Browse > Article
http://dx.doi.org/10.7780/kjrs.2021.37.1.11

Surface Deformation Measurement of the 2020 Mw 6.4 Petrinja, Croatia Earthquake Using Sentinel-1 SAR Data  

Achmad, Arief Rizqiyanto (Department of Smart Regional Innovation, Kangwon National University)
Lee, Chang-Wook (Department of Science Education, Kangwon National University)
Publication Information
Korean Journal of Remote Sensing / v.37, no.1, 2021 , pp. 139-151 More about this Journal
Abstract
By the end of December 2020, an earthquake with Mw about 6.4 hit Sisak-Moslavina County, Croatia. The town of Petrinja was the most affected region with major power outage and many buildings collapsed. The damage also affected neighbor countries such as Bosnia and Herzegovina and Slovenia. As a light of this devastating event, a deformation map due to this earthquake could be generated by using remote sensing imagery from Sentinel-1 SAR data. InSAR could be used as deformation map but still affected with noise factor that could problematize the exact deformation value for further research. Thus in this study, 17 SAR data from Sentinel-1 satellite is used in order to generate the multi-temporal interferometry utilize Stanford Method for Persistent Scatterers (StaMPS). Mean deformation map that has been compensated from error factors such as atmospheric, topographic, temporal, and baseline errors are generated. Okada model then applied to the mean deformation result to generate the modeled earthquake, resulting the deformation is mostly dominated by strike-slip with 3 meter deformation as right lateral strike-slip. The Okada sources are having 11.63 km in length, 2.45 km in width, and 5.46 km in depth with the dip angle are about 84.47° and strike angle are about 142.88° from the north direction. The results from this modeling can be used as learning material to understand the seismic activity in the latest 2020 Petrinja, Croatia Earthquake.
Keywords
StaMPS; InSAR; Okada Model; Earthquake; Croatia;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Storchak, D.A., D. Di Giacomo, E.R. Engdahl, J. Harris, I. Bondár, W.H.K. Lee, P. Bormann, and A. Villasenor, 2015.The ISC-GEM Global Instrumental Earthquake Catalogue (1900-2009): Introduction, Physics of the Earth and Planetary Interiors, 239: 48-63, https://doi.org/10.1016/j.pepi.2014.06.009   DOI
2 Tobita, M., 2016.Combined logarithmic and exponential function model for fitting postseismic GNSS time series after 2011 Tohoku-Oki earthquake, Earth, Planets and Space, 68(1): 41, https://doi.org/10.1186/s40623-016-0422-4   DOI
3 Ustaszewski, K., M. Herak, B. Tomljenovie, D. Herak, and S. Matej, 2014. Neotectonics of the Dinarides-Pannonian Basin transition and possible earthquake sources in the Banja Luka epicentral area, Journal of Geodynamics, 82: 52-68, https://doi.org/10.1016/j.jog.2014.04.006   DOI
4 Weston, J., A.M.G. Ferreira, and G.J. Funning, 2012. Systematic comparisons of earthquake source models determined using InSAR and seismic data, Tectonophysics, 532-535: 61-81, https://doi.org/10.1016/j.tecto.2012.02.001   DOI
5 Wilkinson, M.W., K.J.W. McCaffrey, R.R. Jones, G.P. Roberts, R.E. Holdsworth, L.C. Gregory, Walters, R.J. Wedmore, L., H. Goodall, and F. Iezzi, 2017. Near-field fault slip of the 2016 Vettore Mw 6.6 earthquake (CentralItaly) measured using low-cost GNSS, Scientific Reports, 7(1): 1-7, https://doi.org/10.1038/s41598-017-04917-w   DOI
6 Wright, T.J., B.E. Parsons, J.A. Jackson, M. Haynes, E.J. Fielding, P.C. England, and P.J. Clarke, 1999. Source parameters of the 1 October 1995 Dinar (Turkey) earthquake from SAR interferometry and seismic bodywave modelling, Earth and Planetary Science Letters, 172(1-2): 23-37, https://doi.org/10.1016/S0012-821X(99)00186-7   DOI
7 Pawluszek-Filipiak, K. and A. Borkowski, 2020. Integration of DInSAR and SBAS Techniques to Determine Mining-Related Deformations Using Sentinel-1 Data: The Case Study of Rydultowy Mine in Poland, Remote Sensing, 12(2): 242, https://doi.org/10.3390/rs12020242   DOI
8 Pikija, M., 1987. Basic geological map of SFRY 1:100000, List Sisak L-33-93. Croatian Geological Survey (HGI-CGS), Belgrade, HRV (in Croatian).
9 Sousa, J.J., A.J. Hooper, R.F. Hanssen, L.C. Bastos, and A.M. Ruiz, 2011. Persistent Scatterer InSAR: A comparison of methodologies based on a model of temporal deformation vs. spatial correlation selection criteria, Remote Sensing of Environment, 115(10): 2652-2663, https://doi.org/10.1016/j.rse.2011.05.021   DOI
10 Wright, T.J., Z. Lu, and C. Wicks, 2003. Source model for the Mw 6.7, 23 October 2002, Nenana Mountain Earthquake (Alaska) from InSAR, Geophysical Research Letters, 30(18): 1974, https://doi.org/10.1029/2003GL018014   DOI
11 Hooper,A.J., P. Segall, and H. Zebker, 2007. Persistent scatterer interferometric synthetic aperture radar for crustal deformation analysis, with application to Volcán Alcedo, Galapagos, Journal of Geophysical Research: Solid Earth, 112(7): B07407, https://doi.org/10.1029/2006JB004763   DOI
12 Xu, X., D.T. Sandwell, and B. Smith-Konter, 2020. Coseismic displacements and surface fractures from sentinel-1 InSAR: 2019 Ridgecrest earthquakes, Seismological Research Letters, 91(4): 1979-1985, https://doi.org/10.1785/0220190275   DOI
13 Hakim, W.L., A.R. Achmad, and C.-W. Lee, 2020. Land Subsidence Susceptibility Mapping in Jakarta Using Functional and Meta-Ensemble Machine Learning Algorithm Based on Time-Series InSAR Data, Remote Sensing, 12(21): 3627, https://doi.org/10.3390/rs12213627   DOI
14 Hooper, A.J., 2006. Persistent Scatterer Radar Interferometry for Crustal Deformation Studies and Modeling of Volcanic Deformation, Stanford University, Stanford, CA, USA.
15 Hooper, A.J., 2008. A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches, Geophysical Research Letters, 35(16):L16302, https://doi.org/10.1029/2008GL034654   DOI
16 Bruyninx, C., J. Legrand, A. Fabian, and E. Pottiaux, 2019. GNSS metadata and data validation in the EUREF Permanent Network, GPS Solutions, 23(4): 106, https://doi.org/10.1007/s10291-019-0880-9   DOI
17 Okada, Y., 1985. Surface deformation due to shear and tensile faults in a half-space, Bulletin of the Seismological Society of America, 75(4): 1135-1154.   DOI
18 Osmanoglu, B., F. Sunar, S. Wdowinski, and E. Cabral-Cano, 2016. Time series analysis of InSAR data: Methods and trends, ISPRS Journal of Photogrammetry and Remote Sensing, 115: 90-102, https://doi.org/10.1016/j.isprsjprs.2015.10.003   DOI
19 Achmad, A.R., S. Lee, S. Park, J. Eom, and C.-W. Lee, 2020. Estimating the potential risk of the Mt. Baekdu Volcano using a synthetic interferogram and the LAHARZ inundation zone, Geosciences Journal, 24(6): 755-768, https://doi.org/10.1007/s12303-020-0032-9   DOI
20 Hooper, A.J., 2010. A statistical-cost approach to unwrapping the phase of InSAR time series, http://radar.tudelft.nl/-ahooper/Hooper_FRINGE_2009.pdf, Accessed on Dec. 16, 2020.
21 Hooper, A.J., D. Bekaert, K. Spaans, and M. Arikan, 2012. Recent advances in SAR interferometry time series analysis for measuring crustal deformation, Tectonophysics, 514-517: 1-13, https://doi.org/10.1016/J.TECTO.2011.10.013   DOI
22 Hooper, A.J., H. Zebker, P. Segall, and B. Kampes, 2004. A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers, Geophysical Research Letters, 31(23):L23611, https://doi.org/10.1029/2004GL021737   DOI
23 Nur, A.S., A.R. Achmad, and C.-W. Lee, 2020. Land Subsidence Measurement in Reclaimed Coastal Land: Noksan UsingC-Band Sentinel-1 Radar Interferometry, Journal of Coastal Research, 102(sp1): 218-223, https://doi.org/10.2112/SI102-027.1   DOI
24 Lee, C.-W., Z. Lu, and H.S. Jung, 2012. Simulation of time-series surface deformation to validate a multi-interferogram InSAR processing technique, International Journal of Remote Sensing, 33(22): 7075-7087, https://doi.org/10.1080/01431161.2012.700137   DOI
25 Marquardt, D.W., 1963. An Algorithm for Least Squares Estimation of Nonlinear Parameters, Journal of the Society for Industrial and Applied Mathematics, 11(2): 431-441, https://doi.org/10.1137/0111030   DOI
26 Ministry of Internal Affairs of Republic of Croatia, 2020. Earthquake near Petrinja, https://civilnazastita.gov.hr/vijesti/potres-kod-petrinje-3357/3357,Accessed on Jan. 25, 2021 (In Croatian).
27 Ganas, A.,P. Elias, S. Valkaniotis, V. Tsironi, I. Karasante, and P. Briole, 2021. Petrinja earthquake moved crust 10 feet, https://doi.org/10.32858/temblor.156, Accessed on Feb. 8, 2021.
28 Dodangeh, E., M. Panahi, F. Rezaie, S. Lee, D. TienBui, C.-W. Lee, and B. Pradhan, 2020. Novel hybrid intelligence models for flood-susceptibility prediction: Meta optimization of the GMDH and SVR models with the genetic algorithm and harmony search, Journal of Hydrology, 590: 125423, https://doi.org/10.1016/j.jhydrol.2020.125423   DOI
29 Fadhillah, M.F., A.R. Achmad, and C.-W. Lee, 2020. Integration of InSAR Time-Series Data and GIS to Assess Land Subsidence along Subway Lines in the Seoul Metropolitan Area, South Korea, Remote Sensing, 12(21): 3505, https://doi.org/10.3390/rs12213505   DOI
30 Ferretti, A., C. Prati, and F. Rocca, 2001. Permanent scatterers in SAR interferometry, IEEE Transactions on Geoscience and Remote Sensing, 39(1): 8-20, https://doi.org/10.1109/36.898661   DOI
31 Crosetto, M., O. Monserrat, M. Cuevas-Gonzalez, N. Devanthery, and B. Crippa, 2016. Persistent Scatterer Interferometry: A review, ISPRS Journal of Photogrammetry and Remote Sensing, 115: 78-89, https://doi.org/10.1016/j.isprsjprs.2015.10.011   DOI
32 Geng, T., X. Xie, R. Fang, X. Su, Q. Zhao, G. Liu, H. Li, C. Shi, and J. Liu, 2016. Real-time capture of seismic waves using high-rate multi-GNSS observations: Application to the 2015 Mw 7.8 Nepal earthquake, Geophysical Research Letters, 43(1): 161-167, https://doi.org/10.1002/2015GL067044   DOI
33 Hakim, W.L., A.R. Achmad, J. Eom, and C.-W. Lee, 2020.Land Subsidence Measurement of Jakarta Coastal Area Using Time Series Interferometry with Sentinel-1 SAR Data, Journal of Coastal Research, 102(sp1): 75-81, https://doi.org/10.2112/SI102-010.1   DOI
34 Chen, C.W. and H. Zebker, 2002. Phase unwrapping for large SAR interferograms: Statistical segmentation and generalized network models, IEEE Transactions on Geoscience and Remote Sensing,40(8):1709-1719,https://doi.org/10.1109/TGRS.2002.802453   DOI
35 Croatian Geological Survey, 2021. Press release of the Croatian Geological Survey (HGI-CGS), Hrvatski geoloski institut, https://www.hgicgs.hr/press-release-of-the-croatian-geologicalsurvey-hgi-cgs/, Accessed on Jan. 25, 2021.