As more people across the country witness the devastation caused by wildfires and smoke, scientists are utilizing big data, technology, and collaboration to prevent the spread of these large fires.
“Stopping a fire in its early stages makes containment much easier,” said Dr. Ilkay Altintas, founder and director of the WIFIRE Lab at the University of California San Diego.
Dr. Altintas and her team have developed a platform called Firemap, which aims to reduce the response time when combating a wildfire.
This innovative platform analyzes data in unique ways, starting with the collection of general location information from 911 calls reporting fires. To improve accuracy, Firemap relies on a network of mountaintop cameras known as ALERTWildfire, designed by the Scripps Institute of Oceanography, the University of Nevada Reno, and the University of Oregon.
These cameras, powered by artificial intelligence, scan the horizon for smoke. When the smoke is detected on multiple cameras, the system can pinpoint the exact location of the fire.
This precise location data is then combined with localized weather data and real-time video from aircraft dispatched to the scene. All this information enables computer modelers to create fire growth and direction predictions.
In 2019, during the Tick Fire in Southern California, WIFIRE Lab successfully predicted that embers would cross a major highway and ignite fires on the other side. The Los Angeles County Fire Department was able to proactively deploy resources to extinguish the small fires caused by the embers before they grew larger.
WIFIRE’s Firemap software has been developed and tested in collaboration with major fire departments in Los Angeles, Ventura, and Orange Counties. It is now available to fire departments across California for their initial response to wildfires.
Additionally, the lab is working on technology to improve the management and predictability of prescribed fires, which are intentionally set to reduce forest debris. There is a national movement to embrace more prescribed fires for better fire risk management, but there is a backlog in implementing them. Altintas and her colleagues are developing detailed mapping software to assess factors like vegetation, tree canopy height, and dryness to better understand the local fire environment.
Using artificial intelligence, they can simulate how a prescribed fire will behave in the actual environment before it is ignited, reducing the risk of it getting out of control.
“The wildland fire problem can be solved if we collaborate and implement effective strategies,” Altintas emphasized.
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