Modern Technologies and Applications for Innovative Forest Fire Management
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Forestry".
Deadline for manuscript submissions: closed (25 March 2024) | Viewed by 502
Special Issue Editors
Interests: artificial Intelligence; distributed information systems; internet technologies; machine learning; environmental intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: forest fires; land-use/land-cover mapping; pre-fire planning and post-fire assessment; remote sensing; GIS; forest management
Special Issues, Collections and Topics in MDPI journals
Interests: computer vision; image understanding; deep learning; machine learning
Interests: computer vision; artificial intelligence; wildfire propagation; wildfire propagation potential; wildfire risk; computer security
Special Issue Information
Dear Colleagues,
Wildfire management plays a crucial role in improving the sustainability of forests by mitigating the negative impacts of wildfires and promoting ecological resilience. Advancement of novel sensing technologies, including remote sensing, joined with data from citizen volunteers and publicly available data, provides a fertile ground for innovation and excellence in forest management. Recent advances in robotics have allowed cutting-edge innovations to be made in the surveillance and suppression of wildfires. New forecasting models and techniques for natural and climate changes, in addition to providing insight into future regimes, help guide methods for mitigating their effects.
This Special Issue invites original submissions and review articles describing innovations in conceptual, technical and computational methods and solutions in wildfire management for sustainable forestry.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but not limited to) the following:
Wildfire prevention:
- Wildfire monitoring;
- Automatic early wildfire detection;
- Machine learning techniques for wildfire prediction;
- Wildfire risk assessment;
- Future and fire resilient landscape management;
- Spatial analysis for firebreaks planning;
- Remote sensing wildfire risk prediction;
- Decision support systems for wildfire prevention;
- Citizen science for wildfire risk assessment and prevention;
- Meteorology and forecasting in seasonal and daily fire risk assessment.
Wildfire suppression:
- Wildfire real time surveillance;
- Sensor systems for fire monitoring, surveillance and probing;
- Wildfire digital twin technologies and applications;
- Decision support systems for efficient fire suppression;
- Fire propagation and behaviour simulation and prediction;
- Wind speed and direction interpolation for wildfire simulation and modeling.
Wildfire post analysis:
- Remote sensing for fire analysis;
- Using volunteer geographical information (VGI) for fire analysis;
- Statistical approaches for fire season analysis;
- Data mining techniques for spatial and temporal distribution of fire reports;
- Mapping fire ignitions and spatial analysis;
- Remote sensing and mapping in wildfire management;
- Fuels and fuel load estimation.
Wildfires in future:
- Climate change scenarios and future fire regimes;
- Land use change detection and fire susceptibility.
We look forward to receiving your contributions.
Dr. Ljiljana Seric
Prof. Dr. Ioannis Gitas
Prof. Dr. Damir Krstinić
Dr. Marin Bugaric
Dr. Fermín Alcasena
Guest Editors
Manuscript Submission Information
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Keywords
- forest resilience
- wildfire prevention
- forest fire simulation
- wildfire suppression
- wildfire monitoring, wildfire risk assessment
- forest post-fire recovery
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