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Recurrent Convolutional Deep Neural Networks for Modeling Time-Resolved Wildfire Spread Behavior
While deep learning approaches have demonstrated the ability to predict wildfire propagation over large time periods, time-resolved fire-spread predictions are needed for active fire management.
Convolutional LSTM Neural Networks for Modeling Wildland Fire Dynamics
Machine learning techniques provide a potential approach for developing such models.
Deep Learning Models for Predicting Wildfires from Historical Remote-Sensing Data
Identifying regions that have high likelihood for wildfires is a key component of land and forestry management and disaster preparedness.
Machine Learning for Precipitation Nowcasting from Radar Images
High-resolution nowcasting is an essential tool needed for effective adaptation to climate change, particularly for extreme weather.
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