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.


Keywords


2018 Palu earthquake; Postseismic deformation; InSAR; Sentinel-1; GACOS

Full Text:

PDF


References

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

Article Metrics

Abstract views : 1137 | views : 620

Refbacks

  • There are currently no refbacks.




Copyright (c) 2022 hidayat panuntun, Leni Sophia Heliani, Wiwit Suryanto, Cecep Pratama

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

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)

ISSN 2354-9114 (online), ISSN 0024-9521 (print)

Web
Analytics IJG STATISTIC