Wildfire Prediction

Wildfire prediction research aims to improve forecasting accuracy and timeliness to mitigate the devastating impacts of wildfires. Current efforts heavily utilize machine learning, particularly deep learning architectures like convolutional neural networks (CNNs), recurrent neural networks (RNNs, including LSTMs), and graph neural networks (GNNs), often integrated with ensemble methods and transfer learning, to analyze diverse data sources including satellite imagery, weather patterns, and topographical features. These models are evaluated using metrics such as accuracy, error rates, and explainability measures, with a growing emphasis on understanding model uncertainty and the underlying stochastic processes driving fire spread. Improved prediction capabilities are crucial for effective resource allocation, risk assessment, and ultimately, reducing wildfire damage and saving lives.

Papers

November 14, 2024

Deep Autoencoders for Unsupervised Anomaly Detection in Wildfire Prediction
İrem Üstek, Miguel Arana-Catania, Alexander Farr, Ivan Petrunin
Human Prediction Supervised Autoencoder Unsupervised Learning Unsupervised Anomaly Detection Fully Connected Neural Network Wildfire Prediction Forest Wildfire Observation Deep Autoencoders

November 12, 2024

Comprehensive and Comparative Analysis between Transfer Learning and Custom Built VGG and CNN-SVM Models for Wildfire Detection
Aditya V. Jonnalagadda, Hashim A. Hashim, Andrew Harris
Convolutional Neural Network Transfer Learning Comparative Study Support Vector Machine Wildfire Detection Wildfire Prediction

November 9, 2024

Advanced Wildfire Prediction in Morocco: Developing a Deep Learning Dataset from Multisource Observations
Ayoub Jadouli, Chaker El Amrani
Deep Learning Data Set Multi Source Wildfire Prediction Wildfire Dynamic Wildfire Danger

September 18, 2024

Bushfire Severity Modelling and Future Trend Prediction Across Australia: Integrating Remote Sensing and Machine Learning
Shouthiri Partheepan, Farzad Sanati, Jahan Hassan
Machine Learning Remote Sensing Future Trend Wildfire Prediction

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 Wildfire Forecasting Hyperbolic Model 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 Wildfire Prediction Meteorological Satellite

April 1, 2024

Explainable AI Integrated Feature Engineering for Wildfire Prediction
Di Fan, Ayan Biswas, James Paul Ahrens
Machine Learning Model Human Prediction Random Forest Interpretable Feature Fire Occurrence Wildfire Prediction

March 20, 2024

Next day fire prediction via semantic segmentation
Konstantinos Alexis, Stella Girtsou, Alexis Apostolakis, Giorgos Giannopoulos, Charalampos Kontoes
Semantic Segmentation Binary Classification Deep Learning Pipeline Wildfire Prediction

February 23, 2024

Has the Deep Neural Network learned the Stochastic Process? A Wildfire Perspective
Harshit Kumar, Beomseok Kang, Biswadeep Chakraborty, Saibal Mukhopadhyay
Deep Neural Network Stochastic Process Stochastic Dynamical System Wildfire Prediction

February 14, 2024

Statistical and Machine Learning Models for Predicting Fire and Other Emergency Events
Dilli Prasad Sharma, Nasim Beigi-Mohammadi, Hongxiang Geng, Dawn Dixon, Rob Madro, Phil Emmenegger, Carlos Tobar, Jeff Li, Alberto Leon-Garcia
Machine Learning Model Predictive Model Prediction Model Wildfire Prediction Public Emergency Event Prediction Method

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

September 4, 2023

An FPGA smart camera implementation of segmentation models for drone wildfire imagery
Eduardo Guarduño-Martinez, Jorge Ciprian-Sanchez, Gerardo Valente, Vazquez-Garcia, Gerardo Rodriguez-Hernandez, Adriana Palacios-Rosas, Lucile Rossi-Tisson, Gilberto Ochoa-Ruiz
Segmentation Model Segmentation Performance Field Programmable Gate Array Wildfire Detection Camera Based Wildfire Prediction

August 5, 2023

A generative model for surrogates of spatial-temporal wildfire nowcasting
Sibo Cheng, Yike Guo, Rossella Arcucci
Data Driven Nowcasting Surrogate Assisted Version Wildfire Prediction

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

August 18, 2022

A Multi-Modal Wildfire Prediction and Personalized Early-Warning System Based on a Novel Machine Learning Framework
Rohan Tan Bhowmik
System Description Wildfire Prediction Wildfire Data Wildfire Dynamic

July 24, 2022

A Parallel Novelty Search Metaheuristic Applied to a Wildfire Prediction System
Jan Strappa, Paola Caymes-Scutari, Germán Bianchini
Simulation Study Causal Relation Propagation Environment Wildfire Prediction Parallel Optimization New Metaheuristic Wildfire Dynamic

March 23, 2022

An Emulation Framework for Fire Front Spread
Andrew Bolt, Joel Janek Dabrowski, Carolyn Huston, Petra Kuhnert
Wildfire Prediction Spread Model

December 4, 2021

Next Day Wildfire Spread: A Machine Learning Data Set to Predict Wildfire Spreading from Remote-Sensing Data
Fantine Huot, R. Lily Hu, Nita Goyal, Tharun Sankar, Matthias Ihme, Yi-Fan Chen
Machine Learning Raw Data Remote Sensing Fighting Fire Forest Wildfire Observation Wildfire Prediction

November 28, 2021

Learning Wildfire Model from Incomplete State Observations
Alissa Chavalithumrong, Hyung-Jin Yoon, Petros Voulgaris
Remote Sensing Spatiotemporal Modeling Wildfire Prediction Forest Wildfire Observation State Observation Wildfire Modeling

Wildfire Prediction

Papers

Deep Autoencoders for Unsupervised Anomaly Detection in Wildfire Prediction

Comprehensive and Comparative Analysis between Transfer Learning and Custom Built VGG and CNN-SVM Models for Wildfire Detection

Advanced Wildfire Prediction in Morocco: Developing a Deep Learning Dataset from Multisource Observations

Bushfire Severity Modelling and Future Trend Prediction Across Australia: Integrating Remote Sensing and Machine Learning

Deep learning surrogate models of JULES-INFERNO for wildfire prediction on a global scale

Enhancing Wildfire Forecasting Through Multisource Spatio-Temporal Data, Deep Learning, Ensemble Models and Transfer Learning

Explainable AI Integrated Feature Engineering for Wildfire Prediction

Next day fire prediction via semantic segmentation

Has the Deep Neural Network learned the Stochastic Process? A Wildfire Perspective

Statistical and Machine Learning Models for Predicting Fire and Other Emergency Events

Explainable Global Wildfire Prediction Models using Graph Neural Networks

An FPGA smart camera implementation of segmentation models for drone wildfire imagery

A generative model for surrogates of spatial-temporal wildfire nowcasting

Wildfire Forecasting with Satellite Images and Deep Generative Model

A Multi-Modal Wildfire Prediction and Personalized Early-Warning System Based on a Novel Machine Learning Framework

A Parallel Novelty Search Metaheuristic Applied to a Wildfire Prediction System

An Emulation Framework for Fire Front Spread

Next Day Wildfire Spread: A Machine Learning Data Set to Predict Wildfire Spreading from Remote-Sensing Data

Learning Wildfire Model from Incomplete State Observations