LANDFIRE
Description
Improve fire behavior prediction by mapping vegetation and detecting disturbances for the United States contributing to the downstream production of current fuel types and fuel metrics.
Detailed example
LANDFIRE produces a comprehensive, consistent, and scientifically credible collection of more than 25 geospatial layers focusing on disturbance, vegetation, and fuel metrics that are used by fire behavior modeling on active wildfires, as well as for prescribed fire planning and smoke management.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
Increasing accuracy in fire behavior prediction models and assessing, prioritizing, and reducing risk for firefighters and land managers.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
The Landscape Fire and Resource Management Planning Tools (LANDFIRE) reference database includes plot data from across the United States including Forest Inventory and Analysis plots, Bureau of Land Management Assessment Inventory and Monitoring plots, National Resources Conservation Service National Resource Inventory plots as well as other national and state inventories.