Trend analysis and random forests models assessing spatial and temporal patterns of wildfire probability for the eastern United States

We used historic fire perimeters from Monitoring Trends in Burn Severity to assess trends and drivers of wildfires in the eastern United States. We used a suite of predictor variables relating to weather, vegetation cover, and human infrastructure to parameterize random forests models predicting fire occurrence. Models were used to project annual burned areas using all selected predictors, and to project the marginal response of annual burned areas to the most important weather predictors. This dataset includes Python scripts, raster maps of fire probability, and tables summarizing analysis results.