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A comprehensive survey of research towards AI-enabled unmanned aerial systems in pre-, active-, and post-wildfire management
Wildfires have emerged as one of the most destructive natural disasters worldwide, causing
catastrophic losses. These losses have underscored the urgent need to improve public …
catastrophic losses. These losses have underscored the urgent need to improve public …
[HTML][HTML] A systematic review of applications of machine learning techniques for wildfire management decision support
Wildfires threaten and kill people, destroy urban and rural property, degrade air quality,
ravage forest ecosystems, and contribute to global warming. Wildfire management decision …
ravage forest ecosystems, and contribute to global warming. Wildfire management decision …
Climate warming increases extreme daily wildfire growth risk in California
California has experienced enhanced extreme wildfire behaviour in recent years,–, leading
to substantial loss of life and property,. Some portion of the change in wildfire behaviour is …
to substantial loss of life and property,. Some portion of the change in wildfire behaviour is …
Machine learning based wildfire susceptibility map** using remotely sensed fire data and GIS: A case study of Adana and Mersin provinces, Turkey
In recent years, the number of wildfires has increased all over the world. Therefore, map**
wildfire susceptibility is crucial for prevention, early detection, and supporting wildfire …
wildfire susceptibility is crucial for prevention, early detection, and supporting wildfire …
Explainable artificial intelligence (XAI) detects wildfire occurrence in the Mediterranean countries of Southern Europe
The impacts and threats posed by wildfires are dramatically increasing due to climate
change. In recent years, the wildfire community has attempted to estimate wildfire …
change. In recent years, the wildfire community has attempted to estimate wildfire …
Integrated wildfire danger models and factors: A review
Wildfires have been systematically studied from the early 1950s, with significant progress in
the applied computational methodologies during the 21st century. However, modern …
the applied computational methodologies during the 21st century. However, modern …
The importance of geography in forecasting future fire patterns under climate change
An increasing amount of California's landscape has burned in wildfires in recent decades, in
conjunction with increasing temperatures and vapor pressure deficit due to climate change …
conjunction with increasing temperatures and vapor pressure deficit due to climate change …
Wildfire risk modeling
Wildfires occur worldwide and affect different territories in diverse ways. New challenges in
wildfire management are emerging, fueled by climatic, land cover, and sociodemographic …
wildfire management are emerging, fueled by climatic, land cover, and sociodemographic …
[HTML][HTML] Improving wildland fire spread prediction using deep U-Nets
Forest fires are able to cause significant damage to humans and the earth's fauna and flora.
If a fire is not detected and extinguished before it spreads, it can have disastrous results. In …
If a fire is not detected and extinguished before it spreads, it can have disastrous results. In …
Machine learning techniques for fine dead fuel load estimation using multi-source remote sensing data
Fine dead fuel load is one of the most significant components of wildfires without which
ignition would fail. Several studies have previously investigated 1-h fuel load using standard …
ignition would fail. Several studies have previously investigated 1-h fuel load using standard …