Identification of Precursors in InSAR Time Series Using Functional Data Analysis Post-Processing: Demonstration on Mud Volcano Eruptions
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| Udgivet i: | Remote Sensing vol. 16, no. 7 (2024), p. 1191 |
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| Andre forfattere: | , , , , |
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MDPI AG
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| Online adgang: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 024 | 7 | |a 10.3390/rs16071191 |2 doi | |
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| 045 | 2 | |b d20240101 |b d20241231 | |
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| 100 | 1 | |a Fontana, Matteo |u MOX-Department of Mathematics, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy; <email>matteo.fontana@rhul.ac.uk</email> (M.F.); <email>alessandra.menafoglio@polimi.it</email> (A.M.); <email>simone.vantini@polimi.it</email> (S.V.) | |
| 245 | 1 | |a Identification of Precursors in InSAR Time Series Using Functional Data Analysis Post-Processing: Demonstration on Mud Volcano Eruptions | |
| 260 | |b MDPI AG |c 2024 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a One of the most promising applications of satellite data is providing users in charge of land and emergency management with information and data to support decision making for geohazard mapping, monitoring and early warning. In this work, we consider ground displacement data obtained via interferometric processing of satellite radar imagery, and we provide a novel post-processing approach based on a Functional Data Analysis paradigm capable of detecting precursors in displacement time series. The proposed approach appropriately accounts for the spatial and temporal dependencies of the data and does not require prior assumptions on the deformation trend. As an illustrative case, we apply the developed method to the identification of precursors to a mud volcano eruption in the Santa Barbara village in Sicily, southern Italy, showing the advantages of using a Functional Data Analysis framework for anticipating the warning signal. Indeed, the proposed approach is able to detect precursors of the paroxysmal event in the time series of the locations close to the eruption vent and provides a warning signal months before a scalar approach would. The method presented can potentially be applied to a wide range of geological events, thus representing a valuable and far-reaching monitoring tool. | |
| 653 | |a Kinematics | ||
| 653 | |a Datasets | ||
| 653 | |a Emergency management | ||
| 653 | |a Data analysis | ||
| 653 | |a Mud | ||
| 653 | |a Emergency preparedness | ||
| 653 | |a Interferometric synthetic aperture radar | ||
| 653 | |a Forecasting techniques | ||
| 653 | |a Velocity | ||
| 653 | |a Volcanic eruptions | ||
| 653 | |a Volcanoes | ||
| 653 | |a Time series | ||
| 653 | |a Emergency communications systems | ||
| 653 | |a Precursors | ||
| 653 | |a Earthquakes | ||
| 653 | |a Algorithms | ||
| 653 | |a Decision making | ||
| 653 | |a Hypothesis testing | ||
| 653 | |a Satellite imagery | ||
| 653 | |a Radar imaging | ||
| 653 | |a Monitoring | ||
| 653 | |a Eruptions | ||
| 653 | |a Geology | ||
| 653 | |a Sensors | ||
| 653 | |a Geological hazards | ||
| 653 | |a Information management | ||
| 653 | |a Statistical methods | ||
| 700 | 1 | |a Bernardi, Mara Sabina |u MOX-Department of Mathematics, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy; <email>matteo.fontana@rhul.ac.uk</email> (M.F.); <email>alessandra.menafoglio@polimi.it</email> (A.M.); <email>simone.vantini@polimi.it</email> (S.V.) | |
| 700 | 1 | |a Cigna, Francesca |u Italian Space Agency (ASI), Via del Politecnico snc, 00133 Rome, Italy; <email>f.cigna@isac.cnr.it</email> (F.C.); <email>deodato.tapete@asi.it</email> (D.T.) | |
| 700 | 1 | |a Deodato Tapete |u Italian Space Agency (ASI), Via del Politecnico snc, 00133 Rome, Italy; <email>f.cigna@isac.cnr.it</email> (F.C.); <email>deodato.tapete@asi.it</email> (D.T.) | |
| 700 | 1 | |a Menafoglio, Alessandra |u MOX-Department of Mathematics, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy; <email>matteo.fontana@rhul.ac.uk</email> (M.F.); <email>alessandra.menafoglio@polimi.it</email> (A.M.); <email>simone.vantini@polimi.it</email> (S.V.) | |
| 700 | 1 | |a Vantini, Simone |u MOX-Department of Mathematics, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy; <email>matteo.fontana@rhul.ac.uk</email> (M.F.); <email>alessandra.menafoglio@polimi.it</email> (A.M.); <email>simone.vantini@polimi.it</email> (S.V.) | |
| 773 | 0 | |t Remote Sensing |g vol. 16, no. 7 (2024), p. 1191 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
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| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3037631100/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3037631100/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |