Wildfire Forecasting

Wildfire forecasting aims to predict the location, intensity, and spread of wildfires using various data sources and advanced modeling techniques. Current research heavily utilizes deep learning, employing architectures like recurrent neural networks (RNNs, including LSTMs and GRUs), convolutional neural networks (CNNs), graph neural networks (GNNs), and vision transformers, often integrated with ensemble methods and transfer learning to improve accuracy and efficiency. These models leverage multi-source spatiotemporal data, including satellite imagery, weather patterns, vegetation indices, and human activity data, to enhance predictive capabilities. Improved forecasting significantly aids wildfire management, disaster mitigation, and resource allocation, contributing to both ecological preservation and human safety.

Papers

September 4, 2024

Neural Networks with LSTM and GRU in Modeling Active Fires in the Amazon
Ramon Tavares, Ricardo Olinda
Neural Network Recurrent Neural Network Long Short Term Memory Gated Recurrent Unit Target Amazon Ally Extreme Weather Wildfire Forecasting

August 30, 2024

Deep learning surrogate models of JULES-INFERNO for wildfire prediction on a global scale
Sibo Cheng, Hector Chassagnon, Matthew Kasoar, Yike Guo, Rossella Arcucci
Surrogate Model Fighting Fire Global Scale Hyperbolic Model Wildfire Forecasting Wildfire Prediction Wildfire Danger

July 20, 2024

Enhancing Wildfire Forecasting Through Multisource Spatio-Temporal Data, Deep Learning, Ensemble Models and Transfer Learning
Ayoub Jadouli, Chaker El Amrani
Deep Learning Transfer Learning Ensemble Model Temporal Data SpatioTemporal Data Wildfire Forecasting Meteorological Satellite Wildfire Prediction

April 9, 2024

Seasonal Fire Prediction using Spatio-Temporal Deep Neural Networks
Dimitrios Michail, Lefki-Ioanna Panagiotou, Charalampos Davalas, Ioannis Prapas, Spyros Kondylatos, Nikolaos Ioannis Bountos, Ioannis Papoutsis
Spatio Temporal Wildfire Forecasting

March 13, 2024

Causal Graph Neural Networks for Wildfire Danger Prediction
Shan Zhao, Ioannis Prapas, Ilektra Karasante, Zhitong Xiong, Ioannis Papoutsis, Gustau Camps-Valls, Xiao Xiang Zhu
Graph Neural Network Graph Learning Wildfire Forecasting Wildfire Danger

February 11, 2024

Explainable Global Wildfire Prediction Models using Graph Neural Networks
Dayou Chen, Sibo Cheng, Jinwei Hu, Matthew Kasoar, Rossella Arcucci
Graph Neural Network Cluster Structure Wildfire Forecasting Wildfire Prediction Wildfire Data

December 12, 2023

November 27, 2023

Reinforcement Learning for Wildfire Mitigation in Simulated Disaster Environments
Alexander Tapley, Marissa Dotter, Michael Doyle, Aidan Fennelly, Dhanuj Gandikota, Savanna Smith, Michael Threet, Tim Welsh
Reinforcement Learning Fighting Fire Wildfire Forecasting

September 5, 2023

Generative Algorithms for Fusion of Physics-Based Wildfire Spread Models with Satellite Data for Initializing Wildfire Forecasts
Bryan Shaddy, Deep Ray, Angel Farguell, Valentina Calaza, Jan Mandel, James Haley, Kyle Hilburn, Derek V. Mallia, Adam Kochanski, Assad Oberai
Hybrid Fusion Fighting Fire Satellite Data Generative Algorithm Fire Detection Wildfire Forecasting Wildfire Data Wildfire Modeling

August 17, 2023

Estimating fire Duration using regression methods
Hansong Xiao
Regression Model Grid Based Wildfire Forecasting Standard Random Forest

June 19, 2023

TeleViT: Teleconnection-driven Transformers Improve Subseasonal to Seasonal Wildfire Forecasting
Ioannis Prapas, Nikolaos Ioannis Bountos, Spyros Kondylatos, Dimitrios Michail, Gustau Camps-Valls, Ioannis Papoutsis
Earth System Long Term Forecasting Global Scale Wildfire Forecasting

May 3, 2023

Widespread Increases in Future Wildfire Risk to Global Forest Carbon Offset Projects Revealed by Explainable AI
Tristan Ballard, Matthew Cooper, Chris Lowrie, Gopal Erinjippurath
Explainable AI Long Term Wildfire Forecasting Forest Carbon Wildfire Risk

December 29, 2022

Multimodal Wildland Fire Smoke Detection
Siddhant Baldota, Shreyas Anantha Ramaprasad, Jaspreet Kaur Bhamra, Shane Luna, Ravi Ramachandra, Eugene Zen, Harrison Kim, Daniel Crawl, Ismael Perez, Ilkay Altintas, Garrison W. Cottrell, Mai H. Nguyen
Wildfire Forecasting Forest Wildfire Observation Detection Time

November 1, 2022

Deep Learning for Global Wildfire Forecasting
Ioannis Prapas, Akanksha Ahuja, Spyros Kondylatos, Ilektra Karasante, Eleanna Panagiotou, Lazaro Alonso, Charalampos Davalas, Dimitrios Michail, Nuno Carvalhais, Ioannis Papoutsis
Deep Learning Wildfire Forecasting

August 19, 2022

Wildfire Forecasting with Satellite Images and Deep Generative Model
Thai-Nam Hoang, Sang Truong, Chris Schmidt
Satellite Image Deep Generative Model Video Prediction Wildfire Forecasting Wildfire Prediction Autoregressive Image Stochastic Video Prediction

November 4, 2021

Deep Learning Methods for Daily Wildfire Danger Forecasting
Ioannis Prapas, Spyros Kondylatos, Ioannis Papoutsis, Gustau Camps-Valls, Michele Ronco, Miguel-Ángel Fernández-Torres, Maria Piles Guillem, Nuno Carvalhais
Deep Learning Spatio Temporal Context Fire Occurrence Wildfire Forecasting Wildfire Danger