Seasonal Fire Prediction using Spatio-Temporal Deep Neural Networks

arXiv:2404.06437v1 Announce Type: cross
Abstract: With climate change expected to exacerbate fire weather conditions, the accurate anticipation of wildfires on a global scale becomes increasingly crucial for disaster mitigation. In this study, we utilize SeasFire, a comprehensive global wildfire dataset with climate, vegetation, oceanic indices, and human-related variables, to enable seasonal wildfire forecasting with machine learning. For the predictive analysis, we train deep learning models with different architectures that capture the spatio-temporal context leading to wildfires. Our investigation focuses on …

abstract arxiv change climate climate change cs.cv cs.lg dataset disaster fire global human networks neural networks prediction scale study temporal type variables weather wildfire wildfires