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Using machine learning techniques to reconstruct the signal observed by the GRACE mission based on AMSR-E microwave data Cover

Using machine learning techniques to reconstruct the signal observed by the GRACE mission based on AMSR-E microwave data

Miscellanea Geographica
Volume 28 (2024): Issue 2 (April 2024)
By: Viktor Szabó,  Katarzyna Osińska-Skotak and  Tomasz Olszak  
Open Access
|Apr 2024

Authors

Viktor Szabó

viktor.szabo.dokt@pw.edu.pl

Department of Geodesy and Geodetic Astronomy, Faculty of Geodesy and Cartography, Warsaw University of Technology, Warsaw, Poland

Katarzyna Osińska-Skotak

katarzyna.osinska-skotak@pw.edu.pl

Department of Photogrammetry, Remote Sensing and Spatial Information Systems, Faculty of Geodesy and Cartography, Warsaw University of Technology, Warsaw, Poland

Tomasz Olszak

tomasz.olszak@pw.edu.pl

Department of Geodesy and Geodetic Astronomy, Faculty of Geodesy and Cartography, Warsaw University of Technology, Warsaw, Poland
DOI: https://doi.org/10.2478/mgrsd-2023-0033 | Journal eISSN: 2084-6118 | Journal ISSN: 0867-6046
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Language: English
Page range: 80 - 86
Submitted on: Jan 20, 2024
Accepted on: Apr 21, 2024
Published on: Apr 30, 2024
Published by: Faculty of Geography and Regional Studies, University of Warsaw
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
GRACE,
AMSR-E,
total water storage anomalies,
soil moisture,
remote sensors
Related subjects:
Geosciences,
Geography,
Geosciences, other

© 2024 Viktor Szabó, Katarzyna Osińska-Skotak, Tomasz Olszak, published by Faculty of Geography and Regional Studies, University of Warsaw
This work is licensed under the Creative Commons Attribution 4.0 License.

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