Multimodal Sensing and Fusion Driven Intelligent Computing in Advanced Remote Sensing

Dear Colleagues,

Advanced remote sensing is rapidly evolving from single-sensor observation to multimodal sensing systems that integrate optical, hyperspectral, SAR, LiDAR, thermal, and UAV-borne data. This transition is accelerated by recent advances in intelligent computing, including deep learning, foundation models, cross-modal representation learning, and physics-informed data analysis. However, the heterogeneity, high dimensionality, and varying spatial–temporal resolutions of remote sensing data still pose major challenges to robust interpretation, efficient fusion, and trustworthy decision support. Research in this area is therefore essential for improving Earth observation capabilities and enabling more accurate, scalable, and application-oriented remote sensing solutions.

This Special Issue aims to collect original studies that advance the fields of multimodal sensing, information fusion, and intelligent computing for remote sensing image processing and interpretation. This aim is closely aligned with the scope of Remote Sensing because it addresses data acquisition; image analysis; algorithm development; feature extraction; scene understanding; and practical applications across land, ocean, atmosphere, agriculture, ecology, urban systems, and infrastructure monitoring. Contributions that bridge sensor innovation with computational intelligence and domain-level applications are particularly encouraged.

Suggested themes include multimodal remote sensing data fusion; hyperspectral and SAR image analysis; LiDAR–image integration; cross-modal feature learning; multimodal foundation models for Earth observation; weakly supervised, self-supervised, or transfer learning for remote sensing; intelligent target detection, change detection, and semantic segmentation; uncertainty-aware and explainable remote sensing AI; edge/cloud collaborative sensing; and real-world applications in environmental monitoring, smart agriculture, disaster response, transportation, and urban analytics. We welcome research articles, review papers, technical notes, and application-oriented studies.

Prof. Dr. Jinchang Ren
Prof. Dr. Jon Atli Benediktsson
Dr. Maher Assaad
Dr. Jaime Zabalza
Dr. Erlei Zhang
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 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.