Applications of Remote Sensing for Natural Hazard and Environment Monitoring

Dear Colleagues,

Natural hazards can lead to severe damage to the environment and to society, not only in the areas where such events occur, but also in neighboring regions or entire countries. In recent years, climate change and other factors have led to the amplification of such events and also to them occurring more frequently. The integration of Earth observation-based methodologies into data collected from multiple sensors combines the advantages of these data sources and systematically provides critical, reliable, and up-to-date information, covering a wide range of multidisciplinary scientific topics related to natural hazards and environmental monitoring applications.

From this perspective, research efforts are needed to develop methods and tools for the integration of sensors with different spatial, spectral, and temporal characteristics. This is expected to enhance the capabilities of EO-sensor-driven approaches and strategies to mitigate the disastrous effects of natural hazards and expand our multi-temporal and multi-scale monitoring of the environment. This Special Issue aims to collect high-quality contributions to the advancement of satellite remote-sensing technologies/solutions for environmental monitoring and natural hazard detection, monitoring and modelling, risk and impact assessments, disaster management, early warning systems, and decision support systems for the following:

• Geohazards: earthquakes, landslides, soil erosion, land degradation/desertification, etc.
• Forest fires: burnt-area mapping, fire monitoring and spread, etc.
• Hydrometeorological hazards: floods, extreme weather events, etc.
• Epidemics/health.
• Multi-hazards: the combination of two or more of the hazards mentioned above.

Dr. Marios Tzouvaras
Dr. Chris Danezis
Dr. Charalampos Kontoes
Prof. Dr. Fabio Del Frate
Guest Editors

Manuscript Submission Information

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• natural hazards
• environmental monitoring
• deformation monitoring
• change detection
• SAR
• multispectral data
• GIS
• time series analysis
• big data
• data fusion