Fire, Water, and Signal Processing: Researchers are turning to signal processing to help them address challenges posed by two of the planet’s fundamental forces

Wildfire Damage Watch

Stanford University and California Polytechnic State University (Cal Poly) researchers have developed a system that’s designed to help people driven out of their homes by massive wildfires to discover if their residences were damaged or destroyed by the giant infernos. The team’s DamageMap technology combines artificial intelligence (AI) and signal processing to provide rapid visual building assessments, helping displaced homeowners to see if their homes were damaged or destroyed by the blaze. Instead of comparing before and after photos, the researchers trained their system to rely entirely on postfire images.

The project’s roots extend back to November 2018, when two giant wildfires—“Camp” and “Woosley”—broke out virtually simultaneously in Northern and Southern California. “The ‘Camp’ fire was the largest, fastest, and most deadly fire to date in California history,” says team member G. Andrew Fricker, a Cal Poly assistant professor. Tens of thousands of people from both fires had to evacuate quickly, leaving without any knowledge of the final fate of their homes and businesses—sometimes for weeks or even months. Ultimately, over 18,000 structures burned completely to the ground, yet approximately 30,000 structures were partially damaged by fire or heat. “It was clear there is a need to get reliable information out after a natural disaster, without slowing emergency efforts, both for personal and insurance purposes,” he notes.

Currently, wildfire damage assessment requires trained people going door-to-door to check on the status of every building in the affected area. While DamageMap isn’t intended to replace in-person damage classification, it can be used as a supplementary tool that offers rapid results while providing the exact locations of identified buildings.