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Automated methods for detecting volcanic deformation using Sentinel-1 InSAR time series illustrated by the 2017-2018 unrest at Agung, Indonesia

Research output: Contribution to journalArticle

Original languageEnglish
Number of pages18
JournalJournal of Geophysical Research
Issue number2
Early online date29 Jan 2020
DateAccepted/In press - 26 Jan 2020
DateE-pub ahead of print - 29 Jan 2020
DatePublished (current) - 15 Feb 2020


Radar satellites, such as Sentinel-1, are now able to produce time-series of ground deformation at any volcano around the world, but atmospheric effects still limit the real time detection of unrest at tropical volcanoes. Here, we test two approaches to correct atmospheric errors - phase-elevation correlations and global weather models - and assess the ability of InSAR time-series to detect deformation anomalies using either a fixed threshold or a cumulative sum control chart. We use the 2017-2018 crisis at Agung volcano as a case example because strong atmospheric signals were originally misidentified as true deformation, and obscured the subtle deformation pattern associated with magmatic activity. We assess the Receiver Operating Characteristics (ROC) of each method and found the average area under the ROC curve to be about 0.5 for the uncorrected data (corresponding to no discrimination capability), around 0.8 after combined atmospheric corrections (weather model and phase-elevation approaches), and more than 0.95 using a cumulative sum control chart (where 1 corresponds to ideal separation between classes). Our results retrospectively show that uplift could have been detected to a 95% level of confidence for both ascending and descending time series by October 2017, 15 days after the start of the seismic swarm and one month prior to the eruption. Thus our approach successfully flags anomalous behavior without relying on visual inspection or selection of an arbitrary threshold, and hence shows potential as a monitoring tool for volcano observatories globally.

    Research areas

  • Sentinel-1 time series, atmospheric corrections, weather model, volcanic unrest, real-time monitoring, Agung volcano

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