Aerosol and Atmospheric Correction
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".
Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 16852
Special Issue Editors
Interests: remote sensing technology and application; information extraction and engineering; quantitative remote sensing
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; artificial intelligence; big data; air pollution; aerosol; particulate matter; trace gas; cloud
Special Issues, Collections and Topics in MDPI journals
Interests: aerosol remote sensing; biomass burning aerosol aging characteristic; climate change
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Aerosol is the key factor in atmospheric correction of remote sensing images, while atmospheric aerosol severely influences global climate and air quality. Remote sensing is a complex system. The radiation signal received by the sensor is surface-atmosphere coupled, including the signal of path radiance, surface reflection, and surface-atmosphere interaction, a phenomenon which impedes quantitative information acquisition from both a surface and atmosphere aspect. Accurate aerosol estimation and atmospheric correction are needed to solve this puzzle.
The goal of this Special Issue is to discuss accurate retrieval and estimation of aerosol to help precise atmospheric correction and narrow down its uncertainty in climatic and environmental effect. Further, with the development of new technologies, such as high resolution and hyperspectral sensors as well as artificial intelligence, new ways of aerosol estimation and atmospheric correction are awaiting exploration. Therefore, we cordially invite our colleagues in the scientific community to submit their recent findings on “Aerosol and Atmospheric Correction” to this Special Issue of Remote Sensing. Potential topics include but are not limited to the following:
- Aerosol retrieval;
- Atmospheric correction;
- Radiative transfer;
- Surface–atmosphere signal decoupling;
- Aerosol estimation;
- Climatic and environmental effect of aerosol;
- Remote sensing image preprocessing;
- Artificial intelligence aid atmospheric correction;
- High-resolution image atmospheric correction;
- Hyperspectral image atmospheric correction.
Prof. Dr. Xingfa Gu
Dr. Jing Wei
Dr. Shuaiyi Shi
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
- aerosol retrieval
- atmospheric correction
- radiative transfer
- surface-atmosphere signal decoupling
- aerosol estimation
- climatic and environmental effect
- image preprocessing
- artificial intelligence
- high resolution image
- hyperspectral image
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