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Found 4 papers, 2 papers with code
Causal Graph Neural Networks for Wildfire Danger Prediction
In that direction, we propose integrating causality with Graph Neural Networks (GNNs) that explicitly model the causal mechanism among complex variables via graph learning.
SeasFire as a Multivariate Earth System Datacube for Wildfire Dynamics
The global occurrence, scale, and frequency of wildfires pose significant threats to ecosystem services and human livelihoods.
Kuro Siwo: 12.1 billion $m^2$ under the water. A global multi-temporal satellite dataset for rapid flood mapping
Kuro Siwo stands out for its unparalleled annotation quality to facilitate rapid flood mapping in a supervised setting.
Deep Learning for Global Wildfire Forecasting
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.
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