Remote Sensing and GeoAI in Natural Hazard Assessment: Emerging Trends and Applications
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: 29 October 2025 | Viewed by 37
Special Issue Editors
Interests: GeoAI; damage assessment; natural hazards; landslides; wildfire; machine/deep learning
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; machine learning algorithms; natural hazard modeling applied machine learning; computer vision; image processing
Special Issues, Collections and Topics in MDPI journals
Interests: applied machine learning; computer vision; image processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Natural hazards such as floods, landslides, earthquakes, erosion, wildfires, and droughts continue to pose significant risks to human societies and the environment. As climate change exacerbates these hazards, improving their assessment and management is becoming increasingly important. Recent advancements in remote sensing, GeoAI (geospatial artificial intelligence), and machine learning techniques are playing a pivotal role in the real-time monitoring, prediction, and analysis of these natural disasters. These innovations enable more accurate hazard prediction, vulnerability mapping, and damage assessment, leading to more efficient emergency response strategies, disaster risk reduction, and resilience-building.
This Special Issue aims to showcase the latest developments in the integration of remote sensing and GeoAI, including the application of machine learning and deep learning models for natural hazard assessment. It seeks to demonstrate the utility of these technologies to improve hazard monitoring, enhance early warning systems, and optimize disaster response strategies. This Special Issue aligns with the journal’s focus on advancing geospatial technologies, Earth observation, and AI methodologies for addressing pressing environmental challenges and disaster management issues.
We invite original research articles, reviews, and case studies that address the following themes:
- Machine learning/deep learning applications in natural hazard detection and assessment.
- The integration of remote sensing and GeoAI (including AI-based models) for improved hazard prediction and monitoring.
- The fusion of various datasets (e.g., SAR, optical, LiDAR, and UAV imagery) for enhanced hazard analysis.
- The remote sensing-based monitoring of specific hazards such as floods, landslides, wildfires, and earthquakes.
- GeoAI, machine learning, and deep learning applications in vulnerability assessment and risk mapping.
- Explainable AI (XAI) models in geohazard applications to improve the transparency and interpretability of AI-based predictions.
- Earth observation technologies for improving disaster management and emergency response.
- Case studies demonstrating the use of machine learning, deep learning, or XAI models in geohazard assessment.
Dr. Husam A. H. Al-Najjar
Dr. Bahareh Kalantar
Dr. Alfian Abdul Halin
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
- natural hazards (floods, landslides, earthquakes, erosion, wildfires, droughts, etc.)
- remote sensing
- GeoAI (geospatial artificial intelligence)
- damage assessment
- data fusion (e.g., SAR, optical, LiDAR)
- intelligent geohazard computation
- explainable AI (XAI) for geohazards
- hazard and risk assessment
- Earth observation
- vulnerability mapping
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