Challenge
Extreme drought conditions combined with a century of suppressing wildfires have created a dangerous accumulation of flammable vegetation on landscapes. This has resulted in a substantial increase in extreme wildfires that devastate ecosystems and risk human life and property. Prescribed fires are one of the most important tools available to mitigate the risk of wildfires, but scaling these vegetation treatments comes with many challenges.

Solution
3D fuel, fire and smoke models can enable next-generation tools for planning and implementing prescribed burns, helping fire managers reduce fuels to restore fire-dependent ecosystems and mitigate the risk of devastating wildfires.

Case Study Goal
This case study aims to understand the cyberinfrastructure and data discovery needs for the scientific and practitioner community working to build AI-ready datasets and immersive visualization of scientific data for new modes of training, decision making, and public communication related to prescribed fires. Collectively, we hope to develop prototype workflows that are integrated, repeatable, and reproducible - from multi-model data collection to fuel, fire, and smoke modeling to the generation of interpretable outputs tailored to specific real-world use cases.