A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean. Deep Learning models for wildfire modeling, e.g. danger forecasting, burned area prediction, etc

Forecasting wildfire danger using deep learning.

Teleconnection-driven vision transformers for improved long-term forecasting

Data science for wildfire risk forecasting and monitoring

Wildfire risk assessment using remote sensing data - Prediction of Wildfires

Physics-informed fire occurrence prediction using structured fire indices (ISI, FFMC, DMC, DC, BUI, FWI), and latent clustering. Implements an interpretable neural model fulfilling ISI’s predictive role. Stage 1 of a modular fire propagation modeling framework grounded in physical science. Resulted in a perfect 100% accuracy

A probabilistic approach to wildfire spread prediction using a denoising diffusion model

Wildfire Management Tool (WMT) - desktop version, with the Campbell Prediction System (CPS). (This git repo was migrated from the original BitBucket/Mercurial repo.)

General Assembly Data Science Immersive (GA-DSI) Group Project - A machine learning model to predict the likelihood of a California wildfire based on historical weather and wildfire data.

This repository includes some applications of extreme value analysis techniques for modeling wildfire data. It's a work in progress :) — feel free to reach out if you'd like more details!

In this repository you will find the complete implementation of the model proposed in the paper entitled “Wildfire prediction using zero-inflated negative binomial mixed models: Application to Spain”

As part of MSBA, developed a wildfire prediction model using Machine Learning and XGBoost to predict the likelihood of a wildfire occurring given historical weather data.

This repository has the codes to predict wildfire susceptibility with various geospatial data.