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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Main Authors: Boqi Peng, Biyan Chen, Busheng Xie, Lixin Wu
Format: Article
Language:English
Published: MDPI AG 2025-04-01
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.
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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
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AT biyanchen ionosphericanomalyidentificationbasedongnsstecdatafusionsupportedbythreedimensionalsphericalvoxelvisualization
AT bushengxie ionosphericanomalyidentificationbasedongnsstecdatafusionsupportedbythreedimensionalsphericalvoxelvisualization
AT lixinwu ionosphericanomalyidentificationbasedongnsstecdatafusionsupportedbythreedimensionalsphericalvoxelvisualization