Exploring Innovative Ionospheric Applications Using Ground and Spaceborne Observations
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".
Deadline for manuscript submissions: 28 November 2024 | Viewed by 98
Special Issue Editors
Interests: machine learning; space weather; uncertainty quantification
Special Issues, Collections and Topics in MDPI journals
Interests: GNSS remote sensing; ionospheric scintillation
Interests: ionospheric irregularities; uncertainty quantification
Interests: GPS/GNSS; geodesy; atmospheric modelling; radio occultation; indoor positioning and tracking; space situational awareness; satellite orbit determination; space weather and severe weather
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The ionosphere, a region of the Earth’s atmosphere extending from approximately 50 to 1000 kilometers above the surface, plays a crucial role in various atmospheric and space weather phenomena. Crucially, the arrival of solar maxima, marking the beginning of a new solar cycle, significantly impacts this region. Understanding its dynamics is essential for predicting and mitigating the impacts of space weather events on communication, navigation, and other technological systems reliant on satellite signals. However, traditional modeling approaches encounter challenges in capturing the complex and nonlinear behavior of the ionosphere. We hope to find new cutting-edge techniques that can be used as effective tools for addressing these challenges by extracting patterns and relationships from large datasets of ground and spaceborne observations, including, but not limited to, global navigation satellite systems (GNSSs).
The aim of this Special Issue is to showcase the latest advancements in applications for studying the ionosphere using ground and spaceborne observations. By bringing together researchers from diverse backgrounds, the Special Issue seeks to foster interdisciplinary collaboration and facilitate the exchange of ideas and methodologies in this rapidly evolving field. Its contributions will highlight the potential of new techniques to enhance ionospheric modeling, forecasting, and understanding extreme phenomena, including those such as ionospheric irregularities, EIA, MSNA, MSTID, and their influence on communication, such as scintillation.
Suggested themes for submissions include, but are not limited to, ML-based ionospheric modeling, data assimilation techniques, the prediction and analysis of ionospheric disturbances, anomaly detection, and applications of GNSS data in space weather monitoring. It is highly encouraged to develop new techniques and utilize multiple types of observations to improve the specification of the ionosphere environment and to advance understandings of extreme space weather phenomena in the current solar maximum.
This Special Issue welcomes original research articles, reviews, methodologies, and case studies that demonstrate innovative approaches, novel findings, and practical applications in ionospheric research. Contributions that integrate multiple datasets or combine ML with traditional modeling approaches are particularly encouraged.
Dr. Andong Hu
Dr. Dongsheng Zhao
Dr. Weijia Zhan
Prof. Dr. Kefei Zhang
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
- ionosphere
- machine learning
- global navigation satellite system (GNSS)
- space weather
- data assimilation
- ionospheric disturbances
