Fighting fire with data

The wildfires that consumed the west coast of the U.S. this year were a part of a larger pattern. Experts warn that climate change is increasing the severity and extent of wildfires over the past several, and their impact on communities, the environment and the economy is growing.

Industrial engineer and professor Oleg Prokopyev at the University of Pittsburgh’s Swanson School of Engineering is utilizing optimization to find a solution to this problem. Prokopyev will collaborate with Lewis Ntaimo and Jianbang Gan at Texas A&M University on the project, titled “Collaborative Research: Fuel Treatment Planning Optimization for Wildfire Management.”

The National Science Foundation recently awarded $550,000 for the work, with $270,000 designated for Pitt.

“One strategy for mitigating forest fires is fuel treatment, which involves strategically removing some of the vegetation–the ‘fuel’ for the fire–with controlled burns, grazing or mechanical thinning,” said Prokopyev. “Our models will help predict when, where and how to best implement these methods.”

Using advanced decision-making methods, such as mixed-integer optimization and simulation, the project will provide a better understanding of what types of fuel treatment options would be most effective, and when to implement them.

In addition, the project will use historical data from the Texas A&M Forest Service to calibrate and validate the developed mathematical models.

The project began Sept. 1, 2020 and is expected to last three years.

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