Knowledge-Driven and/or Data-Driven Methods for Remote Sensing Image Processing (2nd Edition)
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "AI Remote Sensing".
Deadline for manuscript submissions: 30 April 2026 | Viewed by 653
Special Issue Editors
Interests: machine learning; hyperspectral unmixing of remote sensing images; remote sensing image fusion; data mining; intelligent computing
Special Issues, Collections and Topics in MDPI journals
Interests: hyperspectral image processing; machine learning; scientific computing
Special Issues, Collections and Topics in MDPI journals
2. Faculty of Electrical and Computer Engineering, University of Iceland, 101 Reykjavík, Iceland
Interests: hyperspcetral image processing; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Remote sensing image processing plays a critical role in diverse fields such as environmental monitoring, resource management, and disaster response. However, processing and analyzing remotely sensed data can be challenging due to complex environments, limited signal-to-noise ratios, and the presence of noise and artifacts. In recent years, two differing approaches to remote sensing image processing have emerged: knowledge-driven and data-driven methods. The knowledge-driven methods, based on expert experience or mathematical models that describe the physical processes underlying remote sensing data, exhibit high interpretability. In contrast, data-driven methods leverage machine learning algorithms to identify correlations and patterns from observed data, and have become prevalent in recent years. Therefore, this Special Issue focuses on exploring the advantages and limitations of knowledge-driven and data-driven approaches and suggests ways to combine them to enhance remote sensing image processing. We hope to receive a variety of both theoretical or heuristic works on this topic, leverage the strengths of knowledge-driven and data-driven methods, and provide valuable insights into the development of enhanced remote sensing techniques for a broad range of applications.
The scope of this Special Issue includes, but is not limited to, the following topics:
- General remote sensing image processing, such as classification, object detection, segmentation, super-resolution, denoising, etc.
- Real-world applications based on remote sensing images, such as land use mapping, vegetation analysis, and environmental monitoring.
- Combining traditional methods and deep learning methods for remote sensing image processing and analysis.
- Multi-modal remote sensing image processing, such as multi-modal image fusion, pan-sharpening, etc.
Prof. Dr. Junmin Liu
Prof. Dr. Xile Zhao
Prof. Dr. Bin Zhao
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
- image processing
- remote sensing
- knowledge-driven methods
- data-driven methods
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