Advances in Atmospheric Aerosol Monitoring Based on Lidar and Satellites
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".
Deadline for manuscript submissions: 14 November 2025 | Viewed by 580
Special Issue Editor
Interests: atmospheric and oceanic lidar; machine vision; image processing; deep learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent advances in LiDAR and remote sensing satellites have revolutionized the way we observe and understand atmospheric aerosols. Aerosols play a crucial role in climate regulation, air quality, and human health, yet their variability and impact remain challenging to characterize due to their complex spatial and temporal distributions. LiDAR, with its ability to provide high-resolution vertical profiles, has become an invaluable tool for aerosol monitoring, while remote sensing satellites offer large-scale, vertical observations that are essential for understanding aerosol transport and distribution globally. These technologies have greatly enhanced our ability to study aerosol properties, sources, and sinks, improving climate models and air quality predictions. The development of innovative LiDAR technologies and new satellite missions has pushed the boundaries of our knowledge, creating opportunities for more precise and comprehensive aerosol monitoring.
This Special Issue aims to bring together studies that leverage LiDAR and remote sensing satellites for atmospheric aerosol monitoring. We encourage submissions that demonstrate diverse uses of these technologies across different atmospheric conditions, scales, and regions. The objective is to foster a deeper understanding of aerosol properties, their spatial and temporal dynamics, and their effects on climate and air quality.
Articles may address, but are not limited to, the following topics:
- Development of novel aerosol monitoring technology;
- Aerosol–cloud interactions and dynamics;
- Aerosol change detection and long-term trends;
- Aerosol optical and microphysical properties;
- Carbon cycle/sequestration related to aerosols;
- Aerosol dispersion effect and influence;
- Aerosol radiative forcing and climate feedbacks;
- Novel algorithms and machine learning techniques for aerosol detection;
- Multispectral and hyperspectral approaches for aerosol characterization;
- Regional and global aerosol transport modeling.
Prof. Dr. Dong Liu
Guest Editor
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
- atmospheric aerosols
- LiDAR and remote sensing satellites
- machine learning in aerosol detection
- climate regulation
- aerosol–cloud interactions
- aerosol transport modeling
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