* Corresponding Author
Importance of Tropospheric Correction to C-band InSAR Measurements: Application in the 2018 Palu Earthquake
https://doi.org/10.22146/ijg.68984 Hidayat Panuntun(1*), Leni Sophia Heliani(2), Wiwit Suryanto(3), Cecep Pratama(4)
(1) Geomatics Laboratory, Department of Earth Technology, Vocational College, Universitas Gadjah Mada
(2) Department of Geodetic Engineering, Faculty of Engineering, Universitas Gadjah Mada
(3) Seismology Research Group, Geophysics, Universitas Gadjah Mada
(4) Department of Geodetic Engineering, Faculty of Engineering, Universitas Gadjah Mada
(*) Corresponding Author
Abstract
Long-term InSAR-based observations are prone to atmospheric delay interference. The active-phase signals emitted and recorded back by sensors during imaging are easily disturbed by the electron content in the ionospheric layer and the water vapor content in the tropospheric layer. Given that the short wavelength of the C-band used by Sentinel-1 is more sensitive to tropospheric delay than to ionospheric delay, in this work, we utilized InSAR Sentinel-1 data to observe the postseismic deformation that occurred following the 2018 Palu earthquake and to evaluate the effect of tropospheric delay on the estimated interferogram time series. The cloud computation of Looking into Continent from Space with Synthetic Aperture Radar (LiCSAR) and LiCSBAS was used to generate interferograms and analyze the time series. Here the atmospheric delay was modeled by using Generic Atmospheric Correction Online Service (GACOS) and removed from the generated interferograms. Results showed that the annual velocity and cumulative line-of-sight (LOS) displacement were refined by correcting the atmospheric delay. Specifically, by applying GACOS, the standard deviation of the generated interferograms decreased by up to 76.6%. GNSS observations were utilized to verify the improvement due to the removal of tropospheric noise. We found that LOS displacement with GACOS correction better fitted the GNSS observation than LOS displacement without GACOS correction. Therefore, atmospheric correction plays an important role in long-term InSAR-based observations, especially in avoiding any bias in the interpretation of the estimated time series.
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Albino, F., Biggs, J., Yu, C., & Li, Z. (2020). Automated Methods for Detecting Volcanic Deformation Using Sentinel-1 InSAR Time Series Illustrated by the 2017–2018 Unrest at Agung, Indonesia. Journal of Geophysical Research: Solid Earth, 125(2), e2019JB017908. doi:https://doi.org/10.1029/2019JB017908
Bacques, G., de Michele, M., Foumelis, M., Raucoules, D., Lemoine, A., & Briole, P. (2020). Sentinel optical and SAR data highlights multi-segment faulting during the 2018 Palu-Sulawesi earthquake (Mw 7.5). Scientific Reports, 10(1), 9103. doi:10.1038/s41598-020-66032-7
Bekaert, D. P. S., Hooper, A., & Wright, T. J. (2015). A spatially variable power law tropospheric correction technique for InSAR data. Journal of Geophysical Research: Solid Earth, 120(2), 1345-1356. doi:https://doi.org/10.1002/2014JB011558
Berardino, P., Fornaro, G., Lanari, R., & Sansosti, E. (2002). A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Transactions on Geoscience and Remote Sensing, 40(11), 2375-2383. doi:10.1109/TGRS.2002.803792
Fang, J., Xu, C., Wen, Y., Wang, S., Xu, G., Zhao, Y., & Yi, L. (2019). The 2018 Mw 7.5 Palu Earthquake: A Supershear Rupture Event Constrained by InSAR and Broadband Regional Seismograms. Remote Sensing, 11(11), 1330.
Fattahi, H., & Amelung, F. (2015). InSAR bias and uncertainty due to the systematic and stochastic tropospheric delay. Journal of Geophysical Research: Solid Earth, 120(12), 8758-8773. doi:https://doi.org/10.1002/2015JB012419
Fattahi, H., Simons, M., & Agram, P. (2017). InSAR Time-Series Estimation of the Ionospheric Phase Delay: An Extension of the Split Range-Spectrum Technique. IEEE Transactions on Geoscience and Remote Sensing, 55(10), 5984-5996. doi:10.1109/TGRS.2017.2718566
He, L., Feng, G., Li, Z., Feng, Z., Gao, H., & Wu, X. (2019). Source parameters and slip distribution of the 2018 Mw 7.5 Palu, Indonesia earthquake estimated from space-based geodesy. Tectonophysics, 772, 228216. doi:https://doi.org/10.1016/j.tecto.2019.228216
He, X., Montillet, J.-P., Fernandes, R., Bos, M., Yu, K., Hua, X., & Jiang, W. (2017). Review of current GPS methodologies for producing accurate time series and their error sources. Journal of Geodynamics, 106, 12-29. doi:https://doi.org/10.1016/j.jog.2017.01.004
Hu, Y., Bürgmann, R., Freymueller, J. T., Banerjee, P., & Wang, K. (2014). Contributions of poroelastic rebound and a weak volcanic arc to the postseismic deformation of the 2011 Tohoku earthquake. Earth, Planets and Space, 66(1), 106. doi:https://doi.org/10.1186/1880-5981-66-106
Jaya, A., Nishikawa, O., & Jumadil, S. (2019). Distribution and morphology of the surface ruptures of the 2018 Donggala–Palu earthquake, Central Sulawesi, Indonesia. Earth, Planets and Space, 71(1), 144. doi:10.1186/s40623-019-1126-3
Kang, Y., Lu, Z., Zhao, C., Xu, Y., Kim, J.-w., & Gallegos, A. J. (2021). InSAR monitoring of creeping landslides in mountainous regions: A case study in Eldorado National Forest, California. Remote Sensing of Environment, 258, 112400. doi:https://doi.org/10.1016/j.rse.2021.112400
Lazecký, M., Spaans, K., González, P. J., Maghsoudi, Y., Morishita, Y., Albino, F., Elliott, J., Greenall, N., Hatton, E., Hooper, A., Juncu, D., McDougall, A., Walters, R. J., Watson, C. S., Weiss, J. R., & Wright, T. J. (2020). LiCSAR: An Automatic InSAR Tool for Measuring and Monitoring Tectonic and Volcanic Activity. Remote Sensing, 12(15). doi:10.3390/rs12152430
Li, Z., Cao, Y., Wei, J., Duan, M., Wu, L., Hou, J., & Zhu, J. (2019). Time-series InSAR ground deformation monitoring: Atmospheric delay modeling and estimating. Earth-Science Reviews, 192, 258-284. doi:https://doi.org/10.1016/j.earscirev.2019.03.008
Li, Z. W., Xu, W. B., Feng, G. C., Hu, J., Wang, C. C., Ding, X. L., & Zhu, J. J. (2012). Correcting atmospheric effects on InSAR with MERIS water vapour data and elevation-dependent interpolation model. Geophysical Journal International, 189(2), 898-910. doi:https://doi.org/10.1111/j.1365-246X.2012.05432.x
Liang, C., Agram, P., Simons, M., & Fielding, E. J. (2019). Ionospheric Correction of InSAR Time Series Analysis of C-band Sentinel-1 TOPS Data. IEEE Transactions on Geoscience and Remote Sensing, 57(9), 6755-6773. doi:10.1109/TGRS.2019.2908494
Mears, C. A., Wang, J., Smith, D., & Wentz, F. J. (2015). Intercomparison of total precipitable water measurements made by satellite-borne microwave radiometers and ground-based GPS instruments. Journal of Geophysical Research: Atmospheres, 120(6), 2492-2504. doi:https://doi.org/10.1002/2014JD022694
Morishita, Y., Lazecky, M., Wright, T. J., Weiss, J. R., Elliott, J. R., & Hooper, A. (2020). LiCSBAS: An Open-Source InSAR Time Series Analysis Package Integrated with the LiCSAR Automated Sentinel-1 InSAR Processor. Remote Sensing, 12(3), 424.
Nijholt, N., Simons, W. J. F., Efendi, J., Sarsito, D. A., & Riva, R. E. M. (2021). A Transient in Surface Motions Dominated by Deep Afterslip Subsequent to a Shallow Supershear Earthquake: The 2018 Mw7.5 Palu Case. Geochemistry, Geophysics, Geosystems, 22(4), e2020GC009491. doi:https://doi.org/10.1029/2020GC009491
Panuntun, H. (2021). Geodetic slip model of the November 26, 2019 Albania earthquake estimated from Sentinel-1 TOPS interferometry. Tectonophysics, 807, 228814. doi:https://doi.org/10.1016/j.tecto.2021.228814
Panuntun, H., Miyazaki, S., Fukuda, Y., & Orihara, Y. (2018). Probing the Poisson's ratio of poroelastic rebound following the 2011 Mw 9.0 Tohoku earthquake. Geophysical Journal International, 215(3), 2206-2221. doi:10.1093/gji/ggy403
Pepe, S., De Siena, L., Barone, A., Castaldo, R., D'Auria, L., Manzo, M., Casu, F., Fedi, M., Lanari, R., Bianco, F., & Tizzani, P. (2019). Volcanic structures investigation through SAR and seismic interferometric methods: The 2011–2013 Campi Flegrei unrest episode. Remote Sensing of Environment, 234, 111440. doi:https://doi.org/10.1016/j.rse.2019.111440
Pratama, C., Meilano, I., Sunarti, E., Haksama, S., & Sulistiyo, M. D. (2020, 24-26 June 2020). Data-Driven of Time Series Decomposition on Estimating Geodetic Secular Motion Around Palu- Koro Fault Zone. Paper presented at the 2020 8th International Conference on Information and Communication Technology (ICoICT).
Qiu, J., Ji, L., Liu, L., & Liu, C. (2019). Seismogenic fault and tectonic significance of 1996 Karakoram Pass earthquake (Ms 7.1) based on InSAR. Earth, Planets and Space, 71(1), 108. doi:10.1186/s40623-019-1089-4
Socquet, A., Hollingsworth, J., Pathier, E., & Bouchon, M. (2019). Evidence of supershear during the 2018 magnitude 7.5 Palu earthquake from space geodesy. Nature Geoscience, 12(3), 192-199. doi:10.1038/s41561-018-0296-0
Song, X., Zhang, Y., Shan, X., Liu, Y., Gong, W., & Qu, C. (2019). Geodetic Observations of the 2018 Mw 7.5 Sulawesi Earthquake and Its Implications for the Kinematics of the Palu Fault. Geophysical Research Letters, 46(8), 4212-4220. doi:https://doi.org/10.1029/2019GL082045
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. doi:https://doi.org/10.1186/s40623-016-0422-4
USGS. (2018). Earthquake Catalog Released by U.S Geological Survey. Retrieved from https://earthquake.usgs.gov/earthquakes/eventpage/us1000h3p4/executive
Watson, A. R., Elliott, J. R., & Walters, R. J. (2022). Interseismic Strain Accumulation Across the Main Recent Fault, SW Iran, From Sentinel-1 InSAR Observations. Journal of Geophysical Research: Solid Earth, 127(2), e2021JB022674. doi:https://doi.org/10.1029/2021JB022674
Yu, C., Li, Z., Penna, N. T., & Crippa, P. (2018). Generic Atmospheric Correction Model for Interferometric Synthetic Aperture Radar Observations. Journal of Geophysical Research: Solid Earth, 123(10), 9202-9222. doi:https://doi.org/10.1029/2017JB015305
Yu, C., Penna, N. T., & Li, Z. (2017). Generation of real-time mode high-resolution water vapor fields from GPS observations. Journal of Geophysical Research: Atmospheres, 122(3), 2008-2025. doi:https://doi.org/10.1002/2016JD025753
DOI: https://doi.org/10.22146/ijg.68984
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Copyright (c) 2022 hidayat panuntun, Leni Sophia Heliani, Wiwit Suryanto, Cecep Pratama
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Accredited Journal, Based on Decree of the Minister of Research, Technology and Higher Education, Republic of Indonesia Number 225/E/KPT/2022, Vol 54 No 1 the Year 2022 - Vol 58 No 2 the Year 2026 (accreditation certificate download)
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