Artificial intelligence has been applied in wildfire science and management since the 1990s,
with early applications including neural networks and expert systems. Since then, the field …

Wildfires have been systematically studied from the early 1950s, with significant progress in
the applied computational methodologies during the 21st century. However, modern …

Because of their rapid maneuverability, extended operational range, and improved
personnel safety, unmanned aerial vehicles (UAVs) with vision-based systems have great …

Predicting wildfire spread is critical for land management and disaster preparedness. To this
end, we present “Next Day Wildfire Spread,” a curated, large-scale, multivariate dataset of …

The increasing global concern about wildfires, mostly caused by people, has triggered the
development of human-caused fire occurrence models in many countries. The premise is …

Forest fires are one of the most important factors in environmental risk assessment and it is
the main cause of forest destruction in the Mediterranean region. Forestlands have a …

Wildfires are a major natural hazard that lead to deforestation, carbon emissions, and loss of
human and animal lives every year. Effective predictions of wildfire occurrence and burned …

Natural hazard risk is largely projected to increase in the future, placing growing
responsibility on decision makers to proactively reduce risk. Consequently, decision support …

Increasing Australian bush-fire frequencies over the last decade has indicated a major
climatic change in coming future. Understanding such climatic change for Australian bush …

The Himachal Pradesh district's biggest natural disaster is the forest fire. Forest fire threat
evaluation, model construction, and forest management using geographic information …