Advances in Multimodal Remote Sensing Data: Processing, Fusion and Applications
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "AI Remote Sensing".
Deadline for manuscript submissions: 25 July 2025 | Viewed by 204
Special Issue Editors
Interests: remote sensing fundamentals and system design; signal processing; SAR imaging techniques
Interests: image processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The processing of multimodal remote sensing data enables the comprehensive utilization of data from different sensors, overcoming the limitations of incomplete information inherent in single-mode data and providing more comprehensive and accurate Earth observation information. In practical applications such as land planning, environmental monitoring, and land cover classification, different modalities of data, such as visible light, infrared, and radar, offer complementary information and multidimensional features. However, multi-source data acquired from heterogeneous platforms like satellites and drones face challenges such as spatial–temporal matching, target feature association, and data imbalance, leading to underutilization of data in complex scenarios. Moreover, with the surge in remote sensing data volume, traditional processing methods struggle to handle the complexity and diversity of multimodal data. Therefore, the introduction of algorithms such as remote sensing large models and adaptive processing not only allows automatic alignment and fusion of multi-source heterogeneous data to achieve data complementation and enhancement but also makes breakthroughs in real-time performance and processing efficiency, thereby improving the accuracy of information extraction and analysis. This Special Issue focuses on new methods and applications for multimodal remote sensing data correlation and fusion. Studies may include the following:
- multimodal remote sensing data co-learning and modality alignment.
- multimodal remote sensing image interpretation.
- registration of remote sensing images from multi-source heterogeneous platforms.
- processing methods for multimodal and multi-temporal data.
- multimodal representation learning for remote sensing data.
- multimodal datasets and evaluation metrics.
Dr. Luomei Yixiang
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
- multimodal data alignment
- multi-source data fusion
- multimodal representation
- multimodal co-learning
- image interpretation
- multimodal machine learning
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