Data Analysis and Algorithms for Aerosols Remote Sensing
A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".
Deadline for manuscript submissions: 30 November 2025 | Viewed by 12
Special Issue Editor
Special Issue Information
Dear Colleagues,
This Special Issue focuses on methods and algorithms for atmospheric remote sensing, with particular emphasis on atmospheric aerosols. We aim to highlight recent advances in the development and application of the algorithms used in both passive and active remote sensing, as well as in data processing techniques related to atmospheric instrumentation.
The scope of this Special Issue includes a wide range of topics, such as the retrieval and analysis of aerosol and cloud properties, calibration and validation methods, data harmonization across networks, and innovative approaches to improve the accuracy and resolution of atmospheric measurements. Contributions that promote open-source tools and collaborative development are particularly encouraged, as they play a key role in improving transparency, reproducibility, and the overall quality of scientific research.
The purpose of this Special Issue is to provide a platform for researchers to share their methodologies, exchange best practices, and disseminate software tools that can benefit the atmospheric science community. A central objective is to encourage authors to share links to software repositories. Making tools and codes openly accessible increases their visibility, facilitates their use and adaptation by the community, and helps to advance the field through a collective effort.
We warmly invite you to contribute to this Special Issue by sharing your work on data analysis methodologies and remote sensing algorithms. Please ensure that, where possible, links to repositories are provided to maximize the impact and usability of your developed tools.
Dr. Juan Vicente Pallotta
Guest Editor
Manuscript Submission Information
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Keywords
- atmospheric remote sensing
- atmospheric aerosols
- air quality
- lidar data analysis
- atmospheric radiometric data analysis
- time series analysis
- data analysis
- open source
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