USGS Flow Photo Explorer [2024 INV#WO0000000109196]

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

2021-10-01 (day precision)Source: 10/1/2021

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

The Flow Photo Explorer (FPE) is an integrated database, machine learning, and data visualization platform for monitoring streamflow and other hydrologic conditions using timelapse images. The goal of this project is to develop new approaches for collecting hydrologic data in streams, lakes, and other waterbodies, especially in places where traditional monitoring methods and technologies are not feasible or cost-prohibitive. FPE uses an artificial intelligence/machine learning (AI/ML) deep learning model to estimate relative streamflow using timelapse imagery. The model is trained using pairs of images for which a person (a.k.a. an annotator) has selected which of the two images in each pair appears to have more flow. From this, the model learns how to sort the images from lowest to highest apparent flow. The rankings of the sorted images then serve as indicators of the relative amount of streamflow.

Expected benefits

cost savings, increased safety for employees and the public

System outputs

Predicted relative flow hydrograph.

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

www.usgs.gov ↗

Sourcing

How it was built

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

Vendor (as reported)

Walker Environmental Research LLC

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

k) None of the above

Training and evaluation data

The model is trained on human annotations of images captured by trail cameras. See the USGS Flow Photo Explorer to view training data and interface. Model performance is evaluated with timeseries streamflow data collected by collocated USGS streamgages. The streamflow data is made publicly available via the USGS National Water Information System (NWIS).

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