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Satellite Missions for Magnetic Field Analysis
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Satellite Missions for Magnetic Field Analysis

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Satellite Missions for Earth and Planetary Exploration".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 8635

Special Issue Editors

Prof. Dr. Xuhui Shen

E-Mail Website
Guest Editor
Space Observation Research Center, National Institute of Natural Hazards, MEMC, Beijing 100085, China
Interests: earthquake observation from space; satellite-based geophysical field investigation; active tectonics
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Keke Zhang

E-Mail Website
Guest Editor
State Key Laboratory of Lunar and Planetary Science, Macau University of Science and Technology, Macau, China
Interests: theories of convection and waves in rotating systems; generation and dynamics of planetary and stellar magnetic fields; hydrodynamic and magnetohydrodynamic instabilities in rapidly rotating systems; shape, gravity, and internal structure of rotating planets; large-scale numerical simulations for planetary and astrophysical systems
Prof. Dr. Angelo De Santis

E-Mail Website
Guest Editor
Istituto Nazionale di Geofisica e Vulcanologia, Rome, Italy
Interests: geomagnetism; earthquake precursors; LAIC; geosystemics; entropy
Special Issues, Collections and Topics in MDPI journals
Dr. Yanyan Yang

E-Mail Website
Guest Editor
National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China
Interests: satellite magnetic field calibration; global geomagnetic field modeling; geomagnetic field variation

Special Issue Information

Dear Colleagues,

The geomagnetic field is fundamental geophysical parameters, playing a vital role in geoscience and space science as well as in scientific applications such as communication and navigation, natural disaster early warning, global change, and so on. Though there are many geomagnetic field models, new datasets and methods are still needed to update these models and continuously improve their spatial resolution. In recent years, apparent geomagnetic field changes have been observed, such as the fast position movement of the north magnetic pole, the change of the SAA region, the possible arrival of new global geomagnetic jerks, etc.

LEO satellite magnetic field measurement is thus quickly becoming the dominant approach for geomagnetic field exploration. At present, there are plenty of satellites (e.g., Swarm, CSES, etc.) operating in the near-Earth space to provide geomagnetic field observations. Further, there are other future missions (e.g., CSES 02, Macau Science Satellite-1, MagQuest, NanoMagsat) that are going to be launched soon. The availability of the geomagnetic field will significantly increase at that time. Thus, it is of great importance to make a list of current and upcoming missions and determine how to achieve data calibration/validation, especially for missions that have already operated for several years. Such observations and newly updated models will help us to investigate variations in the geomagnetic field and obtain new findings from other scientific applications.

This issue aims to collect the state of the art of new missions and data calibration/validation studies on near-Earth magnetic fields. In addition, taking full advantage of current operating satellites, it aims to present the latest results on global/regional geomagnetic field modeling, multiscale variations of the geomagnetic field and their possible mechanism, and other related applications on communication and navigation, geoscience and space physic studies, natural hazard early warning, and global change.

We are looking for contributions that include but are not limited to:

  • New missions, instruments, and tools to monitor the near-Earth magnetic field
  • Data processing, validation, and evaluation methods of measurements
  • Theory, progress on global/regional geomagnetic field modeling
  • Results on geomagnetic field multiscale variations
  • Observational analysis or simulations on communication and navigation
  • Data applications in geoscience and space physic studies and natural hazards including earthquakes, volcanoes, tsunami, typhoons, space weather, etc.
  • Data application in global change, Earth systematic science, and Earth critical zone research

Prof. Dr. Xuhui Shen
Prof. Dr. Keke Zhang
Prof. Dr. Angelo De Santis
Dr. Yanyan Yang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • LEO satellites
  • payload
  • geomagnetic field modeling
  • data calibration/validation
  • communication and navigation
  • natural hazards monitoring

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Published Papers (5 papers)

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25 pages, 58247 KiB  
Article
Spatial Characteristics of Global Strong Constant-Frequency Electromagnetic Disturbances from Electric-Field VLF Data of the CSES
by Ying Han, Qiao Wang, Jianping Huang, Jing Yuan, Zhong Li, Yali Wang, Jingyi Jin and Xuhui Shen
Remote Sens. 2023, 15(15), 3815; https://doi.org/10.3390/rs15153815 - 31 Jul 2023
Cited by 2 | Viewed by 1201
Abstract
Ionospheric disturbances are mainly caused by solar and Earth surface activity. The electromagnetic data collected by the CSES (China Seismo-Electromagnetic Satellite, popularly known as the Zhangheng-1 satellite) can capture many space disturbances. Different spatial disturbances can exhibit distinctive shapes on spectrograms. Constant-frequency electromagnetic [...] Read more.
Ionospheric disturbances are mainly caused by solar and Earth surface activity. The electromagnetic data collected by the CSES (China Seismo-Electromagnetic Satellite, popularly known as the Zhangheng-1 satellite) can capture many space disturbances. Different spatial disturbances can exhibit distinctive shapes on spectrograms. Constant-frequency electromagnetic disturbances (CFEDs) such as artificially transmitted VLF radio waves, power line harmonics, and satellite platform disturbances can appear as horizontal lines on spectrograms. Therefore, we used computer vision and machine learning techniques to extract the frequency of global CFEDs and analyze their strong spatial signal characteristics. First, we obtained time-frequency spectrograms from CSES VLF electric-field waveform data using Fourier transform. Next, we employed an unsupervised clustering algorithm to automatically recognize CFED horizontal lines on spectrograms, merging horizontal lines from different spectrograms, to obtain the CFED horizontal-line frequency range. In the third stage, we verified the presence of CFEDs in power spectrograms, thus extracting their true frequency values. Finally, for strong CFED signals, we generated eight revisited periods, resulting in 10,230 power spectrograms for analyzing each CFED’s spatial characteristics using a combined periodic sequence and spatial region that included frequency offsets, frequency fluctuations, and signal non-observation areas. These findings contribute to enhancing the quality of CSES observational data and provides a theoretical basis for constructing global CFED spatial background fields and earthquake monitoring and early prediction systems. Full article
(This article belongs to the Special Issue Satellite Missions for Magnetic Field Analysis)
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23 pages, 20265 KiB  
Article
Frequency Extraction of Global Constant Frequency Electromagnetic Disturbances from Electric Field VLF Data on CSES
by Ying Han, Qiao Wang, Jianping Huang, Jing Yuan, Zhong Li, Yali Wang, Haijun Liu and Xuhui Shen
Remote Sens. 2023, 15(8), 2057; https://doi.org/10.3390/rs15082057 - 13 Apr 2023
Cited by 1 | Viewed by 1669
Abstract
The electromagnetic data observed with the CSES (China Seismo-Electromagnetic Satellite, also known as Zhangheng-1 satellite) contain numerous spatial disturbances. These disturbances exhibit various shapes on the spectrogram, and constant frequency electromagnetic disturbances (CFEDs), such as artificially transmitted very-low-frequency (VLF) radio waves, power line [...] Read more.
The electromagnetic data observed with the CSES (China Seismo-Electromagnetic Satellite, also known as Zhangheng-1 satellite) contain numerous spatial disturbances. These disturbances exhibit various shapes on the spectrogram, and constant frequency electromagnetic disturbances (CFEDs), such as artificially transmitted very-low-frequency (VLF) radio waves, power line harmonics, and interference from the satellite platform itself, appear as horizontal lines. To exploit this feature, we proposed an algorithm based on computer vision technology that automatically recognizes these lines on the spectrogram and extracts the frequencies from the CFEDs. First, the VLF waveform data collected with the CSES electric field detector (EFD) are converted into a time–frequency spectrogram using short-time Fourier Transform (STFT). Next, the CFED automatic recognition algorithm is used to identify horizontal lines on the spectrogram. The third step is to determine the line frequency range based on the proportional relationship between the frequency domain of the satellite’s VLF and the height of the time–frequency spectrogram. Finally, we used the CSES power spectrogram to confirm the presence of CFEDs in the line frequency range and extract their true frequencies. We statistically analyzed 1034 orbit time–frequency spectrograms and power spectrograms from 8 periods (5 days per period) and identified approximately 200 CFEDs. Among them, two CFEDs with strong signals persisted throughout an entire orbit. This study establishes a foundation for detecting anomalies due to artificial sources, particularly in the study of short-term strong earthquake prediction. Additionally, it contributes to research on other aspects of spatial electromagnetic interference and the suppression and cleaning of electromagnetic waves. Full article
(This article belongs to the Special Issue Satellite Missions for Magnetic Field Analysis)
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19 pages, 19669 KiB  
Article
The Study of the Lithospheric Magnetic Field over Xinjiang and Tibet Areas Based on Ground, Airborne, and Satellite Data
by Yan Feng, Abbas Nasir, Yijun Li, Jinyuan Zhang, Jiaxuan Zhang and Ya Huang
Remote Sens. 2023, 15(8), 2002; https://doi.org/10.3390/rs15082002 - 10 Apr 2023
Cited by 1 | Viewed by 1659
Abstract
Combined with the ground, airborne, and CHAMP satellite data, the lithospheric field over Xinjiang and Tibet is modeled through the three-dimensional Surface Spline (3DSS) model, Regional Spherical Harmonic Analysis (RSHA) model, and CHAOS-7.11 model. Then, we compare the results with the original measuring [...] Read more.
Combined with the ground, airborne, and CHAMP satellite data, the lithospheric field over Xinjiang and Tibet is modeled through the three-dimensional Surface Spline (3DSS) model, Regional Spherical Harmonic Analysis (RSHA) model, and CHAOS-7.11 model. Then, we compare the results with the original measuring data, NGDC720, LCS-1, and the newest SHA model with the degree to 1000 (SHA1000). Moreover, the error estimation and the geological analysis are carried out, and we investigate the possible correspondence between the lithospheric field and the surface heat flow. The results show that the 3DSS model can better describe the detailed distribution of the lithospheric field after comparing it with other models. Some new features are reflected, particularly in the areas of Southern Xinjiang and Tibet, such as a positive anomaly stripe in the southwest, its neighboring Tashkurgan–Hotan–Cele–Minfeng–Qiemo–Ruoqiang belt, and the middle edge of the Kunlun Mountains. The stripe, in terms of rock composition, has a shallow magnetic field source and is related to magnetic intrusions; the lithospheric field in Tibet is weak. Additionally, when the heat flow distribution is compared to our results, there is a good consistency between a positive stripe of heat flow and a positive stripe of the lithospheric field in southern Tibet. The large heat flow values may be related to the shallow Curie surface, which shows that demagnetization is happening close to the surface. However, more of a ferromagnetic mineral, Titanium magnetite, is found there. Full article
(This article belongs to the Special Issue Satellite Missions for Magnetic Field Analysis)
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Other

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11 pages, 6962 KiB  
Technical Note
An Improved In-Flight Calibration Scheme for CSES Magnetic Field Data
by Yanyan Yang, Zeren Zhima, Xuhui Shen, Bin Zhou, Jie Wang, Werner Magnes, Andreas Pollinger, Hengxin Lu, Feng Guo, Roland Lammegger, Na Zhou, Yuanqing Miao, Qiao Tan and Wenjing Li
Remote Sens. 2023, 15(18), 4578; https://doi.org/10.3390/rs15184578 - 17 Sep 2023
Cited by 3 | Viewed by 1637
Abstract
The CSES high precision magnetometer (HPM), consisting of two fluxgate magnetometers (FGM) and one coupled dark state magnetometer (CDSM), has worked successfully for more than 5 years providing continuous magnetic field measurements since the launch of the CSES in February 2018. After rechecking [...] Read more.
The CSES high precision magnetometer (HPM), consisting of two fluxgate magnetometers (FGM) and one coupled dark state magnetometer (CDSM), has worked successfully for more than 5 years providing continuous magnetic field measurements since the launch of the CSES in February 2018. After rechecking almost every year’s data, it has become possible to make an improvement to the in-flight intrinsic calibration (to estimate offsets, scale values and non-orthogonality) and alignment (to estimate three Euler angles for the rotation between the orthogonalized sensor coordinates and the coordinate system of the star tracker) of the FGM. The following efforts have been made to achieve this goal: For the sensor calibration, FGM sensor temperature corrections on offsets and scale values have been taken into account to remove seasonal effects. Based on these results, Euler angles have been estimated along with global geomagnetic field modeling to improve the alignment of the FGM sensor. With this, a latitudinal effect in the east component of the originally calibrated data could be reduced. Furthermore, it has become possible to prolong the updating period of all calibration parameters from daily to 10 days, without the separation of dayside and nightside data. The new algorithms optimize routine HPM data processing efficiency and data quality. Full article
(This article belongs to the Special Issue Satellite Missions for Magnetic Field Analysis)
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10 pages, 2827 KiB  
Technical Note
Blind Spots Analysis of Magnetic Tensor Localization Method
by Lei Xu, Xianyuan Huang, Zhonghua Dai, Fuli Yuan, Xu Wang and Jinyu Fan
Remote Sens. 2023, 15(8), 2199; https://doi.org/10.3390/rs15082199 - 21 Apr 2023
Cited by 1 | Viewed by 1404
Abstract
In order to compare and analyze the positioning efficiency of the magnetic tensor location method, this paper studies the blind spots of the magnetic tensor location method. By constructing two magnetic tensor localization models, the localization principles of the single-point magnetic tensor localization [...] Read more.
In order to compare and analyze the positioning efficiency of the magnetic tensor location method, this paper studies the blind spots of the magnetic tensor location method. By constructing two magnetic tensor localization models, the localization principles of the single-point magnetic tensor localization method (STLM) and the two-point magnetic tensor linear localization method (TTLM) are analyzed. Furthermore, the eigenvalue analysis method is studied to analyze the blind spots of STLM, and the spherical analysis method is proposed to analyze the blind spots of TTLM. The results show that when the direction of any measuring point is perpendicular to the direction of the target magnetic moment, blind spots of STLM appear. However, TTLM still has good positioning performance in the blind spot. Full article
(This article belongs to the Special Issue Satellite Missions for Magnetic Field Analysis)
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