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Detection of neotectonic motions in Germany based on GNSS and machine learning

Authors
/persons/resource/nhung

Nhung,  Le
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;
1.1 Space Geodetic Techniques, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/maennelb

Männel,  B.
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;
1.1 Space Geodetic Techniques, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Sakic,  Pierre
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

/persons/resource/deng

Deng,  Z.
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;
1.1 Space Geodetic Techniques, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/parker

Usifoh,  Saturday
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;
1.1 Space Geodetic Techniques, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

/persons/resource/schuh

Schuh,  H.
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;
1.1 Space Geodetic Techniques, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

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Citation

Nhung, L., Männel, B., Sakic, P., Deng, Z., Usifoh, S., Schuh, H. (2023): Detection of neotectonic motions in Germany based on GNSS and machine learning, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-1113


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5018104
Abstract
Space geodetic techniques, particularly Global Navigation Satellite Systems (GNSS), have contributed significantly to neotectonic research on continental plates over the last decades, allowing us to observe crustal motions in all three spatial directions. Meanwhile, the previous studies of German neotectonics have mainly focused on several areas associated with the European Cenozoic rift system. Thus, this study investigates the entire German territory to identify the neotectonic motion characteristics based on GNSS-integrated data and Machine Learning (ML). Parallelly, high-precise GNSS time series processing techniques are applied to reflect actual motions. Our results show that the German Earth’s crust tends to uplift, especially in the active graben regions moving with a speed of almost +1.0 mm/yr. In contrast, the local subsidence of around -0.8 mm/yr is concentrated in the large groundwater extraction regions and the river basins such as the Rhine, Ems, Elbe, Northern Oder, and Danube. In the horizontal movements, the German Earth’s crust moves with an average intra-plate velocity of ~0.8 mm/yr, while some places reach up to ~2.5 mm/yr. Furthermore, ML detects the noticeable surface deformation regions, namely Lower Rhine Bay, Upper Rhine Graben, Eifel volcano, and Thuringian-Vogtland slate mountains. Our findings have filled the overall picture of German neotectonics and provide a valuable material source for infrastructure management toward sustainable development in Germany.