Closed · W81EWF-23-SOI-0014 · CFDA 12.630 · Discretionary
LandCart Expansion for Global Range Attributes
Federal grant opportunity posted by Engineer Research and Development Center, cataloged on Grants.gov.
- up to $60K
- Award range
- Closed
- Status
- August 14, 2023
- Close date
- 1
- Expected awards
The verdict
LandCart Expansion for Global Range Attributes is a closed discretionary listing from Engineer Research and Development Center that offered Up to $60,000 across 1 expected award. Future funding cycles may be published under the same CFDA number.
- up to $60K
- award range
- Closed
- application status
- 1
- expected award
- 12.630
- CFDA program
Opportunity snapshot. This Grants.gov announcement - LandCart Expansion for Global Range Attributes - is cataloged under number W81EWF-23-SOI-0014 and tied to CFDA assistance listing 12.630, posted by Engineer Research and Development Center. Grants.gov currently shows the opportunity as closed, first posted on May 24, 2023 and last updated on June 28, 2023. The funding category is Discretionary, delivered as a cooperative agreement.
Award economics. The award range on file is Up to $60,000. The agency has projected $360,000 in total estimated funding for this announcement. It expects to issue 1 award. If the agency funds the expected 1 award from the $360,000 estimated pool, the average award works out to roughly $360,000. Cost sharing is not required, so applicants do not need to commit matching funds to be competitive on this opportunity. Federal award ranges are often upper bounds; actual allocations reflect program appropriations, the strength of the applicant pool, and the evaluation committee's scoring.
Deadline and action path. This opportunity closed on August 14, 2023. Future funding cycles may be published under the same CFDA number, so monitoring the parent program page is the most reliable way to catch re-announcements. Every Grants.gov submission requires an active SAM.gov registration and a Unique Entity ID. Review the Eligibility section below carefully, federal eligibility categories (nonprofit, state or local government, tribal, individual, educational institution, small business) have distinct registration and reporting requirements. Pre-application outreach to the listed agency contact is permitted and often welcomed, it helps clarify scope and scoring priorities. Before acting on the deadline or award figures above, verify them directly on the official Grants.gov listing, amendments can change dates and amounts after this page was last refreshed.
Award Range
Up to $60,000
Close Date
August 14, 2023
Posted
May 24, 2023
Est. Total Funding
$360,000
Expected Awards
1
Instrument
Cooperative Agreement
Description
ERDC seeks applications for an opportunity to enter into a cooperative agreement for: Global Rangeland Attribute Model. A highly functional, highly accurate rangeland attribute model, LandCart, has been developed for the western United States using a significant and standardized rangeland data set. The overall goal of this agreement is to expand a LandCart type of predictive algorithm to global rangelands. As global rangelands lack the level and quality of data that were available for LandCart development, the first step is determining if the data that exists can be utilized in a manner that is conducive to development of rangeland attribute algorithms. If it is, the next step is utilizing this and supplemental data to develop a global rangeland attribute model. Once a model is completed, validation and model improvements will be required. Finally, model delivery and reporting will ensure technology transfer. Rangeland landscapes cover approximately 50% of Earth’s land surface. Knowledge of rangeland attributes at a global scale is important for ecosystem sustainment and sustainable use. The ability to remotely predict these attributes is paramount to planning and management of these critical environments. Spatial and temporal patterns of biomass and cover have been estimated for decades using satellite imagery, which allows for the examination of larger areas with limited field work and the ability to reproduce outputs. Biomass, cover, and height can be estimated or directly measured in the field, but it is impractical for managers to carry out field sampling across extensive rangeland systems, often covering tens of thousands of hectares or more, with adequate temporal frequency and spatial resolution to capture the spatiotemporal heterogeneity that commonly exists across rangeland landscapes. Remote sensing-based methods to produce estimates of rangeland properties at varying scales would be highly desirable to facilitate a more comprehensive understanding of the spatial and temporal trends in rangeland condition. However, global satellite-based predictions applicable to rangeland vegetation properties remain sparse. This new project seeks to expand existing capabilities in the western United States to predict rangeland attributes at a global scale. A highly functional, highly accurate rangeland attribute model, LandCart, has been developed for the western United States using a significant and standardized rangeland data set. The overall goal of this agreement is to expand a LandCart type of predictive algorithm to global rangelands. As global rangelands lack the level and quality of data that were available for LandCart development, the first step is determining if the data that exists can be utilized in a manner that is conducive to development of rangeland attribute algorithms. Funding agency has created a global database of field-based rangeland vegetation measurements. However, it is unknown if this database still possesses the breadth and depth of information required to develop a functional predictive algorithm. Expertise is sought to review the data in the database and make a determination of whether it is adequate, what is required to make it adequate if it is not, or if it cannot be utilized in this capacity in the first year. If it is, the next step is utilizing this and other potential data sources to develop a predictive global rangeland attribute model, with a primary focus on vegetative cover and height prediction in year 2. Once a model is completed, validation and model improvements will be required through a collaborative effort to acquire, analyze, and incorporate field data during the third and fourth years. Finally, model delivery and reporting will ensure technology transfer.
Eligibility
Grants.gov lists this opportunity under eligibility category code 25. These codes correspond to applicant types (state/local government, tribal organization, nonprofit, educational institution, individual, small business, etc.) defined in Grants.gov's own eligibility reference. See the current Grants.gov eligibility categories or check the official listing below for this opportunity's exact eligibility statement.
Official Listing on Grants.gov
View full details, application forms, and submission instructions.
Agency Contact
Phoebe V Fuller Grantor Phone 6016343793
Key Dates
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