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Snapshot · OMB 2025 inventory · processed Oct 11, 2026
USDA · USDA-061 · record R1362

Cover Crop Mapping

Department of Agriculture · Farm Production and Conservation

Overview

Development stage
In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation
High-impactSource: a) High-impact
Impact justification
Not reported
Start date
Not reported
Withheld from public reporting
Not reported

Mission

Topic area
Service Delivery
Operational functions
Image and video analysis Derived by keyword rules; see methodology

Problem the AI is intended to solve

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.

Expected benefits

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.

System outputs

The output is a state-level map of detected cover crops by year, classified by planting date (fall, spring).

Technology

AI classification
Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
System name(s)
Not reported
Custom-developed code
Not reported
Public source code
Not reported

Sourcing

How it was built
Not reported
Vendor (as reported)
Not reported
Vendors (standardized)
None on the standard list

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII
Not reported
Privacy Impact Assessment
Not reported
Authorization to Operate
Not reported
Demographic features
Not reported
Training and evaluation data
Not reported
Federal Data Catalog
Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Pre-deployment testingNo answer reported
AI impact assessmentNo answer reported
Independent reviewNo answer reported
Ongoing monitoringNo answer reported
Operator trainingNo answer reported
Fail-safeNo answer reported
Appeal processNo answer reported
User and public consultationNo answer reported

Potential impacts and how they were identified

Not reported