Progress in combustion science and engineering has led to the generation of large amounts
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …

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 …

Abstract Knowledge of the causes of forest fires, and of the main driving factors of ignition, is
an indispensable step towards effective fire prevention policies. This study analyses the …

Possible causes of a forest fire ignition could be human-caused (arson, smoking, hunting,
picnic fire, shepherd fire, stubble burning) or natural-caused (lightning strikes, power lines) …

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

This paper identifies human factors associated with high forest fire risk in Spain and
analyses the spatial distribution of fire occurrence in the country. The spatial units were …

Portugal has the highest density of wildfire ignitions among southern European countries.
The ability to predict the spatial patterns of ignitions constitutes an important tool for …

Risk analysis evolved out of the need to make decisions concerning highly stochastic
events, and is well suited to analyse the timing, location and potential effects of wildfires …

This paper presents a review of concepts related to wildfire risk assessment, including the
determination of fire ignition and propagation (fire danger), the extent to which fire may …

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 …