Fire behavior prediction models, including the Scott & Reinhardt’s (2001) Rothermel Wildland Fire Modelling System DOI:10.2737/RMRS-RP-29 and Alexander et al.’s (2006) Crown Fire Initiation & Spread model DOI:10.1016/j.foreco.2006.08.174. Also contains sample datasets, estimation of fire behavior prediction model inputs (e.g., fuel moisture, canopy characteristics, wind adjustment factor), results visualization, and methods to estimate fire weather hazard.
Fire behavior predictions using: * the Rothermel modelling system, similar to BehavePlus, NEXUS, and FuelCalc * the Crown Fire Initiation & Spread modelling system
Fire weather indices of two types: * Static (uses instantaneous weather data) * Dynamic (evolving index value based on continuous daily weather data)
Helper functions which can: * Calculate the wind adjustment factor, using a little or a lot of site-specific forest canopy information * Predict canopy fuels characteristics such as canopy bulk density and canopy fuel load * Determine fine fuel moisture from meteorological observations * Plot fire behavior outputs onto the Fire Characteristics Chart
Helper data: * Stylized surface fuel models * Surface fuel moisture scenarios
You can install firebehavioR from GitHub for the development version.
devtools::install_github("EcoFire/firebehavioR")The fireplot() function requires ggplot2; otherwise there are no package dependencies. You should have R (>= 3.4.1) installed.
The vignette in the above references GitHub repo will help you get up and going.
This package is a continual work in progress. Suggestions for
improvements are welcomed. Currently, additional helper functions are
planned: * Incorporation of models to estimate dead and live
fuel moistures using RAWS weather observations * Additional methods to
estimate canopy fuels characteristics * Visual interpretation of
fire behavior results via the Fire Characteristics Chart
GPL (>= 2)