Cover Crop Mapping
Description
The agency needs to independently check and track the use of cover crops on farms. Yearly maps are made using satellite images and models of plant growth to measure the use of cover crops on farms in the U.S. Midwest.
Detailed example
The output is a state-level map of detected cover crops by year, classified by planting date (fall, spring).
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
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Benefits by helping the agency independently check and track how many farmers are using cover crops, reducing the need for on-site visits to determine if cover crops are present on a field.
Controls / human review
ATO: Not reported; PIA: Not published