New Database Empowers Wildfire Management Strategies

Scientists at Oregon State University developed a Fire Program Analysis Fire-Occurrence Database, which was described in a recent paper published in the journal Earth System Science Data.

A newly enhanced database will help scientists and wildfire managers better predict where and when wildfires may occur by incorporating hundreds of additional factors that impact fire ignition and spread.

There is a tremendous amount of interest in what enables wildfire ignitions and what can be done to prevent them. This database increases the ability to access relevant information and contribute to wildfire preparedness and prevention.

Erica Fleishman, Professor, Oregon State University

The Fire Program Analysis Fire-Occurrence Database was developed by the US in 2013 and has since undergone five updates. It includes fundamental data like the location of the wildfire's ignition, its discovery date, and its final size.

The new database has been updated with numerous new environmental and social variables, including topography and vegetation, social vulnerability, and economic justice metrics, as well as useful details like the distance between the ignition and the closest road.

According to Fleishman, the database could help land management agencies decide whether to restrict access to public lands or limit campfires during specific times of the year. Power companies could use it to assess short-term risk when deciding whether to implement a public safety power shutoff. It could also assist on-the-ground firefighters and managers.

There seem to be a lot of policies that are guided to some extent by intuition or emotions rather than by a large body of evidence. These data present one way to increase the objective evidence to consider when making those decisions.

Erica Fleishman, Professor, Oregon State University

The team, led by Yavar Pourmohamad, a doctoral student at Boise State University, and Mojtaba Sadegh, an Associate Professor at Boise State, with the contribution of Fleishman, added nearly 270 additional attributes. The database now includes information on 2.3 million fires in the United States from 1992 to 2020.

This provides a considerably deeper understanding of the individual and compounded impact of these attributes on wildfire ignitions and size. It also identifies the unequal effects of wildfires on distinct human populations and ecosystems, which can, in turn, inform efforts to reduce inequities.

Yavar Pourmohamad, Doctoral Student, Boise State University

According to Fleishman, who is connected to OSU's College of Earth, Ocean, and Atmospheric Sciences and also serves as the Director of the Oregon Climate Change Research Institute, data from the database can also be integrated into artificial intelligence and machine learning models that explain the causes of previous fires, project likelihoods, or describe the effects of future fires.

“It’s amazing what you can infer when you have the computational capacity and this much information. You can ask a lot of questions that inform different actions in different places and to understand what is associated with wildfire ignitions and fire effects,” said Fleishman.

The following people are also co-authors of the paper: 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; Jeffrey Prestemon of the USDA Forest Service Southern Research Station; Erin Belval, Karen Short, Matthew Reeves, and Julia Olszewski of the USDA Forest Service Rocky Mountain Research Station; and Eric Henderson and Sawyer Ball of Boise State.

The study was funded by the US Forest Service and the US Department of the Interior's Joint Fire Science Program. 

Journal Reference:

Pourmohamad, Y., et al. (2024) Physical, social, and biological attributes for improved understanding and prediction of wildfires: FPA FOD-Attributes dataset. doi.org/10.5194/essd-16-3045-2024