Opportunity Information: Apply for USGS 19 FA 0203
The grant opportunity titled "Deep Learning for Automated Detection and Classification of Waterfowl, Seabirds, and other Wildlife from Digital Aerial Imagery" is a Department of the Interior, U.S. Geological Survey (USGS) cooperative agreement focused on modernizing how marine and coastal wildlife are surveyed using aerial photos. The core idea is to develop and improve deep learning and computer vision methods that can automatically find and identify animals such as waterfowl, seabirds, and other marine wildlife in digital aerial imagery, reducing the heavy manual effort typically required to review and annotate large image collections.
This effort is being jointly supported and coordinated by multiple federal partners with overlapping missions in wildlife monitoring and offshore environmental stewardship. The Bureau of Ocean Energy Management (BOEM) is a primary funder and has prioritized the use of Outer Continental Shelf Program funds through USGS across fiscal years 2019, 2020, and 2021 to push forward two key building blocks: (1) expanding and refining an imagery and annotation database, and (2) advancing deep learning algorithms (DLA) that can use those labeled images to automate detection and classification. The U.S. Fish and Wildlife Service (USFWS), specifically the Division of Migratory Bird Management (DMBM) and its Branch of Migratory Bird Surveys, is also collaborating, reflecting the practical need for accurate bird survey tools that can support population assessments, migration monitoring, and conservation decision-making. The partnership framing signals that the project is not just a research exercise, but intended to produce methods and resources that can be applied in real survey programs and environmental assessments.
The technical scope centers on applying deep learning to the challenging conditions found in aerial wildlife imagery, where animals can appear small, partially obscured, clustered, or visually similar across species, and where lighting, sea state, glare, altitude, and sensor differences can all affect image quality. By investing in improved training data (imagery plus high-quality annotations) and algorithm development, the project aims to strengthen automated workflows that can scale to large geographic areas and long time series of flights. In practical terms, success would mean survey teams can process imagery faster, more consistently, and potentially with measurable accuracy metrics, enabling broader monitoring coverage and quicker turnaround for management needs.
From an administrative standpoint, this is a discretionary funding opportunity offered as a cooperative agreement, meaning the federal partners expect to have substantial involvement during the project rather than simply issuing a hands-off grant. The opportunity number is USGS 19 FA 0203, and it falls under the Natural Resources funding activity category with CFDA number 15.808. Eligibility is limited to public and state-controlled institutions of higher education, positioning the work for universities that can combine ecological expertise with machine learning, remote sensing, and data management capabilities. The maximum award amount listed is $85,000, with one expected award, indicating a targeted, single-recipient project rather than a broad multi-award competition. The posting lists a creation date of June 7, 2019, and an original closing date of June 17, 2019, which implies a short application window typical of some specialized cooperative research calls.
Overall, the opportunity is aimed at building practical deep learning tools and supporting datasets that help federal agencies detect and classify birds and other wildlife from aerial imagery more efficiently. The broader value is tied to improving environmental monitoring and decision support, particularly in offshore and coastal contexts where BOEM, USFWS, and USGS rely on accurate wildlife distribution and abundance information for stewardship, planning, and impact assessment.Apply for USGS 19 FA 0203
- The Department of the Interior, U. S. Geological Survey in the natural resources sector is offering a public funding opportunity titled "Deep Learning for Automated Detection and Classification of Waterfowl, Seabirds, and other Wildlife from Digital Aerial Imagery" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 15.808.
- This funding opportunity was created on Jun 07, 2019.
- Applicants must submit their applications by Jun 17, 2019. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- Each selected applicant is eligible to receive up to $85,000.00 in funding.
- The number of recipients for this funding is limited to 1 candidate(s).
- Eligible applicants include: Public and State controlled institutions of higher education.
[Watch] Creating a grant proposal using the step-by-step wizard inside the applicant portal:
Frequently Asked Questions (FAQs)
What is the title of this grant opportunity?
The opportunity is titled "Deep Learning for Automated Detection and Classification of Waterfowl, Seabirds, and other Wildlife from Digital Aerial Imagery."
Which federal agency is offering this opportunity?
This is a Department of the Interior, U.S. Geological Survey (USGS) funding opportunity issued as a cooperative agreement.
What type of funding mechanism is it?
It is a discretionary funding opportunity offered as a cooperative agreement. This indicates the federal partners expect substantial involvement during the project rather than providing a hands-off grant.
What is the opportunity number?
The opportunity number is USGS 19 FA 0203.
What is the CFDA number and funding activity category?
The CFDA number is 15.808, and the funding activity category is Natural Resources.
What is the main purpose of the project?
The main purpose is to modernize marine and coastal wildlife survey workflows by developing and improving deep learning and computer vision methods that can automatically detect and classify animals (including waterfowl, seabirds, and other marine wildlife) in digital aerial imagery.
What problem is this project trying to solve?
The project aims to reduce the heavy manual effort typically required to review and annotate large collections of aerial photos used in wildlife surveys, while improving the speed and consistency of processing imagery at scale.
What types of wildlife are in scope?
The scope includes waterfowl, seabirds, and other wildlife observable in digital aerial imagery, particularly in marine and coastal survey contexts.
What kinds of imagery are referenced in this opportunity?
The opportunity focuses on digital aerial imagery used for marine and coastal wildlife surveys.
What are the two key technical building blocks emphasized by the funder?
Two building blocks are prioritized: (1) expanding and refining an imagery and annotation database, and (2) advancing deep learning algorithms that use labeled images to automate detection and classification.
Why is training data (imagery plus annotations) emphasized?
Because improved, high-quality labeled data strengthens the ability of deep learning algorithms to learn reliable patterns for detecting and classifying wildlife under challenging real-world image conditions.
What makes aerial wildlife imagery challenging for automated detection and classification?
The opportunity notes several challenges: animals can be small, partially obscured, clustered, or visually similar across species. Image conditions can vary due to lighting, sea state, glare, altitude, and sensor differences, all of which can affect image quality and model performance.
What outcomes would indicate success for this project?
Success would mean survey teams can process aerial imagery faster and more consistently, potentially with measurable accuracy metrics, enabling broader monitoring coverage and quicker turnaround to support management needs.
Who are the federal partners supporting and coordinating this work?
The effort is supported and coordinated by multiple federal partners, including USGS, the Bureau of Ocean Energy Management (BOEM), and the U.S. Fish and Wildlife Service (USFWS).
What role does BOEM play in the opportunity?
BOEM is identified as a primary funder and has prioritized the use of Outer Continental Shelf Program funds through USGS across fiscal years 2019, 2020, and 2021 to advance the imagery/annotation database and deep learning algorithm development.
What role does USFWS play in the opportunity?
USFWS is collaborating through the Division of Migratory Bird Management (DMBM) and its Branch of Migratory Bird Surveys, reflecting the practical need for accurate bird survey tools to support population assessments, migration monitoring, and conservation decision-making.
Is this opportunity intended to be purely academic research?
The partnership framing suggests it is not just a research exercise. The project is intended to produce methods and resources that can be applied in real survey programs and environmental assessments.
What kinds of applications are expected for the results?
The intended applications include wildlife monitoring and decision support in offshore and coastal contexts, including survey programs and environmental assessments that rely on accurate distribution and abundance information.
What is the maximum award amount?
The maximum award amount listed is $85,000.
How many awards are expected?
One award is expected, indicating a targeted single-recipient project rather than a multi-award competition.
Who is eligible to apply?
Eligibility is limited to public and state-controlled institutions of higher education.
What types of institutional capabilities are implied as useful for this work?
The description positions the work for universities that can combine ecological expertise with machine learning, remote sensing, and data management capabilities.
When was the opportunity posted and when did it close?
The posting lists a creation date of June 7, 2019, and an original closing date of June 17, 2019.
What does the short time between the creation date and closing date imply?
It implies a short application window, which is typical of some specialized cooperative research calls.
How does this project support environmental stewardship?
By improving automated detection and classification of wildlife in aerial imagery, the project supports more efficient and scalable monitoring. This strengthens the information base used by federal agencies for stewardship, planning, and impact assessment in offshore and coastal environments.
What kinds of improvements to survey workflows are envisioned?
The opportunity envisions automated workflows that reduce manual image review and annotation burdens, scale to large geographic areas and long time series of flights, and deliver faster and more consistent results for management and monitoring needs.
Browse more opportunities from the same category: Natural Resources
Next opportunity: Working Together to Combat the Dark Web of Human Trafficking
Previous opportunity: BJA FY 19 Comprehensive Corrections Training and Technical Assistance
Applicant Portal:
Are you interested in learning about about how to apply for this government funding opportunity? You can create a free applicant account and receive instant access to our applicant portal that many business owners like you have benefited from.
Apply for USGS 19 FA 0203
Applicants also applied for:
Applicants who have applied for this opportunity (USGS 19 FA 0203) also looked into and applied for these:
| Funding Opportunity |
|---|
| Hydrologic Monitoring, Analysis, and Protocol Documentation in California and Nevada Apply for F19AS00238 Funding Number: F19AS00238 Agency: Department of the Interior, Fish and Wildlife Service Category: Natural Resources Funding Amount: $561,000 |
| Cooperative GIS Research and Support for Cultural Resource Condition Apply for P19AS00243 Funding Number: P19AS00243 Agency: Department of the Interior, National Park Service Category: Natural Resources Funding Amount: $104,711 |
| Cooperative Research and GIS support for Visitor and Land Use Apply for P19AS00244 Funding Number: P19AS00244 Agency: Department of the Interior, National Park Service Category: Natural Resources Funding Amount: $77,256 |
| Vegetation Mapping Project for the Seboeis Unit of Katahdin Woods and Waters National Monument. Apply for USGS 19 FA 0204 Funding Number: USGS 19 FA 0204 Agency: Department of the Interior, U. S. Geological Survey Category: Natural Resources Funding Amount: $29,428 |
| Soundscapes and Auditory Evoked Potentials to Inform Acoustic Deterrents for Bigheaded Carp Apply for USGS 19 FA 0206 Funding Number: USGS 19 FA 0206 Agency: Department of the Interior, U. S. Geological Survey Category: Natural Resources Funding Amount: $99,298 |
| Monitoring of the Flat-Tailed Horned Lizard and the Sonoran Pronghorn Captive Breeding Pen Apply for N624731920010 Funding Number: N624731920010 Agency: Department of Defense, NAVAL FACILITIES ENGINEERING COMMAND Category: Natural Resources Funding Amount: $162,620 |
| Notice of Intent: Earth Science Week 2019 Apply for USGS FA 19 0088 Funding Number: USGS FA 19 0088 Agency: Department of the Interior, U. S. Geological Survey Category: Natural Resources Funding Amount: $49,000 |
| NOTICE OF INTENT: Maintaining Access to Recreation Opportunities by Controlling Invasive Plants Apply for P19AS00249 Funding Number: P19AS00249 Agency: Department of the Interior, National Park Service Category: Natural Resources Funding Amount: $54,000 |
| Soils mapping on Valles Caldera in support of forest restoration Apply for P19AS00252 Funding Number: P19AS00252 Agency: Department of the Interior, National Park Service Category: Natural Resources Funding Amount: $36,469 |
| Eightmile Wild and Scenic River Assistance Apply for NPS 19 NERO 0041 Funding Number: NPS 19 NERO 0041 Agency: Department of the Interior, National Park Service Category: Natural Resources Funding Amount: $120,000 |
| Post-treatment Assessment of Floodplain plant communities and Channel form Apply for P19AS00253 Funding Number: P19AS00253 Agency: Department of the Interior, National Park Service Category: Natural Resources Funding Amount: $29,760 |
| 3DEP for the Nation Apply for USGS 19 FA0202 Funding Number: USGS 19 FA0202 Agency: Department of the Interior, U. S. Geological Survey Category: Natural Resources Funding Amount: $395,000 |
| Geoscientists-in-the-Parks Internships Apply for P19AS00251 Funding Number: P19AS00251 Agency: Department of the Interior, National Park Service Category: Natural Resources Funding Amount: $1,096,167 |
| Bridge rehabilitation; 3 bridges with safety issues require serious repair Apply for P19AS00257 Funding Number: P19AS00257 Agency: Department of the Interior, National Park Service Category: Natural Resources Funding Amount: $30,600 |
| BLM NM Aquatic Habitat Management Apply for L19AS00083 Funding Number: L19AS00083 Agency: Department of the Interior, Bureau of Land Management Category: Natural Resources Funding Amount: $25,000 |
| Improve Trail Signage and Remove Graffiti at Joshua Tree National Park Apply for P19AS00194 Funding Number: P19AS00194 Agency: Department of the Interior, National Park Service Category: Natural Resources Funding Amount: $49,975 |
| Watershed Education for Teachers (WET); Lake Mead National Recreatio Area Apply for P19AS00177 Funding Number: P19AS00177 Agency: Department of the Interior, National Park Service Category: Natural Resources Funding Amount: $40,000 |
| SCA Archaeology Technician Intern Apply for NPSNOITONT1900543 Funding Number: NPSNOITONT1900543 Agency: Department of the Interior, National Park Service Category: Natural Resources Funding Amount: $28,537 |
| SCA Biological Technician Intern Apply for NPSNOITONT1900542 Funding Number: NPSNOITONT1900542 Agency: Department of the Interior, National Park Service Category: Natural Resources Funding Amount: $25,667 |
| NOTICE OF INTENT: Youth Experience in Management of Invasive Species and Hazardous Fuels Apply for P19AS00264 Funding Number: P19AS00264 Agency: Department of the Interior, National Park Service Category: Natural Resources Funding Amount: $91,056 |
Grant application guides and resources
It is always free to apply for government grants. However the process may be very complex depending on the funding opportunity you are applying for. Let us help you!
Apply for Grants
Inside Our Applicants Portal
Access Applicants Portal
- Grants Repository - Access current and historic funding opportunities with ease. Thousands of funding opportunities are published every week. We can help you sort through the database and find the eligible ones to apply for.
- Applicant Video Guides - The grant application process can be challenging to follow. We can help you with intuitive video guides to speed up the process and eliminate errors in submissions.
- Grant Proposal Wizard - We have developed a network of private funding organizations and investors across the United States. We can reach out and submit your proposal to these contacts to maximize your chances of getting the funding you need.
Premium leads for funding administrators, grant writers, and loan issuers
Thousands of people visit our website for their funding needs every day. When a user creates a grant proposal and files for submission, we pass the information on to funding administrators, grant writers, and government loan issuers.
If you manage government grant programs, provide grant writing services, or issue personal or government loans, we can help you reach your audience.
Learn More
Request more information:
Would you like to learn more about this funding opportunity, similar opportunities to "USGS 19 FA 0203", eligibility, application service, and/or application tips? Submit an inquiry below:
Don't forget to subscribe to our grant alerts mailing list to receive weekly alerts on new and updated grant funding opportunities like this one in your email.