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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 (31 August 2023) | Viewed by 12030

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Special Issue Editors

Prof. Dr. Kwangsun Ryu

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Guest Editor

Satellite Technology Research Center, KAIST (Korea Advanced Institute of Science and Technology), Daejeon 34141, Korea
Interests: plasma instruments for ionospheric observation; ionospheric data analysis; preseismic disturbance of ionosphere

Dr. Jian Kong

E-Mail Website
Guest Editor

Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China
Interests: GNSS data processing; ionospheric disturbances; space weather; magnetic storm

Special Issue Information

Dear Colleagues,

Ionospheric disturbances are considered as one of the largest error sources in satellite navigation systems and satellite communications. With the development of technology, the ionospheric and plasma characteristics can now be accurately observed via satellite measurement, which provides an effective way for us to deepen our knowledge of near-Earth space and to better understand the impact of space weather events on precise positioning utilized for navigation.

This Special Issue aims to document the use of satellite remote sensing and in situ measurements to characterize ionospheric and plasma dynamics in the near-Earth environment and asses their impact on space weather. Topics include but are not limited to (1) in situ measurement research and modeling of the global ionosphere/plasma through GNSS or low earth orbit satellites such as ESA Swarm, CSES, C/NOFS, and ICON; (2) the observation tracing and interaction mechanism between ionospheric disturbance/ionospheric delay and space weather anomalies and its possible impact on satellite systems; and (3) correlation research and the establishment of physical explanations between ionospheric changes and earthquake cycles, volcanic eruptions, and other natural disasters.

Prof. Dr. Kwangsun Ryu
Dr. Jian Kong
Guest Editors

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Keywords

ionospheric changes
seismic activities
space plasma
satellite remote sensing
in situ measurements

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Published Papers (5 papers)

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Research

16 pages, 4553 KiB

Open AccessArticle

Design and Testing of an Adaptive In-phase Magnetometer (AIMAG), the Equatorial-Electrojet-Detecting Fluxgate Magnetometer, for the CAS500-3 Satellite

by Seunguk Lee, Kwangsun Ryu, Dooyoung Choi, Seongog Park, Jinkyu Kim, Wonho Cha, Bonju Gu, Jimin Hong, Suhwan Park, Eunjin Jang, Cheongrim Choi and Daeyoung Lee

Remote Sens. 2023, 15(19), 4829; https://doi.org/10.3390/rs15194829 - 5 Oct 2023

Cited by 2 | Viewed by 1505

Abstract

Ionospheric Anomaly Monitoring by Magnetometer And Plasma-probe (IAMMAP) is a suite of scientific instruments used in the Compact Advanced Satellite 500-3 (CAS 500-3), which is planned to be launched by the KSLV (Korean Space Launch Vehicle) in 2025. The main scientific objective of IAMMAP is to understand the complicated correlation between the equatorial electrojet (EEJ) and the equatorial ionization anomaly (EIA), both of which play important roles in the dynamics of ionospheric plasma in the dayside equator region. The magnetic field generated by the EEJ is tiny (~several nT) compared to the background geomagnetic field (~30,000 nT); thus, a high-resolution magnetometer with a wide dynamic range is required to investigate its correlation with the EIA. To achieve this required resolution, IAMMAP includes a set of improved fluxgate magnetometers named the AIMAG (Adaptive In-phase MAGnetometer), which was developed by adopting new technologies. Here, we report the analysis results of the manufactured AIMAG performance based on trade-off studies for optimizing the circuit and sensor configurations. The results support that the AIMAG sensor and electronic circuits with new concepts and technologies will lead to successful observations of EEJ signatures in the ionosphere. Full article

(This article belongs to the Special Issue Satellite Observations of the Global Ionosphere and Plasma Dynamics)

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15 pages, 8165 KiB

Open AccessArticle

A Novel Method of Ionospheric Inversion Based on Horizontal Constraint and Empirical Orthogonal Function

by Debao Wen, Yinghao Tang and Kangyou Xie

Remote Sens. 2023, 15(12), 3124; https://doi.org/10.3390/rs15123124 - 15 Jun 2023

Cited by 1 | Viewed by 1142

Abstract

Tomographic inversion of the ionosphere is a rank-deficient problem. To overcome the above problem, an algebraic reconstruction technique (ART) based on adaptive horizontal constraint and empirical orthogonal function (ARTHCEOF) is proposed. The new algorithm avoids the difficulty of vertically constrained matrix construction and resolves the description of the ionospheric vertical structure by using EOF. To confirm the feasibility and validate the ascendancy of the ARTHCEOF, three algorithms are first tested by using the emulated scheme. The test results show that the ARTHCEOF surpasses the ART and the ART based on the horizontal constraint (ARTHC) in both the inversion accuracy and computational efficiency. Finally, the ARTHCEOF method is applied to invert electron density values using the GNSS measurements during different geomagnetic activities. The tomographic images validate that the ARTHCEOF can reflect ionospheric daily changes in the European region. The altitudinal profiles in a fixed location are illustrated according to the inversion results of ARTHCEOF. Compared with the profiles recorded by the ionosonde station, the altitudinal profiles of ARTHCEOF have a good consistency. In the meantime, the VTEC values are inverted using the CIT results. The differential VTEC values are calculated by means of the inverted VTEC values and ionospheric products of CODE. The differential results further identify the dependability of ARTHCEOF. Full article

(This article belongs to the Special Issue Satellite Observations of the Global Ionosphere and Plasma Dynamics)

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24 pages, 7856 KiB

Open AccessEditor’s ChoiceArticle

Ionospheric–Thermospheric Responses to Geomagnetic Storms from Multi-Instrument Space Weather Data

by Rasim Shahzad, Munawar Shah, M. Arslan Tariq, Andres Calabia, Angela Melgarejo-Morales, Punyawi Jamjareegulgarn and Libo Liu

Remote Sens. 2023, 15(10), 2687; https://doi.org/10.3390/rs15102687 - 22 May 2023

Cited by 12 | Viewed by 3869

Abstract

We analyze vertical total electron content (vTEC) variations from the Global Navigation Satellite System (GNSS) at different latitudes in different continents of the world during the geomagnetic storms of June 2015, August 2018, and November 2021. The resulting ionospheric perturbations at the low and mid-latitudes are investigated in terms of the prompt penetration electric field (PPEF), the equatorial electrojet (EEJ), and the magnetic H component from INTERMAGNET stations near the equator. East and Southeast Asia, Russia, and Oceania exhibited positive vTEC disturbances, while South American stations showed negative vTEC disturbances during all the storms. We also analyzed the vTEC from the Swarm satellites and found similar results to the retrieved vTEC data during the June 2015 and August 2018 storms. Moreover, we observed that ionospheric plasma tended to increase rapidly during the local afternoon in the main phase of the storms and has the opposite behavior at nighttime. The equatorial ionization anomaly (EIA) crest expansion to higher latitudes is driven by PPEF during daytime at the main and recovery phases of the storms. The magnetic H component exhibits longitudinal behavior along with the EEJ enhancement near the magnetic equator. Full article

(This article belongs to the Special Issue Satellite Observations of the Global Ionosphere and Plasma Dynamics)

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20 pages, 4554 KiB

Open AccessArticle

Ionospheric Perturbations Due to Large Thunderstorms and the Resulting Mechanical and Acoustic Signatures

by Babalola O. Ogunsua, Xiushu Qie, Abhay Srivastava, Oladipo Emmanuel Abe, Charles Owolabi, Rubin Jiang and Jing Yang

Remote Sens. 2023, 15(10), 2572; https://doi.org/10.3390/rs15102572 - 15 May 2023

Cited by 5 | Viewed by 1961

Abstract

Perturbations from thunderstorms can play a notable role in the dynamics of the ionosphere. In this work, ionospheric perturbation effects due to thunderstorms were extracted and studied. Thunderstorm-associated lightning activities and their locations were detected by the World-Wide Lightning Location Network (WWLLN). The mechanical components of ionospheric perturbations due to thunderstorms were extracted from the total electron content (TEC), which was measured at selected thunderstorm locations using the polynomial filtering method. Further analyses were conducted using wavelet analysis and Discrete Fourier Transform (DFT) to study the frequency modes and periodicities of TEC deviation. It was revealed that the highest magnitudes of TEC deviations could reach up to ~2.2 TECUs, with dominant modes of frequency in the range of ~0.2 mHz to ~1.2 mHz, falling within the gravity wave range and the second dominant mode in the acoustic range of >1 mHz to <7.5 mHz. Additionally, a 20–60 min time delay was observed between the sprite events, the other high-energy electrical discharges, and the time of occurrence at the highest peak of acoustic-gravity wave perturbations extracted from TEC deviations. The possible mechanism responsible for this phenomenon is further proposed and discussed. Full article

(This article belongs to the Special Issue Satellite Observations of the Global Ionosphere and Plasma Dynamics)

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18 pages, 3294 KiB

Open AccessArticle

Deep Machine Learning Based Possible Atmospheric and Ionospheric Precursors of the 2021 Mw 7.1 Japan Earthquake

by Muhammad Umar Draz, Munawar Shah, Punyawi Jamjareegulgarn, Rasim Shahzad, Ahmad M. Hasan and Nivin A. Ghamry

Remote Sens. 2023, 15(7), 1904; https://doi.org/10.3390/rs15071904 - 2 Apr 2023

Cited by 20 | Viewed by 2926

Abstract

Global Navigation Satellite System (GNSS)- and Remote Sensing (RS)-based Earth observations have a significant approach on the monitoring of natural disasters. Since the evolution and appearance of earthquake precursors exhibit complex behavior, the need for different methods on multiple satellite data for earthquake precursors is vital for prior and after the impending main shock. This study provided a new approach of deep machine learning (ML)-based detection of ionosphere and atmosphere precursors. In this study, we investigate multi-parameter precursors of different physical nature defining the states of ionosphere and atmosphere associated with the event in Japan on 13 February 2021 (M_w 7.1). We analyzed possible precursors from surface to ionosphere, including Sea Surface Temperature (SST), Air Temperature (AT), Relative Humidity (RH), Outgoing Longwave Radiation (OLR), and Total Electron Content (TEC). Furthermore, the aim is to find a possible pre-and post-seismic anomaly by implementing standard deviation (STDEV), wavelet transformation, the Nonlinear Autoregressive Network with Exogenous Inputs (NARX) model, and the Long Short-Term Memory Inputs (LSTM) network. Interestingly, every method shows anomalous variations in both atmospheric and ionospheric precursors before and after the earthquake. Moreover, the geomagnetic irregularities are also observed seven days after the main shock during active storm days (Kp > 3.7; Dst < −30 nT). This study demonstrates the significance of ML techniques for detecting earthquake anomalies to support the Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) mechanism for future studies. Full article

(This article belongs to the Special Issue Satellite Observations of the Global Ionosphere and Plasma Dynamics)

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