Timezone: »
Climate change is expected to aggravate wildfire activity through the exacerbation of fire weather. Improving our capabilities to anticipate wildfires on a global scale is of uttermost importance for mitigating their negative effects.In this work, we use deep learning to forecast the presence of global burned areas on a sub-seasonal scale. We present an open-access global analysis-ready datacube, which contains a variety of variables related to the seasonal and sub-seasonal fire drivers (climate, vegetation, oceanic indices, human-related variables), as well as the historical burned areas and wildfire emissions for 2000-2021. We train a deep learning model, which treats global wildfire forecasting as an image segmentation task and skillfully predicts the presence of burned areas 8, 16, 32 and 64 days ahead of time. Our work paves the way towards improved anticipation of global wildfire patterns.
Author Information
Ioannis Prapas (University of Valencia, National Observatory of Athens)
Akanksha Ahuja (University of Cambridge)
Spyros Kondylatos (National Observatory of Athens)
Ilektra Karasante (National Observatory of Athens)
Lazaro Alonso (Max Planck Institute for Biogeochemistry)
Lefki-Ioanna Panagiotou (Harokopio University of Athens)
Charalampos Davalas (Harokopio University of Athens)
Dimitrios Michail (Harokopio University of Athens)
Nuno Carvalhais (Max Planck Institute for Biogeochemistry)
IOANNIS PAPOUTSIS (National Observatory of Athens)
More from the Same Authors
-
2021 : Deep Learning Methods for Daily Wildfire Danger Forecasting »
Ioannis Prapas -
2022 : Deep Learning for Rapid Landslide Detection using Synthetic Aperture Radar (SAR) Datacubes »
Vanessa Boehm · Wei Ji Leong · Ragini Bal Mahesh · Ioannis Prapas · Siddha Ganju · Freddie Kalaitzis · Edoardo Nemni · Raul Ramos-Pollán -
2022 : Forecasting Global Drought Severity and Duration Using Deep Learning »
Akanksha Ahuja · Xin Rong Chua -
2022 : SAR-based landslide classification pretraining leads to better segmentation »
Ragini Bal Mahesh · Ioannis Prapas · Wei Ji Leong · Vanessa Boehm · Edoardo Nemni · Freddie Kalaitzis · Siddha Ganju · Raul Ramos-Pollán