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Open AccessArticle

Combining InSAR and GNSS to Track Magma Transport at Basaltic Volcanoes

1
University Grenoble Alpes, University Savoie Mont Blanc, CNRS, IRD, IFSTTAR, ISTerre, 38000 Grenoble, France
2
Laboratoire Magmas et Volcans, Univ. Blaise Pascal, CNRS, IRD, OPGC, 63000 Aubière, France
3
University Jean Monnet, University de Lyon, 42000 Saint-Etienne, France
4
Institut de Physique du globe de Paris, Université de Paris, CNRS, UMR 7154, F-97418 La Plaine des Cafres, France
5
Observatoire Volcanologique du Piton de la Fournaise, Institut de Physique du Globe de Paris, CNRS, UMR 7154, F-97418 La Plaine des Cafres, France
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(19), 2236; https://doi.org/10.3390/rs11192236
Received: 26 August 2019 / Revised: 19 September 2019 / Accepted: 20 September 2019 / Published: 25 September 2019
(This article belongs to the Special Issue InSAR for Earth Observation)
The added value of combining InSAR and GNSS data, characterized by good spatial coverage and high temporal resolution, respectively, is evaluated based on a specific event: the propagation of the magma intrusion leading to the 26 May 2016 eruption at Piton de la Fournaise volcano (Reunion Island, France). Surface displacement is a non linear function of the geometry and location of the pressurized source of unrest, so inversions use a random search, based on a neighborhood algorithm, combined with a boundary element modeling method. We first invert InSAR and GNSS data spanning the whole event (propagation phase and eruption) to determine the final geometry of the intrusion. Random search conducted in the inversion results in two best-fit model families with similar data fits. Adding the same time-period GNSS dataset to the inversions does not significantly modify the results. Even when weighting data to provide even contributions, the fit is systematically better for descending than ascending interferograms, which might indicate an eastward flank motion. Then, we invert the GNSS time series in order to derive information on the propagation dynamics, validating our approach using a SAR image acquired during the propagation phase. We show that the GNSS time series can only be used to correctly track the magma propagation when the final intrusion geometry derived from InSAR and GNSS measurements is used as an a priori. A new method to extract part of a mesh, based on the representation of meshes as graphs, better explains the data and better accounts for the opening of the eruptive fissure than a method based on the projection of a circular pressure sources. Finally, we demonstrate that the temporal inversion of GNSS data strongly favors one family of models over an other for the final intrusion, removing the ambiguity inherent in the inversion of InSAR data. View Full-Text
Keywords: InSAR; GNSS; Piton de la Fournaise; dike propagation; inversion; joint inversion InSAR; GNSS; Piton de la Fournaise; dike propagation; inversion; joint inversion
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Smittarello, D.; Cayol, V.; Pinel, V.; Froger, J.-L.; Peltier, A.; Dumont, Q. Combining InSAR and GNSS to Track Magma Transport at Basaltic Volcanoes. Remote Sens. 2019, 11, 2236.

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