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Snapshot · OMB 2025 inventory · processed Oct 11, 2026
DOI · DOI-0254 · record R2509

Development of a computer vision model to monitor for early detection of habitat loss across the landscape. [2024 INV#DOI-65]

Department of the Interior · FWS

Overview

Development stage
In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation
Not high-impactSource: c) Not high-impact
Impact justification
Not reported
Start date
Not reported
Withheld from public reporting
NoSource: a) No

Mission

Topic area
Science
Operational functions
No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

The U.S. Fish and Wildlife Service is planning to partner with the Chesapeake Conservancy, an NGO, to develop a computer vision model to monitor for early detection of habitat loss across the landscape, a significant threat to biodiversity, including threatened and endangered species. By using a computer vision model one can rapidly identify and flag areas where habitat loss may be occurring due to natural or human-caused disturbances. Early detection can facilitate rapid responses, when appropriate, or allow practitioners to accurately calculate habitat loss over time. More accurate estimates of habitat loss allow for better management decisions and potentially shorter recovery times for threatened and endangered species.

Expected benefits

AI-powered computer vision enables early detection of habitat loss, allowing faster, more accurate responses to threats. This supports better conservation decisions and helps protect and recover threatened and endangered species.

System outputs

AI-powered computer vision enables early detection of habitat loss, allowing faster, more accurate responses to threats. This supports better conservation decisions and helps protect and recover threatened and endangered species.

Technology

AI classification
Other
System name(s)
Not reported
Custom-developed code
No
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
No
Privacy Impact Assessment
Not reported
Authorization to Operate
No
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