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Journal Articles
- 2024
[j7]Sijie Lyu
, Yan Xiang, Benedikt Soja, Ningbo Wang, Wenxian Yu, Trieu-Kien Truong:
Uncertainties of Interpolating Satellite-Specific Slant Ionospheric Delays and Impacts on PPP-RTK. IEEE Trans. Aerosp. Electron. Syst. 60(1): 490-505 (2024)- 2023
- [j6]Linda See, Benedikt Soja, Grzegorz Klopotek, Tobias Sturn, Rudi Weinacker, Santosh Karanam, Ivelina Georgieva, Yuanxin Pan, Laura Crocetti, Markus Rothacher, Vicente Navarro, Steffen Fritz, Ian McCallum:
Collecting volunteered geographic information from the Global Navigation Satellite System (GNSS): experiences from the CAMALIOT project. Int. J. Digit. Earth 16(1): 2818-2841 (2023) - [j5]Junyang Gou, Christine Rösch, Endrit Shehaj, Kangkang Chen, Mostafa Kiani Shahvandi, Benedikt Soja, Markus Rothacher:
Modeling the Differences between Ultra-Rapid and Final Orbit Products of GPS Satellites Using Machine-Learning Approaches. Remote. Sens. 15(23): 5585 (2023) - [j4]Alireza Atabati, Iraj Jazireeyan, Mahdi Alizadeh, Mahmoud Pirooznia, Jakob Flury, Harald Schuh, Benedikt Soja:
Analyzing the Ionospheric Irregularities Caused by the September 2017 Geomagnetic Storm Using Ground-Based GNSS, Swarm, and FORMOSAT-3/COSMIC Data near the Equatorial Ionization Anomaly in East Africa. Remote. Sens. 15(24): 5762 (2023) - 2022
- [j3]Pia Ruttner, Roland Hohensinn, Stefano D'Aronco, Jan Dirk Wegner, Benedikt Soja:
Modeling of Residual GNSS Station Motions through Meteorological Data in a Machine Learning Approach. Remote. Sens. 14(1): 17 (2022) - [j2]Randa Natras, Benedikt Soja, Michael Schmidt:
Ensemble Machine Learning of Random Forest, AdaBoost and XGBoost for Vertical Total Electron Content Forecasting. Remote. Sens. 14(15): 3547 (2022) - 2021
- [j1]Laura Crocetti, Matthias Schartner, Benedikt Soja:
Discontinuity Detection in GNSS Station Coordinate Time Series Using Machine Learning. Remote. Sens. 13(19): 3906 (2021)
Conference and Workshop Papers
- 2024
- [c6]Laura Crocetti, Matthias Schartner, Konrad Schindler, Rochelle Schneider, Benedikt Soja:
Modelling the Troposphere with Global Navigation Satellite Systems, Meteorological Data and Machine Learning. IGARSS 2024: 1689-1692 - [c5]Shuyin Mao, Grzegorz Klopotek, Yuanxin Pan, Benedikt Soja:
Global Ionospheric Modeling Using Multi-GNSS: A Machine Learning Approach. IGARSS 2024: 5774-5777 - 2023
- [c4]Benedikt Soja, Grzegorz Klopotek, Yuanxin Pan, Laura Crocetti, Shuyin Mao, Mudathir Awadaljeed, Markus Rothacher, Linda See, Tobias Sturn, Rudi Weinacker, Ian McCallum, Vicente Navarro:
Machine Learning-Based Exploitation of Crowdsourced GNSS Data for Atmospheric Studies. IGARSS 2023: 1170-1173 - 2022
- [c3]Mostafa Kiani Shahvandi, Junyang Gou, Matthias Schartner, Benedikt Soja:
Data Driven Approaches for the Prediction of Earth's Effective Angular Momentum Functions. IGARSS 2022: 6550-6553 - 2021
- [c2]Mostafa Kiani Shahvandi, Benedikt Soja:
Modified Deep Transformers for GNSS Time Series Prediction. IGARSS 2021: 8313-8316 - [c1]Mostafa Kiani Shahvandi, Benedikt Soja:
Small Geodetic Datasets and Deep Networks: Attention-Based Residual LSTM Autoencoder Stacking for Geodetic Time Series. LOD 2021: 296-307
Coauthor Index
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