USDA · USDA-046 · record R1347

Rangeland Analysis Platform

Department of Agriculture · Research, Education and Economics; Farm Production and Conservation

Overview

Development stage: DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: 2017-01-01 (day precision)Source: 1/1/2017
Withheld from public reporting: Not reported

Mission

Topic area: Energy and the Environment
Operational functions: Image and video analysis Derived by keyword rules; see methodology

Problem the AI is intended to solve

Provides ranchers and land managers with information to detect and manage invasive species spread, wildfire risks, woody species encroachment, wildlife habitat condition, and wind erosion risks with high precision across the western U.S.

Expected benefits

The Rangeland Analysis Platform (RAP) allows users to track changes in plant growth and coverage over time. By monitoring the condition of agricultural ecosystems and the impact of conservation efforts, it can guide conservation practices, invasive species management, drought and wildfire responses, and wildlife habitats.

System outputs

Generates detailed maps showing rangeland vegetation cover and vegetation production across the U.S. Also provides imagery analysis and reporting to the end user

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): Rangeland Analysis Platform
Custom-developed code: Yes
Public source code: github.com ↗

Sourcing

How it was built: Contract and in-houseSource: c) Developed with both contracting and in-house resources
Vendor (as reported): Google Cloud, University of Montana, New Mexico State University
Vendors (standardized): Google

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

Data and privacy

Involves PII: No
Privacy Impact Assessment: Not reported
Authorization to Operate: Yes
Demographic features: k) None of the above
Training and evaluation data: The data is collected from over 75,000 monitoring locations collected by Natural Resources Conservation Service (NRCS), Bureau of Land Management, Sentinel-2 mission satellite imagery, Google Earth Engine, and other agencies.
Federal Data Catalog: rangeland.ntsg.umt.edu ↗

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