Trending and emerging prospects of physics-based and ML-based wildfire spread models: A comprehensive review

H Singh, LM Ang, T Lewis, D Paudyal, M Acuna… - Journal of Forestry …, 2024 - Springer
The significant threat of wildfires to forest ecology and biodiversity, particularly in tropical
and subtropical regions, underscores the necessity for advanced predictive models amidst …

Wildfire risk prediction: A review

Z Xu, J Li, S Cheng, X Rui, Y Zhao, H He… - ar** using a hierarchical approach with machine learning and satellite imagery
S Illarionova, P Tregubova, I Shukhratov, D Shadrin… - Scientific Reports, 2024 - nature.com
Remote sensing of forests is a powerful tool for monitoring the biodiversity of ecosystems,
maintaining general planning, and accounting for resources. Various sensors bring together …

New forest fire assessment model based on artificial neural network and analytic hierarchy process or fuzzy-analytic hierarchy process methodology for fire …

M Tahri, S Badr, Z Mohammadi, J Kašpar… - … Applications of Artificial …, 2024 - Elsevier
Forest fires significantly disrupt global ecosystems. Many forecasting techniques predict fire
activity and allocate prevention resources, but various factors are missing from the …

Physics-informed neural networks for parameter learning of wildfire spreading

K Vogiatzoglou, C Papadimitriou, V Bontozoglou… - Computer Methods in …, 2025 - Elsevier
Wildland fires pose a terrifying natural hazard, underscoring the urgent need to develop data-
driven and physics-informed digital twins for wildfire prevention, monitoring, intervention …

[HTML][HTML] A Forest Fire Prediction Model Based on Meteorological Factors and the Multi-Model Ensemble Method

S Choi, M Son, C Kim, B Kim - Forests, 2024 - mdpi.com
More than half of South Korea's land area is covered by forests, which significantly increases
the potential for extensive damage in the event of a forest fire. The majority of forest fires in …

Wildfire Risk Mitigation through Systems Analysis of the Planetary Emergency

JH Lambert, RR Dorn, BM Ayyub… - … Journal of Civil …, 2024 - ascelibrary.org
Recognizing wildfires as a multiscale planetary emergency, this paper describes a systems
analysis of technology countermeasures, with special attention to Sicily, California, and …

[HTML][HTML] Fire-Image-DenseNet (FIDN) for predicting wildfire burnt area using remote sensing data

B Pang, S Cheng, Y Huang, Y **, Y Guo… - Computers & …, 2025 - Elsevier
Predicting the extent of massive wildfires once ignited is essential to reduce the subsequent
socioeconomic losses and environmental damage, but challenging because of the …

[HTML][HTML] Machine Learning and Deep Learning for Wildfire Spread Prediction: A Review

HS Andrianarivony, MA Akhloufi - Fire, 2024 - mdpi.com
The increasing frequency and intensity of wildfires highlight the need to develop more
efficient tools for firefighting and management, particularly in the field of wildfire spread …

[HTML][HTML] Enhancing prediction of wildfire occurrence and behavior in Alaska using spatio-temporal clustering and ensemble machine learning

A Ahajjam, M Allgaier, R Chance, E Chukwuemeka… - Ecological …, 2025 - Elsevier
Wildfires are an integral part of Alaska's ecological landscape, sha** its boreal forests and
tundra. However, recent shifts in wildfire frequency, intensity, and seasonality pose …