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 …

Our current 1.1 C warmer world is already affecting natural and human systems in Europe
(very high confidence1). Since AR5, there has been a substantial increase in detected or …

Global fire monitoring systems are crucial to study fire behaviour, fire regimes and their
impact at the global scale. Although global fire products based on the use of Earth …

Background Wildfires, like many disturbances, can be catalysts for ecosystem change. Given
projected climate change, tree regeneration declines and ecosystem shifts following severe …

Applying artificial intelligence (AI), machine learning (ML), and big data to natural resource
management (NRM) is revolutionizing how natural resources are managed. To gain more …

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 …

Recent fire seasons in the western United States are some of the most damaging and costly
on record. Wildfires in the wildland-urban interface on the Colorado Front Range, resulting …

Over the last two decades wildfire activity, damage, and management cost within the US
have increased substantially. These increases have been associated with a number of …

Forest fires are significant ecological and environmental phenomena that can be influenced
by various climatic factors. This study used fire point records from the Canadian National …