6 citations · 26 across the 11 of their papers we have counts for
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TeleViT1.0: Teleconnection-aware Vision Transformers for Subseasonal to Seasonal Wildfire Pattern Forecasts
Ioannis Prapas, Nikolaos Papadopoulos, Nikolaos-Ioannis Bountos +3
Forecasting wildfires weeks to months in advance is difficult, yet crucial for planning fuel treatments and allocating resources. While short-term predictions typically rely on loc…
FireCastNet: Earth-as-a-Graph for Seasonal Fire Prediction
Dimitrios Michail, Charalampos Davalas, Konstantinos Chafis +5
With climate change intensifying fire weather conditions globally, accurate seasonal wildfire forecasting has become critical for disaster preparedness and ecosystem management. We…
Seasonal Fire Prediction using Spatio-Temporal Deep Neural Networks
Dimitrios Michail, Lefki-Ioanna Panagiotou, Charalampos Davalas +4
With climate change expected to exacerbate fire weather conditions, the accurate anticipation of wildfires on a global scale becomes increasingly crucial for disaster mitigation. I…
SeasFire as a Multivariate Earth System Datacube for Wildfire Dynamics
Ilektra Karasante, Lazaro Alonso, Ioannis Prapas +3
The global occurrence, scale, and frequency of wildfires pose significant threats to ecosystem services and human livelihoods. To effectively quantify and attribute the antecedent…
TeleViT: Teleconnection-driven Transformers Improve Subseasonal to Seasonal Wildfire Forecasting
Ioannis Prapas, Nikolaos Ioannis Bountos, Spyros Kondylatos +3
Wildfires are increasingly exacerbated as a result of climate change, necessitating advanced proactive measures for effective mitigation. It is important to forecast wildfires week…
Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean
Spyros Kondylatos, Ioannis Prapas, Gustau Camps-Valls +1
We introduce Mesogeos, a large-scale multi-purpose dataset for wildfire modeling in the Mediterranean. Mesogeos integrates variables representing wildfire drivers (meteorology, veg…