About this Research Topic
InSAR has revolutionized the way scientists can measure the Earth's surface deformation, and its ability to produce maps of surface motions over wide areas with high spatial resolution is still unparalleled. The recent improvements in satellite technologies, computing and methods mean that InSAR has become a standard monitoring technique to study volcanoes, earthquakes and regional-scale tectonics.
Understanding the mechanics of volcanic systems and active faults is important because eruptions and earthquakes can cause immense damage. InSAR is instrumental to studying all sorts of episodic and time-dependent deformation processes. At active volcanoes, magmatic processes linked to the migration of magma toward the surface, inflation and deflation cycles of magma chambers, but also hydrothermal phenomena are probed with InSAR. In seismic regions, InSAR maps of sudden fault motions and creeping faults, transient post-seismic and progressive inter-seismic displacements enable researchers to improve earthquake cycle models. Input from the highly complementary GPS technique or seismicity provides additional constraints to infer where and how much magma is stored under a volcano or the fault kinematics of an earthquake. Traditionally, predictions of analytical or numerical models are compared to InSAR observations to estimate deformation source parameters. Recently deep learning methods have been developed to automatically and rapidly detect and characterize InSAR deformation signals. New challenges continuously arise in InSAR, like mitigation of the recently discovered short-interval phase bias which limits the usage of short-time interferograms.
We aim at collecting original papers based on InSAR observations, models and technical advances for studying active volcanic and tectonic areas worldwide. We welcome contributions dealing with aspects that remain challenging at volcanoes like discriminating between magma, fluids and hydrothermal phenomena, identifying deep magmatic sources, and the influence of viscoelasticity. We encourage papers on regional tectonics and the earthquake cycle, as well as on the challenges in extracting episodic and creeping fault motions or the detection of small fault slip signals. Methodological papers on the usage of deep learning for automated extraction of signals from InSAR time-series and on strategies to mitigate short-interval phase bias in volcano and earthquake studies are welcomed. Multidisciplinary contributions of integration of InSAR measurements with other techniques can also be submitted.
Cover Image by Fredrik Holm.
Understanding the mechanics of volcanic systems and active faults is important because eruptions and earthquakes can cause immense damage. InSAR is instrumental to studying all sorts of episodic and time-dependent deformation processes. At active volcanoes, magmatic processes linked to the migration of magma toward the surface, inflation and deflation cycles of magma chambers, but also hydrothermal phenomena are probed with InSAR. In seismic regions, InSAR maps of sudden fault motions and creeping faults, transient post-seismic and progressive inter-seismic displacements enable researchers to improve earthquake cycle models. Input from the highly complementary GPS technique or seismicity provides additional constraints to infer where and how much magma is stored under a volcano or the fault kinematics of an earthquake. Traditionally, predictions of analytical or numerical models are compared to InSAR observations to estimate deformation source parameters. Recently deep learning methods have been developed to automatically and rapidly detect and characterize InSAR deformation signals. New challenges continuously arise in InSAR, like mitigation of the recently discovered short-interval phase bias which limits the usage of short-time interferograms.
We aim at collecting original papers based on InSAR observations, models and technical advances for studying active volcanic and tectonic areas worldwide. We welcome contributions dealing with aspects that remain challenging at volcanoes like discriminating between magma, fluids and hydrothermal phenomena, identifying deep magmatic sources, and the influence of viscoelasticity. We encourage papers on regional tectonics and the earthquake cycle, as well as on the challenges in extracting episodic and creeping fault motions or the detection of small fault slip signals. Methodological papers on the usage of deep learning for automated extraction of signals from InSAR time-series and on strategies to mitigate short-interval phase bias in volcano and earthquake studies are welcomed. Multidisciplinary contributions of integration of InSAR measurements with other techniques can also be submitted.
Cover Image by Fredrik Holm.
Keywords: InSAR, volcanoes, tectonics, magma migration, faulting
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