Remote Sensing and GIS for Natural Hazards Mapping
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".
Deadline for manuscript submissions: closed (10 April 2024) | Viewed by 1574
Special Issue Editor
Interests: remote sensing of inland lakes; water quality; water environment; aquatic ecology; machine learning; GIS
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Natural risk assessment is one of the disciplines that has seen the greatest advances in the field of GIS and remote sensing in recent years. The implementation of more sophisticated analysis methodologies, more accurate remote sensing systems, more innovative damage assessment protocols, etc., are some of the various tools that have improved the management of these phenomena.
This Special Issue aims to provide an outlet for peer-reviewed publications that implement state-of-the-art methods and techniques incorporating RS technology, ML methods and GIS so as to map, monitor, evaluate and assess natural hazards.
Potential topics of interest include (but are not limited to) regional or global case studies concerning natural risk phenomena prediction and assessment, software development and the implementation of machine learning, optimization, deep learning techniques, meta-heuristic algorithms and risk mapping methodology. Specifically, this Special Issue aims to cover, but is not limited to, the following areas:
- Monitoring, mapping and assessing earthquakes, landslides, floods, wildfires, soil erosion and water ecology;
- Evaluating the loss and damages after earthquakes, floods, landslides, wildfires, soil erosion and water ecology.
Dr. Ronghua Ma
Guest Editor
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Keywords
- remote sensing
- GIS
- machine learning
- deep learning
- risk mapping methodology
- hazardous and risk mapping
- damage assessment
- natural hazards
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