Multimodal Fusion and Multisource Data Synergy for High-Precision Remote Sensing Target Detection and Tracking
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: 31 August 2026 | Viewed by 277
Editor
Special Issue Information
Dear Colleagues,
(1) Introduction, including scientific background and highlighting the importance of this research area.
The rapid advancement of satellite and aerial sensing technologies has led to an exponential increase in the availability of multimodal remote sensing data, encompassing optical, synthetic aperture radar (SAR), LiDAR, hyperspectral, and infrared imagery. While offering complementary information, effectively integrating these diverse data sources to achieve robust, high-precision target detection and tracking remains a significant challenge for the remote sensing community. Traditional single-source methods often struggle with complex scenarios involving adverse weather, occlusion, camouflage, and day–night cycles.
(2) Aim of the Special Issue and how the subject relates to the journal scope.
This Special Issue aims to address these challenges by soliciting cutting-edge research on novel theories, algorithms, and applications for multimodal fusion and multisource data synergy. The primary goal is to explore how heterogeneous data streams can be synergistically combined to significantly enhance the accuracy, robustness, and real-time capability of detecting, identifying, and tracking targets—such as vehicles, ships, aircraft, and infrastructure—from aerial and spaceborne platforms. We seek to foster breakthroughs that move beyond simple data concatenation toward intelligent fusion that leverages the intrinsic strengths of each modality.
(3) Suggested themes and article types for submissions.
Articles may address, but are not limited to, the following topics:
- Object detection
- Multi-sensor fusion
- Object tracking
- Multimodal Fusion
- Registration
- Advanced deep learning model
Dr. Dongyang Liu
Guest Editor
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 250 words) can be sent to the Editorial Office for assessment.
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-anonymized 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
- object detection
- multi-sensor fusion
- object tracking
- multimodal fusion
- registration
- advanced deep learning model
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