304
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Association of land surface temperature anomalies from GOES/ABI, MSG/SEVIRI, and Himawari-8/AHI with land earthquakes between 2010 and 2021

, , &
Article: 2324982 | Received 12 Sep 2023, Accepted 25 Feb 2024, Published online: 09 Apr 2024

References

  • Adil MA, Şentürk E, Shah M, Naqvi NA, Saqib M, Abbasi AR. 2021. Atmospheric and ionospheric disturbances associated with the M > 6 earthquakes in the East Asian sector: a case study of two consecutive earthquakes in Taiwan. J Asian Earth Sci. 220:104918. doi: 10.1016/j.jseaes.2021.104918.
  • Boudriki Semlali B-E, Amrani CE. 2022. A Stream processing software for air quality satellite datasets. In: Kacprzyk J, Balas VE, Ezziyyani M, editors. Advanced intelligent systems for sustainable development (AI2SD’2020). Vol. 1417. Cham, Switzerland: Springer International Publishing; p. 839–853. [accessed 2022 February 10th]. doi: 10.1007/978-3-030-90633-7_71.
  • Boudriki Semlali B-E, El Amrani C, Ortiz G. 2020a. SAT-ETL-integrator: an extract-transform-load software for satellite big data ingestion. J Appl Rem Sens.14(01):1. doi: 10.1117/1.JRS.14.018501.
  • Boudriki Semlali B-E, El Amrani C, Ortiz G. 2020b. Hadoop paradigm for satellite environmental big data processing. Int J Agric Environ Inform Syst. 11(1):23–47. doi: 10.4018/IJAEIS.2020010102.
  • Boudriki Semlali B-E, Freitag F. 2021. SAT-hadoop-processor: a distributed remote sensing big data processing software for earth observation applications. Appl Sci. 11(22):10610. doi: 10.3390/app112210610.
  • Boudriki Semlali BE, Molina C, Park H, Camps A. 2022. Study of land surface temperature anomalies associated to earthquakes using GOES data. IGARSS 2022–2022 IEEE International Geoscience and Remote Sensing Symposium, 17-22 July 2022. Kuala Lumpur, Malaysia: IEEE; p. 5732–5735. doi: 10.1109/IGARSS46834.2022.9884887.
  • Boudriki Semlali B-E, Molina C, Park H, Camps A. 2023. First results on the systematic search of land surface temperature anomalies as earthquakes precursors. Remote Sens. 15(4):1110. doi: 10.3390/rs15041110.
  • Buchhorn M, Lesiv M, Tsendbazar N-E, Herold M, Bertels L, Smets B. 2020. Copernicus global land cover layers—collection 2. Remote Sens. 12(6):1044. doi: 10.3390/rs12061044.
  • Chakraborty S, Sasmal S, Chakrabarti SK, Bhattacharya A. 2018. Observational signatures of unusual outgoing longwave radiation (OLR) and atmospheric gravity waves (AGW) as precursory effects of May 2015 Nepal earthquakes. J Geodyn. 113:43–51. doi: 10.1016/j.jog.2017.11.009.
  • Chen C-H, Lin L-C, Yeh T-K, Wen S, Yu H, Yu C, Gao Y, Han P, Sun Y-Y, Liu J-Y, et al. 2020. Determination of epicenters before earthquakes utilizing far seismic and GNSS data: insights from ground vibrations. Remote Sensing. 12(19):3252. https://doi.org/10.3390/rs12193252.
  • Choi YY, Suh MS. 2018. Development of Himawari-8/advanced Himawari imager (AHI) land surface temperature retrieval algorithm. Remote Sens. 10(12):2013. doi: 10.3390/rs10122013.
  • Dey S, Singh RP. 2003. Surface latent heat flux as an earthquake precursor. Nat Hazards Earth Syst Sci. 3(6):749–755. doi: 10.5194/nhess-3-749-2003.
  • Dobrovolsky IP, Zubkov SI, Miachkin VI. 1979. Estimation of the size of earthquake preparation zones. PAGEOPH. 117(5):1025–1044. doi: 10.1007/BF00876083.
  • Ghosh S, Chowdhury S, Kundu S, Sasmal S, Politis DZ, Potirakis SM, Hayakawa M, Chakraborty S, Chakrabarti SK. 2021. Unusual surface latent heat flux variations and their critical dynamics revealed before strong earthquakes. Entropy. 24(1):23. doi: 10.3390/e24010023.
  • Hammerle A, Meier F, Heinl M, Egger A, Leitinger G. 2017. Implications of atmospheric conditions for analysis of surface temperature variability derived from landscape-scale thermography. Int J Biometeorol. 61(4):575–588. doi: 10.1007/s00484-016-1234-8.
  • Hassini A, Belbachir AH. 2013. Hardware and software consideration to use near real time MSG-SEVIRI and NOAA-AVHRR images. 2013 11th International Symposium on Programming and Systems (ISPS). Algiers, Algeria: IEEE; p. 12–16. [accessed 2020 Apr 2]. doi: 10.1109/ISPS.2013.6581487.
  • Hassini A, Benabadji N, Belbachir AH. 2009. Acquisition and treatment of MSG satellite images. In: SETIT 2009. TUNISIA: IEEE; p. 6.
  • Hayakawa M, Izutsu J, Schekotov A, Yang S-S, Solovieva M, Budilova E. 2021. Lithosphere–atmosphere–ionosphere coupling effects based on multiparameter precursor observations for February–March 2021 earthquakes (M∼7) in the offshore of Tohoku area of Japan. Geosciences. 11(11):481. doi: 10.3390/geosciences11110481.
  • Himawari-8 Real-time Web - NICT. 2023. [accessed June 18]. https://himawari8.nict.go.jp/.
  • IDDR2018_Economic Losses.pdf. 2018. https://www.unisdr.org/2016/iddr/IDDR2018_Economic%20Losses.pdf.
  • Jiao ZH, Zhao J, Shan X. 2018. Pre-seismic anomalies from optical satellite observations: a review. Nat Hazards Earth Syst Sci. 18(4):1013–1036. doi: 10.5194/nhess-18-1013-2018.
  • Jing F, Singh RP, Cui Y, Sun K. 2020. Microwave brightness temperature characteristics of three strong earthquakes in Sichuan Province, China. IEEE J Sel Top Appl Earth Observ Remote Sens. 13:513–522. doi: 10.1109/JSTARS.2020.2968568.
  • Lukić T, Marić P, Hrnjak I, Gavrilov MB, Mladjan D, Zorn M, Komac B, Milošević Z, Marković SB, Sakulski D, et al. 2017. Forest fire analysis and classification based on a Serbian case study. AGS. 57(1):51–63. doi: 10.3986/AGS.918.
  • Marchetti D, De Santis A, D'Arcangelo S, Poggio F, Piscini A, A. Campuzano S, De Carvalho WV. 2019. Pre-earthquake chain processes detected from ground to satellite altitude in preparation of the 2016–2017 seismic sequence in Central Italy. Remote Sens Environ. 229:93–99. doi: 10.1016/j.rse.2019.04.033.
  • Meng X, Cheng J, Zhao S, Liu S, Yao Y. 2019. Estimating land surface temperature from landsat-8 data using the NOAA JPSS enterprise algorithm. Remote Sens. 11(2):155. doi: 10.3390/rs11020155.
  • Molina C, Boudriki Semlali B-E, Park H, Camps A. 2021. Possible evidence of earthquake precursors observed in ionospheric scintillation events observed from spaceborne GNSS-R data. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS. [place unknown]; p. 8680–8683. doi: 10.1109/IGARSS47720.2021.9555020.
  • Molina C, Boudriki-Semlali B-E, Park H, Camps A. 2022. A preliminary study on ionospheric scintillation anomalies detected using GNSS-R data from NASA CYGNSS mission as possible earthquake precursors. 22. doi: 10.1109/IGARSS46834.2022.9883701.
  • NASA EOSDIS Worldview. 2019. [accessed December 6, 2019]. https://worldview.earthdata.nasa.gov/
  • NOAA CLASS Website. 2020. [accessed January 15, 2020]. https://www.bou.class.noaa.gov/saa/products/welcome.
  • Number of Deaths from Earthquakes. 2021. Our world in data [Internet]. [accessed September 21, 2021]. https://ourworldindata.org/grapher/earthquake-deaths.
  • Pablos M, Piles M, Sanchez N, Gonzalez-Gambau V, Vall-Llossera M, Camps A, Martinez-Fernandez J. 2014. A sensitivity study of land surface temperature to soil moisture using in-situ and spaceborne observations. In: 2014 IEEE Geoscience and Remote Sensing Symposium [Internet]. Quebec City, QC: IEEE; [accessed 2023 Dec 8]; p. 3267–3269. https://doi.org/10.1109/IGARSS.2014.6947176.
  • Panda SK, Choudhury S, Saraf AK, Das JD. 2007. MODIS land surface temperature data detects thermal anomaly preceding October 8th 2005 Kashmir earthquake. Int J Remote Sens. 28(20):4587–4596. doi: 10.1080/01431160701244906.
  • Pavlidou E, van der Meijde M, van der Werff H, Hecker C. 2018. Time series analysis of land surface temperatures in 20 earthquake cases worldwide. Remote Sens. 11(1):61. doi: 10.3390/rs11010061.
  • Prakash R, Srivastava HN. 2015. Thermal anomalies in relation to earthquakes in India and its neighbourhood. Curr Sci. 108(11):13.
  • QGIS Software Website. 2020. [accessed May 2, 2020]. https://www.qgis.org/fr/site/.
  • Qiang Z, Xu X, Dian C. 1997. Case 27 thermal infrared anomaly precursor of impending earthquakes. PAGEOPH. 149(1):159–171. doi: 10.1007/BF00945166.
  • Rasul A, Omar LW. 2020. Land surface temperature anomalies detection for the strong earthquakes in 2018. ARO. 8(2):15–21. doi: 10.14500/aro.10591.
  • Remove Polynomial Trend MATLAB Detrend. 2023. [accessed June 5, 2023]. [https://www.mathworks.com/help/matlab/ref/detrend.html.
  • Rew R, Davis G. 1990. NetCDF: an interface for scientific data access. IEEE Comput Grap Appl. 10(4):76–82. doi: 10.1109/38.56302.
  • GRASS GIS Manual. 2023. r.resamp.filter. [accessed June 5, 2023]. https://grass.osgeo.org/grass82/manuals/r.resamp.filter.html.
  • Santis AD, Marchetti D, Pavón-Carrasco FJ, Cianchini G, Perrone L, Abbattista C, Alfonsi L, Amoruso L, Campuzano SA, Carbone M. 2019. OPEN precursory worldwide signatures of earthquake occurrences on Swarm satellite data. doi: 10.1038/s41598-019-56599-1.
  • Saradjian MR, Akhoondzadeh M. 2011. Thermal anomalies detection before strong earthquakes (Mw > 6.0) using interquartile, wavelet and Kalman filter methods. Nat Hazards Earth Syst Sci. 11(4):1099–1108. doi: 10.5194/nhess-11-1099-2011.
  • Schmetz J, Pili P, Tjemkes S, Just D, Kerkmann J, Rota S, Ratier A. 2002. An introduction to meteosat second generation (MSG). Bull Amer Meteor Soc. 83(7):992–992. doi: 10.1175/1520-0477(2002)083<0977:AITMSG>2.3.CO;2.
  • Sekertekin A, Inyurt S, Yaprak S. 2020. Pre-seismic ionospheric anomalies and spatio-temporal analyses of MODIS Land surface temperature and aerosols associated with Sep, 24 2013 Pakistan Earthquake. J Atmos Sol Terr Phys. 200:105218. doi: 10.1016/j.jastp.2020.105218.
  • Shah M, Ehsan M, Abbas A, Ahmed A, Jamjareegulgarn P. 2022. Possible thermal anomalies associated with global terrestrial earthquakes during 2000–2019 based on MODIS-LST. IEEE Geosci Remote Sensing Lett. 19:1–5. doi: 10.1109/LGRS.2021.3084930.
  • Soleimani Vosta Kolaei F, Akhoondzadeh M. 2018. A comparison of four methods for extracting Land Surface Emissivity and Temperature in the Thermal Infrared Hyperspectral Data. EOGE. 2(1):56–63. [Internet]. [accessed June 18th 2023] doi: 10.22059/eoge.2018.239666.1011.
  • Stănică DA. 2022. Anomalous geomagnetic signal emphasized before the Mw8.2 coastal Alaska earthquake, occurred on July 29th 2021. Entropy. 24(2):274. doi: 10.3390/e24020274.
  • STAR GOES Calibration Validation. Instrument status - GOES-16 ABI satellite - INST-CAL IR statistics. 2022. [accessed November 28, 2022]. https://www.star.nesdis.noaa.gov/GOESCal/G16_ABI_INST_CAL_daily_allmode.php.
  • Sun D, Pinker RT. 2003. Estimation of land surface temperature from a Geostationary Operational Environmental Satellite (GOES-8). J Geophys Res. 108(D11):4326. doi: 10.1029/2002JD002422.
  • Tramutoli V. 2015. From Visual Comparison to Robust Satellite Techniques: 30 years of thermal infrared satellite data analyses for the study of earthquakes preparation phases. BGTA. [Internet]. [accessed 2022 April 11th]. doi: 10.4430/bgta0149.
  • USGS Earthquakes. 2021. [accessed August 8, 2021]. https://www.usgs.gov/natural-hazards/earthquake-hazards/earthquakes.
  • Wan W, Liu B, Zeng Z, Chen X, Wu G, Xu L, Chen X, Hong Y. 2019. Using CYGNSS data to monitor China’s flood inundation during typhoon and extreme precipitation events in 2017. Remote Sens. 11(7):854. doi: 10.3390/rs11070854.
  • Wu L, Qin K, Liu S. 2012. GEOSS-Based Thermal Parameters Analysis for Earthquake Anomaly Recognition. Proc IEEE. 100(10):2891–2907. doi: 10.1109/JPROC.2012.2184789.
  • Xu XD, Xu XM, Wang Y. 2000. Satellite infrared anomaly before the Nantou M S = 7.6 earthquake in Taiwan, China. Acta Seimol Sin. 13(6):710–713. doi: 10.1007/s11589-000-0074-z.
  • Yan Y, Mao K, Shi J, Piao S, Shen X, Dozier J, Liu Y, Ren H, Bao Q. 2020. Driving forces of land surface temperature anomalous changes in North America in 2002–2018. Sci Rep. 10(1):6931. doi: 10.1038/s41598-020-63701-5.
  • Zhang Y, Guo X, Zhong M, Shen W, Li W, He B. 2010. Wenchuan earthquake: brightness temperature changes from satellite infrared information. Chin Sci Bull. 55(18):1917–1924. doi: 10.1007/s11434-010-3016-8.
  • Zhong M, Shan X, Zhang X, Qu C, Guo X, Jiao Z. 2020. Thermal infrared and ionospheric anomalies of the 2017 Mw6.5 Jiuzhaigou earthquake. Remote Sens. 12(17):2843. doi: 10.3390/rs12172843.
  • Zhu C, Jiao Z, Shan X, Zhang G, Li Y. 2019. Land surface temperature variation following the 2017 Mw 7.3 Iran earthquake. Remote Sens. 11(20):2411. doi: 10.3390/rs11202411.
  • Zhu L, Suomalainen J, Liu J, Hyyppä J, Kaartinen H, Haggren H. 2018. A review: remote sensing sensors. In: Rustamov RB, Hasanova S, Zeynalova MH, editors. Multi-purposeful application of geospatial data. London: InTech. [accessed 2018 December 15th]. doi: 10.5772/intechopen.71049.
  • Zoran M. 2012. MODIS and NOAA-AVHRR l and surface temperature data detect a thermal anomaly preceding the March 11th 2011 Tohoku earthquake. Int J Remote Sens. 33(21):6805–6817. doi: 10.1080/01431161.2012.692833.