Neural-parameterized probabilistic cellular automata model for wildfire spread achieves IoU > 0.6 on 72-hour forecasts after 10-day data assimilation on six western US wildfires.
Environmental Modelling & Software 188, 106401
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FireDataForge automates retrieval and harmonization of 11 multi-source wildfire geospatial datasets into common-grid NumPy arrays for a given MTBS Event ID.
A hybrid neural-cellular automaton wildfire model is paired with gradient-based optimization of aerial drops to generate suppression plans that reduce fire-affected area while quantifying uncertainty.
citing papers explorer
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Neural-Parameterized Cellular Automata for Wildfire Spread
Neural-parameterized probabilistic cellular automata model for wildfire spread achieves IoU > 0.6 on 72-hour forecasts after 10-day data assimilation on six western US wildfires.
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FireDataForge: A Unified Framework for Multi-Source Wildfire Data Retrieval and Integration
FireDataForge automates retrieval and harmonization of 11 multi-source wildfire geospatial datasets into common-grid NumPy arrays for a given MTBS Event ID.