Artificial Intelligence Remote Sensing Change Detection: Development and Challenges
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "AI Remote Sensing".
Deadline for manuscript submissions: 26 November 2025 | Viewed by 20
Special Issue Editors
Interests: remote sensing; semi-supervised learning; semantic segmentation; change detection
Interests: change detection; object segmentation; action recognition
Interests: change detection; incremental learning; camouflaged object detection
Interests: image processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Remote sensing change detection has emerged as a pivotal tool for monitoring dynamic environmental processes, urban expansion, disaster response, and ecological shifts. The integration of artificial intelligence (AI), particularly deep learning, has revolutionized this field by enabling automated, high-precision analysis of multi-temporal and multi-source satellite data. However, challenges persist in addressing data heterogeneity, model interpretability, computational efficiency, and generalization across diverse geographical contexts. This Special Issue aims to consolidate cutting-edge research on AI-driven methodologies for remote sensing change detection, while critically examining their limitations and future directions.
We invite contributions that explore innovative algorithms, datasets, and applications to advance the theoretical and practical frontiers of AI in change detection. Topics of interest include, but are not limited to, the following:
- Deep learning architectures;
- Multi-modal data fusion;
- Weakly supervised and self-supervised learning;
- Explainable AI (XAI);
- Lightweight models;
- Cross-domain adaptation;
- Application case studies.
We welcome original research articles, reviews, and perspective papers that align with these themes. Join us in shaping the future of intelligent Earth observation systems.
Dr. Lingyan Ran
Prof. Dr. Tao Zhuo
Dr. Shizhou Zhang
Prof. Dr. Fa-Ming Fang
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
- AI-enhanced remote sensing
- multitemporal change detection
- deep learning in geospatial analysis
- environmental dynamics monitoring
- heterogeneous data fusion
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