Foundation Models and Intelligent Agents for Remote Sensing
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: 20 January 2027 | Viewed by 559
Editors
Interests: fundamental vision; multi-modal large language model; spatial intelligence
Interests: HD mapping; building rooftop delineation; image super-resolution; weakly/semi supervised learning; LULC classification; SAR imagery processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Remote sensing technology now delivers vast Earth observation data, yet traditional deep learning methods face challenges in multi-modal fusion, cross-domain generalization, and spatial reasoning. Foundation models—particularly multi-modal large models—coupled with intelligent agents, are transforming the field by enabling unified systems for generalizable perception, reasoning, and decision-making. Pre-trained on massive datasets, these models robustly adapt to tasks like segmentation and detection with limited samples. AI agents utilize them as a “brain” to autonomously plan and execute multi-step tasks, from dynamic monitoring to disaster response. This synergy enhances the autonomy, accuracy, and efficiency of geospatial analysis, supporting critical applications in sustainability, urban development, and climate resilience. Together, they mark a transformative step toward scalable, interpretable, and actionable remote sensing systems.
This Special Issue highlights cutting-edge research on foundation models and intelligent agents in remote sensing, focusing on autonomous spatial reasoning, multi-modal fusion, and practical applications. It bridges theoretical advances with real-world deployment, emphasizing scalability, interpretability, and efficiency. The theme aligns with the journal’s scope by integrating AI (e.g., large models, agents), sensor technologies (optical, SAR, LiDAR), and big data analytics to tackle key Earth observation challenges, including large-scale spatiotemporal modeling, autonomous planning, and trustworthy AI for environmental and urban applications.
We welcome original research and review articles on the following:
- Foundation Models: Pre-training/fine-tuning for vision–language models; multi-modal fusion (optical, SAR, LiDAR); spatiotemporal representation learning.
- Intelligent Agents: Autonomous multi-step missions (e.g., change detection, target search); agent–environment interaction; human–agent collaboration.
- Multi-Modal Learning: Cross-modal alignment; prompt engineering; retrieval-augmented generation (RAG); benchmarks for QA/scene understanding.
- Efficient and Trustworthy AI: Lightweight deployment; interpretability and uncertainty quantification; bias mitigation.
- Real-World Applications: Case studies in ecology, agriculture, disaster response, and urban planning using foundation models/agents.
Dr. Xue Yang
Dr. Hongjie He
Dr. Yue Zhou
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.
Keywords
- foundation models
- intelligent agents
- multi-modal large language models (MLLMs)
- remote sensing interpretation
- geospatial reasoning
- spatiotemporal analysis
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