Opportunity
Simpler Grants.gov #G26AS00122
USGS Cooperative Agreement for Plant Species Habitat Detection Research with Rocky Mountain CESU Partner
Buyer
U.S. Geological Survey
Posted
May 29, 2026
Respond By
June 30, 2026
Identifier
G26AS00122
NAICS
541715, 541360
The U.S. Geological Survey (USGS) Fort Collins Science Center is seeking a university partner from the Rocky Mountain Cooperative Ecosystem Studies Unit (CESU) for a three-year cooperative research agreement focused on plant species habitat detection using satellite data. - Government Buyer: - U.S. Geological Survey (USGS), Fort Collins Science Center - Eligible Applicants: - Only university partners affiliated with the Rocky Mountain CESU - Project Focus: - Research to improve detection of plant species habitats, especially invasive species, using satellite information - Development of phenology-informed detection models - Assessment of model transferability across broad geographic regions - Analysis of spatial patterns of model uncertainty - Optimization of model result delivery to land management practitioners - Research Deliverables: - Production of research products (data and code) to support management decisions for the Department of the Interior and other land-management partners - Compliance with federal geospatial data standards and open data formats - Robust data management plan required - Funding and Period of Performance: - Total funding available: $49,250 - Three-year project period with full funding obligated at award - Notable Requirements: - Annual progress reports and a final technical report - Research must support federal science quality and wildfire prevention policies - No specific OEMs or commercial vendors are named, as this is a research and development opportunity rather than a product procurement.
Description
The USGS is offering a funding opportunity to a CESU partner for research focused on detecting plant species habitat to inform management. The research aims to investigate phenology informed detection models, model transferability across broad regions, analyze spatial patterns of model uncertainty, and optimize the delivery of model results to land management practitioners. The project will improve methodologies and analytic approaches for plant species habitat detection using satellite information, with a focus on invasive species detection to aid in prevention and control. The outcome will be research products that support plant species management decisions and enhance land management efficiency.