Description: Das Projekt "H2020-EU.1.1. - Excellent Science - European Research Council (ERC) - (H2020-EU.1.1. - Wissenschaftsexzellenz - Für das Einzelziel "Europäischer Forschungsrat (ERC)"), Geodetic data assimilation: Forecasting Deformation with InSAR (GEO-4D)" wird/wurde gefördert durch: Kommission der Europäischen Gemeinschaften Brüssel. Es wird/wurde ausgeführt durch: Universite Paris VI, Ecole Normale Superieure.Recent space-based geodetic measurements of ground deformation suggest a paradigm shift is required in our understanding of the behaviour of active tectonic faults. The classic view of faults classified in two groups - the locked faults prone to generate earthquakes and the creeping faults releasing stress through continuous aseismic slip - is now obscured by more and more studies shedding light on a wide variety of seismic and aseismic slip events of variable duration and size. What physical mechanism controls whether a tectonic fault will generate a dynamic, catastrophic rupture or gently release energy aseismically? Answering such a fundamental question requires a tool for systematic and global detection of all modes of slip along active faults. The launch of the Sentinel 1 constellation is a game changer as it provides, from now on, systematic Radar mapping of all actively deforming regions in the world with a 6-day return period. Such wealth of data represents an opportunity as well as a challenge we need to meet today. In order to expand the detection and characterization of all slip events to a global scale, I will develop a tool based on machine learning procedures merging the detection capabilities of all data types, including Sentinel 1 data, to build time series of ground motion. The first step is the development of a geodetic data assimilation method with forecasting ability toward the first re-analysis of active fault motion and tectonic phenomena. The second step is a validation of the method on three faults, including the well-instrumented San Andreas (USA) and Longitudinal Valley faults (Taiwan) and the North Anatolian Fault (NAF, Turkey). I will deploy a specifically designed GPS network along the NAF to compare with outputs of our method. The third step is the intensive use of the algorithm on a global scale to detect slip events of all temporal and spatial scales for a better understanding of the slip behaviour along all active continental faults.
SupportProgram
Origin: /Bund/UBA/UFORDAT
Tags: Radar ? Wild ? Türkei ? USA ? Textilchemikalien ? Kartographie ? Lehrmittel ? Stress ? Tektonik ? Geodaten ? Beleuchtung ? Berechnungsverfahren ? Daten ? Energie ? Störfall ? Studie ? Werkzeugmaschine ? Zeitreihe ? Erdbeben ? Bedarf ? Erdoberfläche ? Licht ? Planung ? Tal ? Gebiet ? Globale Aspekte ? Assimilation [Biologie] ? Bemessung ? Global Positioning System ? H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) ? Netz ? Sentinel ?
License: cc-by-nc-nd/4.0
Language: Englisch/English
Time ranges: 2018-01-01 - 2022-12-31
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