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 …

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 threaten a large part of the world's forests, communities, and industrial plants,
triggering technological accidents (Natechs). Forest fire modelling with respect to …

In this paper, we present an in-depth analysis of the use of convolutional neural networks
(CNN), a deep learning method widely applied in remote sensing-based studies in recent …

The presented research was performed in order to model the fire risk in a part of Hyrcanian
forests of Iran. The fuzzy sets integrated with analytic hierarchy process (AHP) in a decision …

Fire danger assessment is a vital issue to alleviate the impacts of wildland fires. In this study,
a fire danger assessment system is proposed, which extensively uses geographical …

Predicting the spatial distribution of wildfires is an important step towards proper wildfire
management. In this work, we applied two data-mining models commonly used to predict fire …

This study was done to evaluate the efficiency of three methods to predict the high-risk areas
for fire in District Three of Neka Zalemroud forests located in Mazandaran Province, Iran …

In the framework of climate change, the hazard caused by wildfires approaching the
anthropic settlements is raising an increasing concern. Fatalities and relevant damage to …

Wildfires are a major environmental, economic, and social threat. In Central Côte d'Ivoire,
they are among the biggest environmental and forestry problems during the dry season …