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.
Highlights
We focus on generating an automated differential interferometric SAR (DInSAR) time series processing routine that is integrated with Global Navigation Satellite System (GNSS) data into a unified deformation field to provide more constrained deformation rates and vector measurements related to volcanic activity
We present the unified DInSAR and GNSS time series and compare them to the original datasets
By comparing the integrated product against the original GNSS time series, we find that information in the horizontal direction is slightly improved and information in the vertical direction is significantly enhanced once fused with LOS DInSAR measurements
Summary
Earthquakes, and tsunamis occur over numerous spatial and temporal scales. These phenomena are often studied individually, there is frequently interconnectivity between disaster types. Concentrated swarms of earthquakes, elevated readings of gas emission, and increased ground motion over volcanic regions may indicate an impending eruption [1,2,3,4,5,6,7,8]. Most active volcanoes around the world are monitored using geodetic data sets such as Synthetic Aperture Radar (SAR) and Global Navigation Satellite System (GNSS) data, in conjunction with other ground-based instruments, with the goal of providing early warning for major eruptions and reducing risk to nearby populations or infrastructure [9]. While several studies have attempted to forecast or model potential volcano hazards using remote sensing techniques [2,10,11,12,13,14,15,16], there is currently no single framework in place that simultaneously consolidates geodetic data from multiple sensors, freely provides scientists with near real-time continuous time series products and is capable of distinguishing and broadcasting geophysical events
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