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Special Issue "Multisource Remote Sensing Data Fusion and Assimilation in Atmospheric Observations"
A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".
Deadline for manuscript submissions: 15 October 2023 | Viewed by 185
Special Issue Editors
Interests: data assimilation; multisource data fusion; geostatistics; machine learning; spatio-temporal data analysis
Interests: spatiotemporal statistics; data assimilation; numerical optimization; environmental remote sensing; geoinformatics
Special Issue Information
This Special Issue mainly explores “advanced” or “novel” data fusion and data assimilation techniques for atmospheric observations concerning air pollution, air temperature, precipitation, wind, etc. The availability of multi-resolution remote sensing data has promoted the development of different data fusion and assimilation. The aim of this issue is to collect new ideas on data fusion, data assimilation, machine learning, geostatistics, and quality assessment. The authors will be able to express their creativity without restrictions and ensure the scientific rigor of research. This Special Issue is, therefore, intended to strongly encourage creative endeavors in theory and practice. We are looking for techniques that may bring challenges and lead to breakthroughs, for example, the new methods in the initial experimental stage that have made basic advancements and potentially contributed to a paradigm shift. Recent developments, applications, and evaluations of remote sensing and observation techniques for atmospheric observations are preferred. Required topics include but are not limited to:
- Multi-source data fusion;
- Data assimilation into physical simulation;
- Machine learning;
- Deep learning with interpretability;
- Baysian statistics;
- Microwave remote sensing;
- Spatio-temporal analysis;
- Multi-resolution analysis;
- Quality assessment;
- Model calibration;
- Data validation.
Dr. Jianhui Xu
Dr. Hong Shu
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. Atmosphere is an international peer-reviewed open access monthly 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 2000 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.
- data fusion of different atmospheric observations
- data Assimilation
- machine learning
- deep learning
- multi-resolution analysis
- microwave remote sensing data
- machine learning interpretability in data fusion
- spatio-temporal analysis of atmospheric observations
- atmosphere environmental quality assessment