Applications of Synthetic Aperture Radar (SAR) in Natural Hazard
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: 31 October 2025 | Viewed by 81
Special Issue Editors
Interests: SAR remote sensing; natural hazard analysis; GIS; disaster management; AI applications in remote sensing
2. Department of Geophysical Exploration, Korea University of Science and Technology, 217, Gajeong-ro, Yuseong-gu, Daejeon 34113, Republic of Korea
Interests: integrating machine/deep learning algorithms; metaheuristic optimization approaches; remote sensing data to address global land-related challenges
Interests: change detection; hyperspectral imaging; soil salinity; pattern recognition; satellite oceanography; optical remote sensing; SAR; InSAR; thermal remote sensing; image matching; anomaly detection
Special Issues, Collections and Topics in MDPI journals
Interests: climate change; SAR remote sensing ; nature-based solutions; ecosystem services; sustainable urban development; risk assessment; machine learning; smart cities
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Synthetic Aperture Radar (SAR) is recognized as a robust remote sensing technology that provides unique observational capabilities due to its independence from solar illumination and atmospheric conditions, thus ensuring consistent data collection in all-weather and day-and-night scenarios. The growing frequency and severity of natural hazards, largely attributed to climate change and environmental degradation, emphasize the necessity of reliable remote sensing tools. SAR technology is pivotal for timely and precise hazard identification, risk assessment, mitigation planning, and emergency response.
This Special Issue seeks to gather pioneering research that illustrates the forefront applications of SAR imagery in identifying, monitoring, and addressing diverse natural hazards. The issue's focus is deeply embedded within the scope of Remote Sensing, highlighting methodological innovations, empirical applications, and theoretical insights.
Potential topics include, but are not limited to:
- SAR-based monitoring and characterization of floods, landslides, earthquakes, volcanic eruptions, and related hazards
- Advanced SAR data processing methods and novel algorithms for accurate hazard detection
- Multi-temporal and interferometric SAR (InSAR) methodologies for ground deformation analysis
- Integration of SAR and optical data, alongside other ancillary datasets, for comprehensive hazard evaluation
- Application of machine learning and deep learning techniques in SAR image interpretation for hazard prediction
- Deep learning approaches specifically tailored for SAR imagery classification, segmentation, and hazard delineation
- SAR time-series deformation analysis and change detection methods for hazard monitoring
- Advanced segmentation techniques and their applications in hazard identification and assessment
- Validation frameworks and accuracy assessments of SAR-derived products under hazard conditions
- Strategic disaster management and emergency response approaches informed by SAR-derived data
We welcome submissions of original research papers, comprehensive review articles, and detailed case studies.
Dr. Mahdi Panahi
Dr. Fatemeh Rezaie
Dr. Mahdi Hasanlou
Dr. Zahra Kalantari
Guest Editors
Manuscript Submission Information
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Keywords
- synthetic aperture radar (SAR)
- natural hazard assessment
- SAR interferometry (InSAR)
- SAR image segmentation
- SAR change detection
- SAR time-series analysis
- deep learning in remote sensing
- disaster risk reduction
- ground deformation analysis
- SAR data fusion
- remote sensing for disaster management
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