Machine Learning Image Classification of Wetlands and Soil moisture [2024 INV#WO0000000108779]

Overview

Development stage

PilotSource: b) Pilot – The use case has been deployed in a limited test or pilot capacity.

High-impact designation

Not high-impactSource: c) Not high-impact

Impact justification

Not reported

Start date

2023-10-01 (day precision)Source: 10/1/2023

Withheld from public reporting

NoSource: a) No

Mission

Topic area

Science

Operational functions

Image and video analysis Derived by keyword rules; see methodology

Problem the AI is intended to solve

inform land managers, planners, and researchers about historical and current changes to human and natural environments, focused on floods, droughts, and fires

Expected benefits

ability to classify wetlands and soil moisture at large scales

System outputs

quantification of causal processes behind wildfire

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

No

Public source code

Not reported

Sourcing

How it was built

Contract and in-houseSource: c) Developed with both contracting and in-house resources

Vendor (as reported)

Google

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

No

Demographic features

k) None of the above

Training and evaluation data

Training Samples, Raster Images

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.

Potential impacts and how they were identified

Not reported