OSU’s Erica Fleishman helps update a key tool for predicting wildfires

A newly enhanced database is expected to help wildfire managers and scientists better predict where and when wildfires will occur, by accounting for hundreds of additional factors that influence fires’ start and spread.

“There is tremendous interest in what makes wildfires possible and what can be done to prevent them,” said Erica Fleishman, a professor at Oregon State University. “This database increases the ability to access relevant information to help prepare for and prevent wildfires.”

The Fire Program Analysis Fire-Occurrence Database was developed by the U.S. Forest Service in 2013 and has been updated five times since then. It includes basic information such as the location of ignition, date of discovery, and final size of the wildfire.

The revised database now includes many new environmental and social factors, such as topography and vegetation, social vulnerability and economic equity figures, and practical features such as the distance of the contact to the nearest road.

Fleishman said the database could not only help firefighters and managers on the ground, but it could also help energy companies assess short-term risks. For example, they could decide whether to shut off power for public safety, or land management agencies could determine whether to restrict access to public lands or ban campfires during certain times of the year.

“There seems to be a lot of policy actions that are guided to some extent by intuition or emotion rather than by a large body of evidence,” she said. “These data provide a way to increase the amount of objective evidence that needs to be considered in making those decisions.”

The team, including Fleishman, and led by Yavar Pourmohamad, a doctoral student at Boise State University, and Mojtaba Sadegh, an associate professor at Boise State, added nearly 270 additional features. The database now contains information on 2.3 million fires in the United States from 1992 to 2020.

“This provides a significantly deeper understanding of the individual and compound impacts of these characteristics on the occurrence and extent of wildfires,” Pourmohamad said. “It also identifies the unequal impacts of wildfires on different human populations and ecosystems, which in turn can inform efforts to reduce inequalities.”

Information from the database could also be incorporated into artificial intelligence and machine learning models that explain causes of past fires or predict the likelihood or impacts of future fires, said Fleishman, who is affiliated with OSU’s College of Earth, Ocean, and Atmospheric Sciences and also director of the Oregon Climate Change Research Institute.

“It’s amazing what you can infer when you have the computing power and so much information,” she said. “You can ask lots of questions that inform different actions in different places and understand what’s associated with wildfires and fire impacts.”

A paper describing the database was recently published in the journal Earth System Science Data.

Other co-authors of the paper are Eric Henderson and Sawyer Ball of Boise State; John Abatzoglou of the University of California, Merced; Erin Belval, Karen Short, Matthew Reeves, and Julia Olszewski of the USDA Forest Service Rocky Mountain Research Station; Nicholas Nauslar of the National Weather Service Storm Prediction Center; Philip Higuera of the University of Montana; Amir AghaKouchak of the University of California, Irvine; and Jeffrey Prestemon of the USDA Forest Service Southern Research Station.

The research was supported by the Joint Fire Science Program, a program of the US Forest Service and the US Department of the Interior.

By Sean Nealon