AI, Large Language Models, and Remote Sensing for Disaster Monitoring
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: 30 September 2026 | Viewed by 734
Special Issue Editor
Interests: remote sensing; geospatial analytics; big data analytics; scientific computations; large language models (LLMs)
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Natural disasters present escalating global challenges, with the 2024 Emergency Events Database documenting unprecedented economic losses and humanitarian impacts. Breakthroughs in artificial intelligence and advanced remote sensing technologies offer transformative opportunities for disaster monitoring, prediction, and response. Recent developments in large language models (LLMs), foundation models, and multimodal AI systems are revolutionizing how we process, interpret, and extract actionable insights from satellite imagery and Earth observation data.
Foundation models such as NASA-IBM's Prithvi and emerging vision transformers demonstrate remarkable capabilities in processing multi-spectral satellite data, enabling zero-shot transfer learning across diverse geographical regions and disaster scenarios. Large language models integrated with computer vision capabilities, such as ChatGPT's multimodal functions and specialized models such as DisasterNet-LLM, are bridging the gap between complex satellite imagery and human-interpretable insights. These AI advances enable the automated annotation of disaster-affected areas, real-time change detection, and predictive modeling with unprecedented accuracy rates exceeding 90%.
This Special Issue seeks cutting-edge research that demonstrates how advanced AI methodologies enhance natural disaster monitoring and response capabilities. We welcome original research articles, comprehensive reviews, and methodological papers showcasing innovative applications of LLMs, foundation models, vision transformers, and multimodal AI systems for disaster scenarios, including wildfires, floods, earthquakes, and extreme weather events. Priority topics include automated disaster impact assessment, AI-driven early warning systems, multimodal data fusion techniques, and the development of robust, generalizable models for diverse environmental conditions. This Special Issue aims to establish new benchmarks for AI-powered disaster monitoring while addressing critical challenges in model interpretability, data quality, and real-world deployment.
Dr. Hatef Dastour
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-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
- remote sensing
- natural disasters
- artificial intelligence
- wildfire monitoring
- flood assessment
- large language models
- disaster management
- environmental health
- vision transformers
- machine learning
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
