Articles | Volume 37, issue 4
https://doi.org/10.5194/angeo-37-699-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/angeo-37-699-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Regular paper
| 
12 Aug 2019
Regular paper |
| 12 Aug 2019
| 12 Aug 2019
High-resolution vertical total electron content maps based on multi-scale B-spline representations
Deutsches Geodätisches Forschungsinstitut der Technischen Universität München, Arcisstraße 21, 80333 Munich, Germany
Michael Schmidt
Deutsches Geodätisches Forschungsinstitut der Technischen Universität München, Arcisstraße 21, 80333 Munich, Germany
Eren Erdogan
Deutsches Geodätisches Forschungsinstitut der Technischen Universität München, Arcisstraße 21, 80333 Munich, Germany
Barbara Görres
Bundeswehr GeoInformation Centre (BGIC), Euskirchen, Germany
Florian Seitz
Deutsches Geodätisches Forschungsinstitut der Technischen Universität München, Arcisstraße 21, 80333 Munich, Germany
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22 citations as recorded by crossref.
- Improving estimates of the ionosphere during geomagnetic storm conditions through assimilation of thermospheric mass density I. Fernandez-Gomez et al. 10.1186/s40623-022-01678-3
- Operational Multi‐GNSS Global Ionosphere Maps at GFZ Derived From Uncombined Code and Phase Observations A. Brack et al. 10.1029/2021RS007337
- Global mapping of total electron content from GNSS observations for updating IRI-Plas model V. Shubin & T. Gulyaeva 10.1016/j.asr.2021.09.032
- Computational and numerical simulations for the nonlinear fractional Kolmogorov–Petrovskii–Piskunov (FKPP) equation M. Khater et al. 10.1088/1402-4896/ab76f8
- Two‐Way Assessment of Ionospheric Maps Performance Over the Brazilian Region: Global Versus Regional Products G. Jerez et al. 10.1029/2022SW003252
- High-Resolution Ionosphere Corrections for Single-Frequency Positioning A. Goss et al. 10.3390/rs13010012
- Intercalibration of the Plasma Density Measurements in Earth's Topside Ionosphere A. Smirnov et al. 10.1029/2021JA029334
- Real‐Time Monitoring of Ionosphere VTEC Using Multi‐GNSS Carrier‐Phase Observations and B‐Splines E. Erdogan et al. 10.1029/2021SW002858
- The use of B-splines to represent the topography of river networks E. Boergens et al. 10.1007/s13137-021-00188-w
- A new method for global ionospheric real-time modeling integrating ionospheric VTEC short-term forecast results P. Chen et al. 10.1007/s00190-024-01911-9
- Multi-GNSS global ionosphere modeling enhanced by virtual observation stations based on IRI-2016 model X. Jin et al. 10.1007/s00190-022-01667-0
- Impact and synergies of GIM error estimates on the VTEC interpolation and single-frequency PPP at low latitude region G. Jerez et al. 10.1007/s10291-022-01228-0
- Regional Ionosphere Delay Models Based on CORS Data and Machine Learning R. Natras et al. 10.33012/navi.577
- A Novel Approach for Establishing the Global Ionospheric Model With High Spatiotemporal Resolution P. Chen et al. 10.1109/TGRS.2023.3238044
- Ground GNSS Station Selection to Generate the Global Ionosphere Maps Using the Information Content S. Wang et al. 10.1029/2020SW002675
- Ensemble Machine Learning of Random Forest, AdaBoost and XGBoost for Vertical Total Electron Content Forecasting R. Natras et al. 10.3390/rs14153547
- Ionospheric electron density modelling using B-splines and constraint optimization G. Lalgudi Gopalakrishnan & M. Schmidt 10.1186/s40623-022-01693-4
- Global and Regional High-Resolution VTEC Modelling Using a Two-Step B-Spline Approach A. Goss et al. 10.3390/rs12071198
- Computational simulations of the couple Boiti–Leon–Pempinelli (BLP) system and the (3+1)-dimensional Kadomtsev–Petviashvili (KP) equation C. Yue et al. 10.1063/1.5142796
- Influence of temporal resolution on the performance of global ionospheric maps Q. Liu et al. 10.1007/s00190-021-01483-y
- Approximate Simulations for the Non-linear Long-Short Wave Interaction System H. Qin et al. 10.3389/fphy.2019.00230
- A Least Squares Solution to Regionalize VTEC Estimates for Positioning Applications S. Farzaneh & E. Forootan 10.3390/rs12213545
20 citations as recorded by crossref.
- Improving estimates of the ionosphere during geomagnetic storm conditions through assimilation of thermospheric mass density I. Fernandez-Gomez et al. 10.1186/s40623-022-01678-3
- Operational Multi‐GNSS Global Ionosphere Maps at GFZ Derived From Uncombined Code and Phase Observations A. Brack et al. 10.1029/2021RS007337
- Global mapping of total electron content from GNSS observations for updating IRI-Plas model V. Shubin & T. Gulyaeva 10.1016/j.asr.2021.09.032
- Computational and numerical simulations for the nonlinear fractional Kolmogorov–Petrovskii–Piskunov (FKPP) equation M. Khater et al. 10.1088/1402-4896/ab76f8
- Two‐Way Assessment of Ionospheric Maps Performance Over the Brazilian Region: Global Versus Regional Products G. Jerez et al. 10.1029/2022SW003252
- High-Resolution Ionosphere Corrections for Single-Frequency Positioning A. Goss et al. 10.3390/rs13010012
- Intercalibration of the Plasma Density Measurements in Earth's Topside Ionosphere A. Smirnov et al. 10.1029/2021JA029334
- Real‐Time Monitoring of Ionosphere VTEC Using Multi‐GNSS Carrier‐Phase Observations and B‐Splines E. Erdogan et al. 10.1029/2021SW002858
- The use of B-splines to represent the topography of river networks E. Boergens et al. 10.1007/s13137-021-00188-w
- A new method for global ionospheric real-time modeling integrating ionospheric VTEC short-term forecast results P. Chen et al. 10.1007/s00190-024-01911-9
- Multi-GNSS global ionosphere modeling enhanced by virtual observation stations based on IRI-2016 model X. Jin et al. 10.1007/s00190-022-01667-0
- Impact and synergies of GIM error estimates on the VTEC interpolation and single-frequency PPP at low latitude region G. Jerez et al. 10.1007/s10291-022-01228-0
- Regional Ionosphere Delay Models Based on CORS Data and Machine Learning R. Natras et al. 10.33012/navi.577
- A Novel Approach for Establishing the Global Ionospheric Model With High Spatiotemporal Resolution P. Chen et al. 10.1109/TGRS.2023.3238044
- Ground GNSS Station Selection to Generate the Global Ionosphere Maps Using the Information Content S. Wang et al. 10.1029/2020SW002675
- Ensemble Machine Learning of Random Forest, AdaBoost and XGBoost for Vertical Total Electron Content Forecasting R. Natras et al. 10.3390/rs14153547
- Ionospheric electron density modelling using B-splines and constraint optimization G. Lalgudi Gopalakrishnan & M. Schmidt 10.1186/s40623-022-01693-4
- Global and Regional High-Resolution VTEC Modelling Using a Two-Step B-Spline Approach A. Goss et al. 10.3390/rs12071198
- Computational simulations of the couple Boiti–Leon–Pempinelli (BLP) system and the (3+1)-dimensional Kadomtsev–Petviashvili (KP) equation C. Yue et al. 10.1063/1.5142796
- Influence of temporal resolution on the performance of global ionospheric maps Q. Liu et al. 10.1007/s00190-021-01483-y
Latest update: 14 Dec 2024
Short summary
This paper describes an approach to model VTEC solely from NRT GNSS observations by generating a multi-scale representation (MSR) based on B-splines. The unknown model parameters are estimated by means of a Kalman filter. A number of products are created which differ both in their spectral and temporal resolution. The validation studies show that the product with the highest resolution, based on NRT input data, is of higher accuracy than others used within the selected investigation time span.
This paper describes an approach to model VTEC solely from NRT GNSS observations by generating a...
