امکان‌سنجی استفاده از داده‌های سنجنده مادیس برای برآورد بی‌هنجاری‌های دمایی سطح زمین به‌عنوان پیش‌نشانگر زمین‌لرزه (مطالعه موردی: زلزله سراوان آوریل 2013)

نوع مقاله : پژوهشی

نویسنده

استادیار، گروه فیزیک فضا، مؤسسه ژئوفیزیک، دانشگاه تهران، تهران، ایران

چکیده

دراین مطالعه سری‌های زمانی بی‌هنجاری دمای سطح زمین (LST، Land Surface Temperature) در محدوده فروسرخ گرمایی از تصاویر سنجنده مادیس (MODIS) برای پیش‌نشانگری زمین‌لرزه سراوان با بزرگای 7/5 درروز 16 آوریل 2013 در استان سیستان‌وبلوچستان با بهره‌گیری از الگوریتم‌های پردازش تصویر پنجره مجزا (SWT، SplitWindow Technique) بنام ساب مائو (SobMao) مورد بررسی قرار گرفته است. در این الگوریتم با استفاده از معادله تابش و تعیین ضرایب گسیلمندی زمینی و عبوردهی جوی براساس باندهای فروسرخ نزدیک، مریی و گرمایی بی‌هنجاری در سری‌زمانی پارامتر LST محاسبه و بررسی شد. در این تحقیق تغییرات روزانه پارامتر LST در بازه‌زمانی دو هفته (از روز 100 تا روز 112 در سال 2013) یعنی یک هفته پیش از زمین‌لرزه سراوان و یک هفته پس از آن در منطقه براساس تصاویر مادیس مورد بررسی قرار گرفت. نتایج پردازش تصاویر بیانگر افزایش پارامتر LST یا بی‌هنجاری مثبت گرمایی گسترده در منطقه سراوان پیش از زلزله است، به‌طوری‌که در روز 12 آوریل سال 2013 مصادف با چهار روز پیش از زمین‌لرزه بی‌هنجاری گرمایی به بیشینه مقدار خود رسیده است. نتایج بیانگر وجود بی‌هنجاری‌های مثبت گرمایی در وسعتی از 50 تا 500 کیلومتر طول در منطقه است، که به‌سرعت از لحاظ گسترش منطقه‌ای تغییر کرده است و به‌شدت دچار افت‌وخیز شده است، به‌طوری‌که بیشینه بی‌هنجاری گرمایی دمای سطح زمین چهار روز پیش از زمین‌لرزه ظاهر شده و یک روز پیش از زلزله ناپدید شده است. تغییرات LST در این زلزله، از یک الگوی تقریباً مشابه مطالعه سراف و همکاران (2007) که از حسگر رادیومتر پیشرفته با توان تفکیک بالا استفاده کرده است و نتایج مطالعه فروند (2004) پیروی می‌کند. با توجه به نتایج در زمین‌لرزه سراوان تعیین بی‌هنجاری پارامتر LST می‌توانست به‌عنوان پیش‌نشانگر زلزله مورد توجه قرار گیرد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

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

نویسنده [English]

  • Farahnaz Taghavi
Assistant Professor, Department of Space Physics, Institute of Geophysics, University of Tehran, Tehran, Iran
چکیده [English]

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.

کلیدواژه‌ها [English]

  • Thermal anomalies
  • precursor
  • Saravan earthquake
  • MODIS data
تقوی، ف.، احمدی، ع. و زرگران، ز.، 1395، کاربست روش شبکه‌های عصبی در پیش‌بینی دمای سطح زمین با استفاده از تصاویر حرارتی مادیس، مجله سنجش از دور و  GISایران، 8 (2)، 72-53.
سایت مرکز لرزه نگاری کشوری 1395، (http://www.irsc.ut.ac.ir/IIEES)
عسکری، ق.، حافظی، ن. م.، رحیمی تبار، م. و انصاری، ع.، 1388، بررسی بی‌هنجاری‌های فروسرخ حرارتی قبل از زلزله 23 مهر راور کرمان1383، م. فیزیک زمین و فضا، دوره 35 (4)، 1-16.
گزارش مقدماتی زمین‌لرزه بیست و هفتم فروردین1392 شمال باختری سراوان، 1392، پژوهشگاه بین‌المللی زلزله‌شناسی و مهندسی زلزله.
فاطمی، ب. و رضایی، ی.، 1393، مبانی سنجش از دور، انتشارات آزاده، 296 ص.
Akhoondzadeh, M., 2014, Thermal and TEC anomalies detection using an intelligent hybrid system around the time of the Saravan, Iran, (Mw = 7.7) earthquake of 16 April 2013, Advance in Space Research, http://dx.doi.org/10.1016/j.asr.2013.12.017.
Bhardwaj, A., Singh, S., Sam, L., Joshi, P. K., Bhardwaj, A., Torres, F. J. M., Kumar, R., 2017, A review on remotely sensed land surface temperature anomaly as an earthquake precursor, Int J Appl Earth Obs Geoinformation. http://dx.doi.org/10.1016/ j.jag.2017.08.002
Chmyrev, V., Smith, A., Kataria, D., Nesterov, B., Owen, C., Sammonds, P., Sorokin, V. and Vallianatos, F., 2013, Detection and monitoring of earthquake precursors: TwinSat, a Russia–UK satellite project Available online at www.sciencedirect.com ,Advances in Space Research 52 1135–1145.
Cicerone, R. D., Ebel, J. E. and Briton, J. M., 2009, A systematic compilation of earthquake precursors, Tectonophysics, 476,371-396.
Dash, P., Gottsche, F. M., Olesen, F. S. and Fischer, H., 2002, Land surface temperature and emissivity estimation from passive sensor data: theory and practice-current trends. International Journal of Remote Sensing, 23, 2563–2594.
Filizzola, C., Pergola, N., Pietrapertosa, C. and Tramadol, V., 2004, Robust satellite techniques for seismically active areas monitoring: a sensitivity analysis on September 7, 1999 Athens’s earthquake. Phys. Chem. Earth 29, 517–527.
Freund, F., 2002, Positive hole (P-hole) and positive hole Pairs (PHP): key to understanding many pre-earthquake.
Freund, F., 2004, Toward a better understanding of nonseismic pre-earthquake phenomena. SJSU/NASA Ames Research Center, Earth system and Technology Branch Moffett.
Freund, F., 2007, Pre-earthquake signals – Part II: Flow of battery currents in the crust. Nat. Hazards Earth Syst. Sci., 7, 543–548, 2007.
Freund, F., Takeuchi, A., Lau, B. W. S., Post, Keefner, J., Mellon, J. and Akthem, A. M., 2004, Sress-induced changes in electrical conductivity of igneous rocks and the generation of ground currents. TAO, 15 (3).
Gorny, V. I., Salman, A. G., Tronin, A. A. and Shilin, B. V., 1988, The earth’s outgoing IR radiation as an indicator of seismic activity. Proc. Acad. Sci. USSR 301 (1), 67–69.
Hierarchical Data Format, HDF library, 2017, http://www.hdfgroup.org/HDF-FAQ.html.
Huang, J., Mao, F., Zhou, W. and Zhu, X, 2008, Satellite thermal IR associated with Wenchuan earthquake in China using MODIS data with Wenchuan earthquake in China using MODIS data. The 14th World Conference on Earthquake Engineering October 12-17, 2008, Beijing, China.
Kang, J., Tan, J., Jin , R., Li , X. and Zhang, Y., 2019, Reconstruction of MODIS Land Surface Temperature Products Based on Multi-Temporal Information Remote Sens. 2018, 10(7), 1112; https://doi.org/10.3390/ rs10071112.
Li, Z. L., Tang, B. H., Wu, H., Ren, H., Yan, G., Wan, Z., Trigo, I. F. and Sobrino, J. A., 2013, Satellite-derived land surface temperature: Current status and perspectives. Remote Sens. Environ. 2013, 131, 14–37.
Lisi, M., Filizzola, C., Genzano, N., Paciello, R., Pergola, N. and Tramutoli, V., 2015, Reducing atmospheric noise in RST analysis of TIR satellite radiances for earthquakes prone areas satellite monitoring ,Physics and Chemistry of the Earth, Parts A/B/C Volumes 85–86, 2015, Pages 87-97.
Lu, X., Meng, Q.Y., Gu, X. F., Zhang , X. D., Xie, T. and Geng, F., 2016, Thermal infrared anomalies associated with multi-year earthquakes in the Tibet region based on China’s FY-2E satellite data ,Advance in Space Research,58,989-1001 http://dx.doi.org/10.1016/j.asr.2016.05.038.
Lu, S. L., Shen, X. H., Zou, L. J., Zhang, G. F., Wu, W. Y., Li, C. J. and Mao, Y. J., 2008,. Remote sensing image enhancement method of the fault thermal information based on scale analysis: a case study of Jiangshan–Shaoxing fault between Jinhua and Quzhou of Zhejiang Province, China. Chinese Journal of Geophysics 51, 1047– 1057.
Mao, K., Shi, J., Li, Z. L. and Tang, H., 2007, An RM-NN algorithm for retrieving land surface temperature and emissivity from EOS/MODIS data JGR, VOL. 112, D21102, doi:10.1029 /2007JD008428, 2007.
Mao, k., Shi, J., Li, Z. L., Z., Qin, Z., li, M., Xu, B., 2005, A physics-based statistical algorithm for retrieving land surface temperature from AMSR-E passive microwave data Sci China Ser D-Earth Sci | July 2007 | vol. 50 | no. 7 | 1115-1120.
Mao, K., Qin, Z., Shi, J. and Gong, P., 2005a, A practical split-window algorithm for retrieving land surface temperature from MODIS data, Int. J. Remote Sens., 15, 3181– 3204.
Mao, K., Shi, J., Qin, Z., Gong, P., Liu, W. and  Xu, L., 2005b, A multiple band algorithm for retrieving land-surface temperature and emissivity from MODIS data, in IEEE International Geoscience and Remote Sensing Symposium 2005, vol. 5, edited by S. Liang et al., pp. 3269–3272,
Mao, K., Shi, J., Qin, Z. and  Gong, P., 2005c, An advanced and optimized split-window algorithm for retrieving land-surface temperature from ASTER data, paper presented at Ninth International Symposium on Physical Measurements and Signatures in Remote Sensing, Inst. Of Geogr. Sci. and Nat. Resour. Res., Beijing, China.
Mao, K., Shi, J., Li, Z.L., Qin, Z., Wang, X.F., 2006, A multiple-band algorithm for separating land surface emissivity and temperature from ASTER imagery, in IEEE International Geoscience and Remote Sensing Symposium 2005.
Ma, J. S., Chen, X., Hu, P. and Liu, L., 2010, Spatial-temporal variation of the land surface temperature field and present-day tectonic activity Geoscience Frontiers, Journal homepage: www.elsevier.com/locate/gsf.
MODIS, 2019, http://www.modis.gsfc.nasa.gov.
NASA, 2017, https://ladsweb.nascom. nasa.gov/ data and https://rapidfire.sci. gsfc.nasa.gov/ realtime.
Neteler, M., 2010, Estimating Daily Land Surface Temperatures in Mountainous Environments by Reconstructed MODIS LST Data, Remote Sens. 2010, 2, 333-351; doi:10.3390/rs1020333.
Ouzounov, D., Bryant, N., Logan, T., Pulinets, S. and Taylor, P., 2006, Satellite thermal IR phenomena associated with some of the major earthquakes in 1999–2003. Phys. Chem. Earth 31, 154–163.
Ouzounov, D. and Freund, T., 2004, Mid-infrared emission prior to strong earthquakes analyzed remote sensing data. Adv. Space Res. 33, 268– 273.
Prata, A. J., Caselles, V., Coll, C., Sobrino, J. A., and Ottle, C., 1995, Land surface temperatures derived from satellite, current status and future Prospects, Remote Sensing Review , 10(3-4), 175-224.
Price, J.C., 1984, Land surface temperature measurements from the split window channels of the NOAA 7 Advanced Very High Resolution Radiometer. J. Geophys. Res., 89, 7231-7237.
Pulinets, S.A., Ouzounov, D. Karelin, A.V. Boyarchuk, K.A and Pokhmelnykh, L.A., 2006, The physical nature of thermal anomalies observed before strong earthquakes, Physics and Chemistry of the Earth 31 (2006) 143–153.
Qin, M., Zhang, Y., 2013, Thermal Infrared Anomalies of Several Strong Earthquakes, The Scientific World Journal Volume 2013, Article ID 208407, 11 pages
Qiang, Z., Dian, C., Li, L., Xu, M., Ge, F., Liu, T., Zhao, Y. and Guo, M., 1999, Satellite thermal infrared brightness temperature anomaly image – short term and impending earthquake precursor. Sci. Sinica D., 42, 1-8.
Qiang, Z. J., Xu, X. D., and Dian, C. G.,1991, Thermal infrared anomaly precursor of mpending earthquakes, Chin. Sci. Bull., 36, 319–323,
Qin, Z., Dall Olmo, G., Karnieli, A. and Berliner, P., 2001, Derivation of split window algorithm and its sensitivity analysis for retrieving land surface temperature from NOAA-AVHRR data. J. Geophys. Res., 106(D19): 22655-22670.
Qin, Z. H., Li, W. J., Xu, B., Chen, Z. X., Liu, J., 2004, The estimation of land surface emissivity for LANDSAT TM6.,Remote Sensing for land & Resources 61, 28-32.
Saraf A., K. and Choudhury, S., 2006, Satellite detects pre-earthquake thermal anomalies associated with post major earthquake. Map Asia 2004.
Saraf, A., Choudhury, S., Panda, S. and Dasgupta, S., 2007, Satellite Based Observations of Pre-Earthquake Transient Thermal Anomalies in Iran”, International of Earthquake Engineering and Seismology (IIEES), Vol.14.
Saraf, A., K., Rawat, V., Choudhury, S., Dasgupta, S. and Das, J., 2009, Advances in understanding of the mechanism for generation of earthquake thermal precursors detected by satellitedhttps://doi.org/10.1016/j. jag.2009.07.003
Sobrino, J. A., Jiménez-Munoz, J. C., El-Kharraz, J., Gómez, M., Romaguera, M. and Sòria, G., 2004,“Single-channel and two-channel methods for land surface temperature retrieval from DAIS data and its application to the Barrax site,” Int. J. Remote Sens., vol. 25, no. 1, pp. 215–230.
Sobrino, J. A., Coll, C. and Caselles, V., 1991, Atmospheric correction for land surface temperature using NOAA-11 AVHRR channels 4 and 5. Remote Sens. Environ, 38: 19-34.
Sobrino, J. A., Li, Z. L., Stoll, M. P. and Becker, F., 1994, Improvements in the split-window technique for land surface temperature determination. IEEE Trans. Geosci. Remote Sens., 32(2), 243-253.
Sobrino, J. A. Li, Z.-L, Stoll, M. P and Becker, F., 1996, “Multi-channel and multi-angle algorithms for estimating sea and land surface temperature with ATSR data,” Int. J. Remote Sens., 17(11), 2089–2114.
Sobrino, J.A., Jimenez Muoz, J.C., Soria, G., Romaguera, M., Guanter, L., Moreno, J., Plaza, A. and Martinez, P., 2008, Land Surface Emissivity Retrieval from Different VNIR and TIR Sensors. IEEE Trans. Geosci. Remote Sens. 46, 316–327.
Surkov, V. V., Pokhotelov, O. A., Parrot, M. and Hayakawa, M., 2006, On the origin of stable IR anomalies detected by satellites above seismo-active regions, Physics and Chemistry of the Earth, 31, 164–171.
Saradjian, M. R. and Akhoondzadeh, M., 2011,Thermal anomalies detection before strong earthquakes (M >6.0) using interquartile, wavelet and Kalman filter methods ,Nat. Hazards Earth Syst. Sci., 11, 1099–1108, 2011,www.nat-hazards-earth-syst-sci.net/11/1099/2011/ doi:10.5194/nhess-11-1099-2011.
Tramutoli, V., Aliano, C., Corrado, R., Filizzola, C., Genzano, N., Lisi, M., Martinelli, G. and Ergola, N., 2013, On the possible origin of Thermal Infrared Radiation (TIR) anomalies in earthquake-prone areas observed using Robust Satellite Techniques (RST). Chem. Geol. 339, 157–168.
Tronin, A.A., 2010, Satellite Remote Sensing in Seismology. A Review. Remote Sens. 2010, 2, 124-150;   doi:10.3390 /rs2010124.
Tronin, A. A., 1996, Satellite thermal survey—a new tool for the study of seismoactive regions. International Journal of Remote Sensing 17, 1439–1455.
Tronin, A. A., 2000, Thermal IR satellite sensor data application for earthquake research in China. International Journal of Remote Sensing 21, 3169–3177.
Tronin, A. A., Biagi, P. F., Molchanov, O. A., Khatkevich, Y. M. and Gordeev, E. I., 2004, Temperature variations related to earthquakes from simultaneous observation at the ground stations and by satellites in Kamchatka area. Phys. Chem. Earth 29, 501–504.
Tronin, A. A., Hayakawa, M. and Molchanov, O. A., 2002, Thermal IR satellite data application for earthquake research in Japan and China. J. Geody. 33, 519-534.
Tronin, A. A., 2006, Remote sensing and earthquakes: A review, Physics and Chemistry of the Earth 31 (2006) 138–142.
Venkatanathan, N., Yang,Y. C. and Jun, L., 2017, Observation of abnormal thermal and infrasound signals prior to the earthquakes: a study on Bonin Island earthquake M7.8 (May 30, 2015) Environ Earth Sci (2017) 76:228 DOI 10.1007/s12665-017-6532.
Wan, Z., Li, Z.-L., 1997, A physics-based algorithm for retrieving land-surface emissivity and temperature from EOS/MODIS, data, IEEE Trans. Geosci., Remote Sens., vol. 35, no. 4, pp. 980-996.
Wan, Z., Zhang, Y., Zhang, Q., and Li Z. L., 2004, Quality assessment and validation of the MODIS global land surface temperature INT. J. REMOTE SENSING, Jan, 2004, 25(1), 261–274.
Wu, L., Zhou, Y., Miao, Z. and Qin, K., 2018, Anomaly Identification and Validation for Winter 2017 Iraq and Iran Earthquakes 20th EGU General Assembly, EGU2018, Proceedings from the conference held 4-13 April, 2018 in Vienna, Austria, p.5800.
Yao, Q. L. and Qiang, Z. J., 2012, Thermal infrared anomalies as a precursor of strong earthquakes in the distant future Nat Hazards (2012) 62:991–1003 ,DOI 10.1007/s11069-012-0130-8.
Zhang ,X., Zhang, Y., Tian, X., Zhang, Q. and Tian, J., 2017, Tracking of Thermal Infrared Anomaly before One Strong Earthquake-In the Case of Ms6.2 Earthquake in Zadoi, Qinghai on October 17th, 2016, CTCE2017 IOP Publishing IOP Conf. Series: Journal of Physics: Conf. Series 910 (2017) 012048 doi :10.1088/1742-6596/910/1/012048.
Zhao, S., Qin, Q., Yang, Y., Xiong Y. and Qiu, G., 2009, Comparison of two split-window methods for retrieving land surface temperature from MODIS data ,J. Earth Syst. Sci. 118(4), 345–353.
Zoran, M., Savastru, R., Savastru, D., 2014, Seismic Precursors and Climate Fluctuations Assessment Through Time Series Geospatial and In-situ monitoring Data ,5thEARSeL Workshop on Remote Sensing and Geology "Surveying the Geosphere" 14 ,Warsaw, Poland, 19th – 20th June, 2014.
Zhang, X., Zhang, Y., Tian, X., Zhang, Q. and Tian, J., 2017, Tracking of Thermal Infrared Anomaly before One Strong Earthquake-In the Case of Ms6.2 Earthquake in Zadoi, Qinghai on October 17th, 2016,CTCE2017 IOP Publishing IOP Conf. Series: Journal of Physics: Conf. Series 910 (2017) 012048 doi :10.1088/1742-6596/910/1/012048.