Geodetic slip model of the November 26, 2019 Albania earthquake estimated from Sentinel-1 TOPS interferometry

Panuntun, Hidayat

doi:10.1016/j.tecto.2021.228814

Cited by 6 publications

(1 citation statement)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…InSAR observation has shown to be a valuable tool for identifying the deformation induced by a variety of geophysical phenomena, including tectonic (e.g., Panuntun, 2021;Qiu, Ji, Liu, & Liu, 2019) and volcanic activities (e.g., Albino, Biggs, Yu, & Li, 2020;Pepe et al, 2019). Continuous GNSS measurement is one of the most popular methods for monitoring surface deformation (X.…”

Section: Introductionmentioning

confidence: 99%

Importance of Tropospheric Correction to C-band InSAR Measurements: Application in the 2018 Palu Earthquake

Panuntun

Heliani²,

Suryanto³

et al. 2022

IJG

View full text Add to dashboard Cite

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.

show abstract