Web Reference: A Python-based project to predict wildfire spread using real-time weather and fire data, paired with geospatial visualizations to aid decision-making and risk assessment. Greens could be untouched trees, red shades suggest fire, and a gray box would represent a 0 value, where a tree has burnt to the ground. We can use a pair of for() loops to identify each box to be drawn. The model extends the PyTorch nn.Module and is tailored to perform both prediction and parameter calibration. The model is based on the paper A Cellular Automata Model for Forest Fire Spread Prediction: The Case of the Wildfire That Swept Through Spetses Island in 1990.
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Last Updated: April 6, 2026
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