Integration of DInSAR Time Series and GNSS Data for Continuous Volcanic Deformation Monitoring and Eruption Early Warning Applications

Abstract

With approximately 800 million people globally living within 100 km of a volcano, it is essential that we build a reliable observation system capable of delivering early warnings to potentially impacted nearby populations. Global Navigation Satellite System (GNSS) and satellite Synthetic Aperture Radar (SAR) document comprehensive ground motions or ruptures near, and at, the Earth’s surface and may be used to detect and analyze natural hazard phenomena. These datasets may also be combined to improve the accuracy of deformation results. Here, we prepare a differential interferometric SAR (DInSAR) time series and integrate it with GNSS data to create a fused dataset with enhanced accuracy of 3D ground motions over Hawaii island from November 2015 to April 2021. We present a comparison of the raw datasets against the fused time series and give a detailed account of observed ground deformation leading to the May 2018 and December 2020 volcanic eruptions. Our results provide important new estimates of the spatial and temporal dynamics of the 2018 Kilauea volcanic eruption. The methodology presented here can be easily repeated over any region of interest where an SAR scene overlaps with GNSS data. The results will contribute to diverse geophysical studies, including but not limited to the classification of precursory movements leading to major eruptions and the advancement of early warning systems.

High‐Resolution Finite Fault Slip Inversion of the 2019 Ridgecrest Earthquake Using 3D Finite Element Modeling

“…(2008), and Corsa et al. (2022). The data integration method is based on a Bayesian statistical approach in which an unknown parameter of an energy function is estimated by searching for its minimum (Stan, 2001).…”

“…The geodetic data used for the inversion includes differential interferometric synthetic aperture radar (DInSAR) LOS displacements from ascending and descending Sentinel-1 A/B (S1A/B) interferograms, 3D displacements derived from pixel offsets from the ascending and descending S1A/B SLCs, and static GNSS 3D displacements from NGL GPS Coseismic Displacement 5 min Solutions. We incorporate all of the geodetic displacement data by expanding on the DInSAR-GNSS velocity integration method developed by Samsonov and Tiampo (2006) and described thoroughly in Samsonov (2007), Samsonov et al (2007), Samsonov et al (2008), andCorsa et al (2022). The data integration method is based on a Bayesian statistical approach in which an unknown parameter of an energy function is estimated by searching for its minimum (Stan, 2001).…”

Advanced technologies for landslide monitoring

“…Another significant geotechnical application of DInSAR is the monitoring of volcanic deformation - (Corsa, 2022). Volcanoes are complex geological features that can exhibit various forms of deformation prior to, during, and after volcanic eruptions.…”

Decision-making fusion of InSAR technology and offset tracking to study the deformation of large gradients in mining areas-Xuemiaotan mine as an example

“…Many studies in the literature have demonstrated the effectiveness of the D-InSAR technique in monitoring the rapid displacement of the terrain over short periods of time (Corsa et al, 2022;Liu et al, 2022;Valerio et al, 2022). However, the inability to remove the atmospheric phase has led to a decrease in the accuracy of the D-InSAR monitoring process.…”