because of the stress existing in the underground layersand changes in soil properties. Zuji et al. (1990) provedthat gases such as methane, carbon dioxide and hydrogen are releasedfrom soil cracks before earthquake which lead to intensification ofchlorofluorocarbons (CFC) and magnetic fields of the earth. There aresome other theories about this phenomenon such as piezoelectric andexpansion forces of the elastic strain that increase temperature.
Aftergetting images from NASA website and preprocessing them by deduction ofAir temperature time series from LST time series, atmospheric effectsthat exist because of the weather condition is eliminated. Obtainedsignal was some noisy. In the next step, the waveletas a powerful filter is applied to time series. Forextracting Interpretable results, Statistical test such as standard deviation mustbe perform on filtered time series. Standard deviation (ST) cancreate normal limited area. By using limited area that producedby ST, thermal anomaly is detected 2 days prior tothe earthquake. Also, with colorization of thermal images and then creationof visual time series, strike of fault line is found.
Finally, by Comparingthe earthquake cloud line, focal mechanismandhigh temperature zone, high correlation was found. These results showthe observed cloud related to Rigan’s earthquake and also showthe high temperature zone related to earthquake event.
Resultsof this study can be used in two aspects, oneof which is the application in early warning system and the otheris the application in geology usage. Second usage helps geophysicist andgeologist to detect hidden and caused fault.