Landscape Change Monitoring System (LCMS)
Description
LCMS produces annual vegetation cover change, land cover, land use, and tree canopy cover data on National Forest System lands and more broadly across the conterminous United States, Alaska, Puerto Rico, U.S. Virgin Islands, and Hawaii from 1985 through present.
Detailed example
The model outputs predictions of tree canopy cover, vegetation gain, vegetation loss, land cover, and land uses.
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
Supporting agency priority initiatives such as quick and efficient monitoring of fire and fuels management across the landscape, documenting vegetation changes due to wildland and prescribed fire, tracking post-fire recovery and restoration work, maximizing the value of existing investments, reducing technical barriers, and improving mission outcomes.
Controls / human review
ATO: No; PIA: Not published
Data needed
Training and evaluation data used includes 15,000 sample plots spanning from 1985-2024. Features of the dataset are land cover, land use, and change process categories.