Remote Sensing Image Change Detection and Feature Enhancement Based on Deep Learning
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: 28 February 2026 | Viewed by 135
Special Issue Editors
Interests: intelligent interpretation of remote sensing images; quantitative remote sensing and time-series analysis; multi-source remote sensing image change detection; UAV intelligent application
Interests: image processing; change detection and ecological remote sensing monitoring
Interests: geospatial information science and remote sensing
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing change detection; land use/cover change detection; deep learning
Special Issue Information
Dear Colleagues,
Change detection using deep learning has become essential for understanding various environmental changes, including land use and cover transformations, biodiversity shifts, urbanization, and disaster response. A critical aspect of this process is feature enhancement, which improves the learning of image features. By innovating deep learning techniques for change detection and enhancing features, we can achieve more efficient and interpretable results, ultimately facilitating informed decision-making for both environmental and socio-economic challenges.
This Special Issue seeks to compile advanced research on deep learning-based remote sensing image change detection and feature enhancement, emphasizing innovative algorithms, architectures, and applications that improve accuracy, efficiency, and interpretability.
Submissions may address, but are not limited to, the following topics:
- Remote sensing image change detection.
- Knowledge-guided, data-driven change detection.
- Remote sensing intelligent interpretation.
- Multi-source remote sensing image analysis.
- Multi-modal image analysis.
- Multi-temporal remote sensing image analysis.
- Deep learning for time-series analysis.
- Object detection.
- Semantic segmentation.
- Image matching.
- Scene association.
- Land cover/land use change detection.
- Feature fusion.
- Feature enhancement.
- Multi-scale feature extraction.
- Ecological remote sensing monitoring.
Prof. Dr. Kaimin Sun
Dr. Wenzhuo Li
Dr. Xin Tao
Guest Editors
Dr. Ting Bai
Dr. Wangbin Li
Guest Editor Assistants
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
- remote sensing change detection
- feature enhancement
- feature fusion
- semantic segmentation
- deep learning
- multi-model image analysis
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