HURRICANE RESPONSEDeep Learning Underlies Geographic Dataset Used in Hurricane Response
Extreme weather and natural disasters are happening with increasing frequency across the United States and its territories. Accurate and detailed maps are critical in emergency response and recovery. ORNL’s has mapped and characterized all structures within the United States and its territories to aid FEMA in its response to disasters.
As Hurricane Fiona made landfall as a Category 1 storm in Puerto Rico on Sept. 18, 2022, some areas of the island were inundated with nearly 30 inches of rain, and power to hundreds of thousands of homes was knocked out. Only 10 days later, Hurricane Ian, a Category 4 storm and one of the strongest and most damaging storms on record, landed in Lee County, Florida, leveling homes and flooding cities before moving up the coast and making landfall again as a Category 1 storm in South Carolina.
Extreme weather and natural disasters are happening with increasing frequency across the United States and its territories. Accurate and detailed maps are critical in emergency response and recovery.
Even before the hurricanes made landfall, the Federal Emergency Management Agency was working with researcher Lexie Yang and her team at the Department of Energy’s Oak Ridge National Laboratory to forecast potential damage and accelerate on-the-ground response using USA Structures, a massive dataset of building outlines and attributes covering more than 125 million structures.
Over the past seven years, researchers in ORNL’s Geospatial Science and Human Security Division have mapped and characterized all structures within the United States and its territories to aid FEMA in its response to disasters. This dataset provides a consistent, nationwide accounting of the buildings where people reside and work.
The agency requested two new attributes for the data the same day Fiona made landfall: occupancy types and addresses, critical information in speeding federal emergency funds to households and businesses.
“We encountered some language barriers when we were adding the new data. The limited information that was available to us was in Spanish. In addition, there are many different ways of documenting Puerto Rico’s addresses. Having to unify those data and validate the attribution information was a unique challenge for us,” Yang said.
Even with that challenge, Yang’s team was able to translate, validate and conflate the new attributes to the USA Structures data in about 50 hours. This is the result of having a scalable information pipeline and database in place built from years of effort. FEMA began planning for its response using the baseline USA Structures maps of areas likely to be impacted. FEMA staff added layers of data as the disasters unfolded, allowing the agency to prioritize response to the most heavily impacted areas.
