FireDataForge turns one MTBS fire ID into a stack of harmonized, analysis-ready geospatial layers (perimeters, FRP, terrain, fuels, weather, and more) from many sources.
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Sep 10, 2026 - Python
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mtbs
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This repository contains the logic associated with the research manuscript: "Roadless status under The Roadless Area Conservation Rule is not associated with increased wildfire in the US National Forest System".
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Sep 9, 2026 - Jupyter Notebook
Remote-sensing experiments on wildfire burn-severity mapping, cross-event transfer, and pre-fire prediction using Landsat, MTBS, and CanLaBS.
machine-learning random-forest geospatial landsat remote-sensing wildfire mtbs burn-severity spatial-cross-validation canlabs
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Aug 26, 2026 - Python
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