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Wednesday, December 15, 2021

Advanced Wildfire AI and Global Data

As the power of drones increase the data and pattern recognitions to support their use is also advancing to support wildfire fighting.   Will also address other disaster relief scenarios. 

Quenching the Flames: AI, Data Help Fight Global Wildfires

By Karen Emslie, Commissioned by CACM Staff, December 14, 2021   in CACM

Disturbing images of communities and forests burning increasingly fill our newsfeeds and TV screens. According to analysis by the World Health Organization (WHO), wildfires have impacted millions of people globally. Countless insects, birds, and animals have also been displaced or perished. Wildfires are hitting record levels of size and severity around the world.

The Congressional Research Service (CRS) reports that in 2020, in the U.S. alone, 58,950 wildfires burned over 10 million acres (about 4 million hectares) of land. In Russia, fires devastated more than 18.16 million hectares (nearly 45 million acres) of forest in 2021, predominantly in Siberia. The Washington Post reported these fires were larger than the rest of the world's blazes combined. Similar record-breaking reports come from countries such as Italy, Turkey, and Australia.

Factors like extreme heat, drought, and climate change are fueling the flames. According to a review of 57 scientific articles carried out by ScienceBrief, an online platform that hosts expert-led analyses of consensus and controversies using peer-reviewed publications, "Human-induced climate change promotes the conditions on which wildfires depend, enhancing their likelihood and challenging suppression efforts."

In the face of this, global technologists are collaborating with fire professionals to build artificial intelligence (AI) and data-based solutions for fire detection, response, and recovery.

Fire data for knowledge and modelling

It is perhaps not surprising that wildfire-impacted California is ahead of the curve. The University of California San Diego-based WIFIRE Lab is a collaboration between data and AI researchers, private companies, and public agencies such as fire departments.

"Our mission is to turn data, artificial intelligence, and computing, these three things, into a utility for anyone in this domain," said Ilkay Altintas, chief data science officer at the San Diego Supercomputer Center (SDSC) and founder of the WIFIRE Lab.

The WIFIRE Lab builds AI and data-based platforms and products that have practical applications in fire science. Projects include WIFIRE Commons, a data and modelling environment; FireMap, a tool that creates predictive maps to show wildfires' expected trajectories, and BURNPRO 3D, an in-development prescribed—or controlled— burn simulation tool.

Thanks to its existing monitoring networks, San Diego is rich in fire data. WIFIRE Common's aim is to store and federate that data, which comes from multiple sources: cameras, satellites, Light Detection and Ranging (LiDAR) sensors, drones, and aircraft, and via multiple organizations, including national agencies, fire departments, aviation companies, and utilities.

Once the data has been collected, it must be made useful to researchers and fire professionals via modelling and visualization interfaces. AI is initially deployed "to fuse the data that we receive from different sources and bring it to a form the downstream fire models can accept," said Altintas, for example, through extrapolation or by making it higher or lower resolution.

There is also a semantic component to the work. The WIFIRE team built a fire science ontology on top of the existing environmental ontology. Said Altintas, "We specialize that to our domain so that data sets that we federate or store are tagged with those terms as well as the models."

WIFIRE Commons' modelling tools exploit the SDSC's supercomputing capabilities. Data is integrated with physics-based machine learning within the platform's models to predict, map, and visualize fire behavior. The QUIC-Fire model, for example, is a fast-running simulation tool that captures the interactions between fire, dynamic atmosphere, vegetation structure, and topography.

Like QUIC-Fire, FireMap is deployed in real-life scenarios by fire fighters and first responders, such as the Los Angeles Fire Department. The operational AI-based tool uses visualization techniques for prediction. "In a matter of minutes, someone with the knowledge can create a fire model about where the fire will go over the next couple of hours, so it gets used in initial attack," said Altintas.

While FireMap is responsive, the lab's latest product, BURNPRO 3D — an in-development AI tool funded by the National Science Foundation (NSF)— is proactive. It is designed to support land managers in planning and running prescribed burns— initiated to reduce an area's flammable material as part of the effort to combat megafires..... ' 

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