Ionospheric Anomaly Identification: Based on GNSS-TEC Data Fusion Supported by Three-Dimensional Spherical Voxel Visualization
Ionospheric tomography, an effective method for reconstructing 3-D electron density, is traditionally pictured by 3-D IED (ionospheric electron density) slices to express ionospheric disturbances, which may overlook the critical information in 3-D spherical manifold space. Here, we develop a novel v...
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MDPI AG
2025-04-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/16/4/428 |
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| author | Boqi Peng Biyan Chen Busheng Xie Lixin Wu |
| author_facet | Boqi Peng Biyan Chen Busheng Xie Lixin Wu |
| author_sort | Boqi Peng |
| collection | DOAJ |
| description | Ionospheric tomography, an effective method for reconstructing 3-D electron density, is traditionally pictured by 3-D IED (ionospheric electron density) slices to express ionospheric disturbances, which may overlook the critical information in 3-D spherical manifold space. Here, we develop a novel visualization framework that integrates tomography reconstruction with a spherical latitude–longitude grid system, enabling the comprehensive characterization of 3-D IED dynamic evolution in 3-D manifold spherical space. Through this method, we visualized two cases: the Hualien earthquake on 2 April 2024 and the geomagnetic storm on 24 April 2023. The results demonstrate the evolution of the electron density during earthquake and geomagnetic storms in the real 3-D space, showing that seismic events induce bottom-up IED negative anomalies localized near epicenters, while geomagnetic storms trigger top-down depletion processes, with IED propagating from higher altitudes in the real 3-D manifold space. Compared to the conventional slice, our visualization model can visualize the characteristics, with the coverage area being observed to increase with the altitude within the same geospatial coordinates. This framework can advance the identification of ionosphere anomalies by enabling the precise differentiation of anomaly sources. This work bridges gaps in geospatial modeling by harmonizing ionospheric tomography with Earth system grids, offering a feasible solution for analyzing multi-scale ionospheric phenomena. |
| format | Article |
| id | doaj-art-a34c21600a4f4c34bc877a095f26636b |
| institution | DOAJ |
| issn | 2073-4433 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj-art-a34c21600a4f4c34bc877a095f26636b2025-08-20T03:14:16ZengMDPI AGAtmosphere2073-44332025-04-0116442810.3390/atmos16040428Ionospheric Anomaly Identification: Based on GNSS-TEC Data Fusion Supported by Three-Dimensional Spherical Voxel VisualizationBoqi Peng0Biyan Chen1Busheng Xie2Lixin Wu3School of Geosciences and Info-Physics, Central South University, Changsha 410083, ChinaSchool of Geosciences and Info-Physics, Central South University, Changsha 410083, ChinaSchool of Geosciences and Info-Physics, Central South University, Changsha 410083, ChinaSchool of Geosciences and Info-Physics, Central South University, Changsha 410083, ChinaIonospheric tomography, an effective method for reconstructing 3-D electron density, is traditionally pictured by 3-D IED (ionospheric electron density) slices to express ionospheric disturbances, which may overlook the critical information in 3-D spherical manifold space. Here, we develop a novel visualization framework that integrates tomography reconstruction with a spherical latitude–longitude grid system, enabling the comprehensive characterization of 3-D IED dynamic evolution in 3-D manifold spherical space. Through this method, we visualized two cases: the Hualien earthquake on 2 April 2024 and the geomagnetic storm on 24 April 2023. The results demonstrate the evolution of the electron density during earthquake and geomagnetic storms in the real 3-D space, showing that seismic events induce bottom-up IED negative anomalies localized near epicenters, while geomagnetic storms trigger top-down depletion processes, with IED propagating from higher altitudes in the real 3-D manifold space. Compared to the conventional slice, our visualization model can visualize the characteristics, with the coverage area being observed to increase with the altitude within the same geospatial coordinates. This framework can advance the identification of ionosphere anomalies by enabling the precise differentiation of anomaly sources. This work bridges gaps in geospatial modeling by harmonizing ionospheric tomography with Earth system grids, offering a feasible solution for analyzing multi-scale ionospheric phenomena.https://www.mdpi.com/2073-4433/16/4/4283-D IEDearthquakemagnetic stormDGGS3-D visualization |
| spellingShingle | Boqi Peng Biyan Chen Busheng Xie Lixin Wu Ionospheric Anomaly Identification: Based on GNSS-TEC Data Fusion Supported by Three-Dimensional Spherical Voxel Visualization Atmosphere 3-D IED earthquake magnetic storm DGGS 3-D visualization |
| title | Ionospheric Anomaly Identification: Based on GNSS-TEC Data Fusion Supported by Three-Dimensional Spherical Voxel Visualization |
| title_full | Ionospheric Anomaly Identification: Based on GNSS-TEC Data Fusion Supported by Three-Dimensional Spherical Voxel Visualization |
| title_fullStr | Ionospheric Anomaly Identification: Based on GNSS-TEC Data Fusion Supported by Three-Dimensional Spherical Voxel Visualization |
| title_full_unstemmed | Ionospheric Anomaly Identification: Based on GNSS-TEC Data Fusion Supported by Three-Dimensional Spherical Voxel Visualization |
| title_short | Ionospheric Anomaly Identification: Based on GNSS-TEC Data Fusion Supported by Three-Dimensional Spherical Voxel Visualization |
| title_sort | ionospheric anomaly identification based on gnss tec data fusion supported by three dimensional spherical voxel visualization |
| topic | 3-D IED earthquake magnetic storm DGGS 3-D visualization |
| url | https://www.mdpi.com/2073-4433/16/4/428 |
| work_keys_str_mv | AT boqipeng ionosphericanomalyidentificationbasedongnsstecdatafusionsupportedbythreedimensionalsphericalvoxelvisualization AT biyanchen ionosphericanomalyidentificationbasedongnsstecdatafusionsupportedbythreedimensionalsphericalvoxelvisualization AT bushengxie ionosphericanomalyidentificationbasedongnsstecdatafusionsupportedbythreedimensionalsphericalvoxelvisualization AT lixinwu ionosphericanomalyidentificationbasedongnsstecdatafusionsupportedbythreedimensionalsphericalvoxelvisualization |