Description

Wildfire behavior models rely on accurate representation of surface fuels such as grasses, litter, shrubs, and downed woody material, yet this remains one of the least resolved technical gaps, particularly in non forested ecosystems. Improving how these fuels are measured, classified, and modeled is critical to advancing fire prediction, prescribed burn planning, and operational safety. This exchange brings together federal program managers, operational leaders, fire behavior modelers, and cross sector innovators to refine the scope of an upcoming prize challenge focused on scalable, realistic solutions to this national level problem. This event is ideal for organizations working in AI and machine learning, remote sensing, geospatial analytics, environmental modeling, vegetation science, data fusion, and uncertainty quantification. Attendees will gain direct insight into operational modeling needs, help shape the evaluation criteria for the upcoming prize challenge, and engage with decision makers and potential collaborators. Participants can expect expert briefings, structured discussions, and opportunities to influence the technical direction of future funding efforts. Register today to contribute your expertise and help define the next generation of surface fuels modeling solutions.

Classification

Place of Performance