Cooperative Agreement for CESU-affiliated Partner with Piedmont-South Atlantic Coast Cooperative Ecosystem Studies Unit | G22AS00051

Opportunity Information: Apply for G22AS00051

This funding opportunity is a US Geological Survey (USGS) cooperative agreement aimed at a partner organization within the Piedmont-South Atlantic Coast Cooperative Ecosystem Studies Unit (CESU) network. The core purpose is to support research that improves how built structures and infrastructure in US coastal areas are mapped, described, and prepared for use in coastal hazard modeling, especially for storms that produce storm surge, waves, and damaging winds. The USGS is looking for work that helps create detailed, usable inventories of features like buildings, roads, bridges, railroads, and shoreline structures such as piers, seawalls, and jetties. These elements can significantly change how storm surge moves across the landscape, so having accurate representations of them is important for predicting flooding and other storm impacts.

A major theme of the opportunity is improving the speed and reliability of mapping these features across large coastal regions. The USGS notes that coastal hazard applications often require highly detailed information over broad geographic areas, which makes manual mapping too slow and inconsistent. As a result, the program emphasizes research into efficient and robust extraction methods that can pull relevant features from high-resolution remote sensing data (for example, aerial imagery, satellite imagery, or lidar-derived products) as well as from other geospatial mapping databases. The goal is not just to detect features, but to characterize them in ways that make them directly useful for hazard modeling and prediction workflows.

The opportunity places a strong emphasis on artificial intelligence and machine learning (AI/ML) approaches, with interest in collaborative research that can deliver efficient, accurate, and rapid mapping both before and after coastal storm events. Pre-storm mapping supports baseline inventories for modeling and preparedness, while post-storm mapping supports damage assessment and recovery decision-making. In practice, this means developing and testing AI/ML methods that can identify and delineate structures and infrastructure, distinguish between different feature types, and produce outputs that can be integrated into coastal storm hazard models. The work is expected to move beyond proof-of-concept and into methods that can be implemented and used reliably, especially under time pressure after an event.

The research objectives are organized into three connected areas. First, the award supports research on mapping, inventorying, and characterizing coastal built structures and infrastructure, along with preparing those extracted features so they can be used in hazard modeling and prediction (which typically requires consistent geometry, attribution, and formatting). Second, it supports the development, testing, and implementation of AI/ML techniques for extracting and characterizing these features from remote sensing and existing geospatial databases, reflecting the need for scalable methods that hold up across different coastal settings. Third, it calls for research and method development for identifying damaged structures and infrastructure and assessing susceptibility to damage, including enriching the mapped features with useful attributes such as structure type and primary construction material. That added attribution is important because damage patterns and vulnerability often vary substantially depending on what something is and what it is made of.

Administratively, this is a discretionary financial assistance opportunity issued under the CESU program, which is designed to facilitate partnerships that provide research, technical assistance, and education. Eligibility is limited to participating partners of the Piedmont-South Atlantic Coast CESU, meaning applicants must be affiliated with that CESU network to apply. The funding instrument is a cooperative agreement, which typically indicates substantial involvement or collaboration with the USGS during the project rather than a more hands-off grant structure.

Key opportunity details include the funding opportunity number G22AS00051, activity category in science and technology and other research and development, and CFDA number 15.808. The award ceiling is listed as $81,000. The opportunity was created on October 13, 2021, with an original closing date of November 13, 2021. Overall, the solicitation is focused on strengthening coastal storm hazard modeling and post-disaster assessment by advancing practical, scalable AI/ML-enabled workflows for mapping and characterizing the built environment in vulnerable coastal zones.

• The Geological Survey in the science and technology and other research and development sector is offering a public funding opportunity titled "Cooperative Agreement for CESU-affiliated Partner with Piedmont-South Atlantic Coast Cooperative Ecosystem Studies Unit" 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 2021-10-13.
• Applicants must submit their applications by 2021-11-13. (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 $81,000.00 in funding.
• Eligible applicants include: Others.

Apply for G22AS00051

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