A Brigham Young University (BYU) student has used machine learning and math to improve a key tool that firefighters rely on while they are out in the field battling wildfires. โI think itโs really cool when you study math, you end up working on problems that you never would have really guessed, like I have done things in so many different fields,โ Jane Housley is a BYU mathematics graduate student and a wildfire modeling researcher.
Housley recently wrapped up her master thesis in partnership with the U.S. Forest Serviceโs Missoula Fire Sciences Lab and focused on improving WindNinja. WindNinja is used by fire crews and analysts to predict how wind will move through terrain during a fire. It is a simulation tool created by the Missoula Fire Sciences lab.
According to the U.S. Forest Service, the behavior of wildland fires and the dispersion of smoke from these fires depends, in part, on ambient and fire-induced winds that work to spread fires across the landscape and mix fire emissions into the atmosphere. Housleyโs study focused on improving the device to model whatโs called a cavity zone. Thatโs the area directly behind a mountain or ridge where wind tends to swirl backward and create a whirlpool-like motion.
