Our team recently compiled a summary of the different datasets we have developed to study wildfire behavior using fire-tracking algorithms. These algorithms ingest gridded pixel-level satellite thermal anomaly imagery to track wildfire occurrence, expansion, and extinction. We currently use these datasets to evaluate physics-based fire spread models and to develop new machine-learning models for fire prediction.
Ph.D. student positions available
The Climate, Carbon, and Wildfire Dynamics Lab is looking to hire 2 to 3 Ph.D. students through the Department of Earth System Science. Students interested in studying wildfire dynamics, ecosystem carbon and water fluxes, climate change feedback with the land and...