Opportunity Information: Apply for USGS 19 FA 0048
The grant opportunity titled "Value of Information (VOI): Forest Risk Analysis with LANDFIRE" (Funding Opportunity Number USGS 19 FA 0048) is a discretionary U.S. Geological Survey (USGS) funding call under the Department of the Interior. It is offered as a cooperative agreement, meaning the project is expected to involve active collaboration with the agency rather than functioning purely as an independent research grant. The program sits in the Environment funding activity category and is listed under CFDA number 15.808, which is associated with USGS research and related scientific support activities.
The core purpose of the project is to run a Value of Information (VOI) impact assessment focused on how satellite remote sensing and other Earth science datasets improve forest risk management decisions. In practical terms, the work is meant to quantify the decision-making value of information products derived from Landsat (and related contemporary Earth science data such as geologic maps) when those products are used in risk frameworks relevant to forests. The opportunity specifically highlights the use of Landsat-derived information within LANDFIRE, which is a widely used set of vegetation, fuels, and disturbance layers that support wildfire and land management planning. The project also explicitly calls for incorporating geologic attributes in the subsurface, suggesting that the analysis should not treat forest risk as solely a surface vegetation issue, but should also consider how underlying geologic factors may influence hazards, vulnerability, or management outcomes (for example, through effects on soils, slope stability, hydrology, or fuel and vegetation patterns).
A key feature of the requested work is the coupling of these geospatial and Earth science inputs with an economics framework. That is, the project is not only about producing better maps or better models, but about translating improvements in information into measurable value for risk management. A VOI assessment typically asks questions like: How much does better information change decisions? How much does it improve outcomes (such as avoided losses, reduced suppression costs, improved safety, or better allocation of treatments)? What is the economic benefit of those outcome improvements compared to the costs of producing and maintaining the data products? By structuring the analysis this way, the project aims to produce evidence of the practical and monetary importance of Landsat and related datasets as decision-support assets in forest risk management.
The funding details indicate a small, targeted award: an award ceiling of $84,999, with one expected award. The opportunity was created on February 5, 2019, and had an original closing date of February 12, 2019, implying a short application window consistent with a focused or pre-identified collaboration. Eligibility is listed broadly as "Others," but the description clarifies that the eligible applicant for this particular opportunity is the University of New Mexico, indicating it is effectively a single-organization competition or a directed award intended for that institution.
Overall, this opportunity is best understood as a narrowly scoped, collaborative USGS-supported study designed to quantify the decision and economic value of Landsat-enabled LANDFIRE information, augmented by subsurface geologic attributes, for managing forest risks. The expected deliverable is not just scientific analysis, but an applied VOI impact assessment that helps demonstrate where and how these federal Earth observation and mapping investments pay off in real forest management decisions.Apply for USGS 19 FA 0048
- The Department of the Interior, U. S. Geological Survey in the environment sector is offering a public funding opportunity titled "Value of Information (VOI): Forest Risk Analysis with LANDFIRE" 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 Feb 05, 2019.
- Applicants must submit their applications by Feb 12, 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 $84,999.00 in funding.
- The number of recipients for this funding is limited to 1 candidate(s).
- Eligible applicants include: Others (see text field entitled Additional Information on Eligibility for clarification).
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Frequently Asked Questions (FAQs)
What is the official title of this grant opportunity?
The opportunity is titled "Value of Information (VOI): Forest Risk Analysis with LANDFIRE."
What is the Funding Opportunity Number?
The Funding Opportunity Number (FON) is USGS 19 FA 0048.
Which federal agency is offering this funding?
The funding is offered by the U.S. Geological Survey (USGS), which is part of the Department of the Interior.
What type of award is this (grant vs. cooperative agreement)?
This opportunity is offered as a cooperative agreement. That means the project is expected to involve active collaboration with USGS, rather than operating purely as an independent research effort.
Is this a discretionary funding opportunity?
Yes. The opportunity is described as a discretionary USGS funding call.
What is the funding activity category for this opportunity?
The funding activity category is Environment.
What is the CFDA number associated with this program?
The CFDA number listed is 15.808, associated with USGS research and related scientific support activities.
What is the overall purpose of the project?
The purpose is to run a Value of Information (VOI) impact assessment focused on how satellite remote sensing and other Earth science datasets improve forest risk management decisions.
What does "Value of Information (VOI)" mean in the context of this project?
In this context, a VOI assessment is meant to quantify how improved information changes decisions and outcomes in forest risk management, and to translate those improvements into measurable value (including economic value) relative to the costs of producing and maintaining the underlying data products.
What kinds of data products are emphasized in the VOI assessment?
The opportunity emphasizes information products derived from Landsat and related contemporary Earth science datasets, including examples such as geologic maps.
How does LANDFIRE fit into the project?
The opportunity specifically highlights using Landsat-derived information within LANDFIRE, which provides vegetation, fuels, and disturbance layers used to support wildfire and land management planning.
Is the project only about creating better maps or models?
No. The project is framed as more than map or model improvement. It is intended to link improved geospatial information to decision-making impacts and measurable value for forest risk management.
What does the opportunity mean by "forest risk management decisions"?
Based on the description, the project focuses on decisions made within risk frameworks relevant to forests, especially those that can use LANDFIRE-type information for wildfire and land management planning.
Why does the opportunity mention subsurface geologic attributes?
The project explicitly calls for incorporating geologic attributes in the subsurface, indicating the analysis should consider forest risk as influenced by more than surface vegetation alone. The description suggests underlying geologic factors may influence hazards, vulnerability, or management outcomes (for example through effects on soils, slope stability, hydrology, or fuel and vegetation patterns).
What kinds of benefits or outcomes could the VOI assessment consider?
The description gives examples of outcomes such as avoided losses, reduced suppression costs, improved safety, and better allocation of treatments, and it emphasizes comparing these benefits to the costs of producing and maintaining the data products.
Does the project require an economics component?
Yes. A key feature is coupling geospatial and Earth science inputs with an economics framework so improvements in information can be translated into measurable value for risk management.
What is the maximum amount of funding available?
The award ceiling is $84,999.
How many awards are expected?
One award is expected.
When was the opportunity created?
The opportunity was created on February 5, 2019.
What was the original closing date?
The original closing date was February 12, 2019.
How long was the application window?
Based on the listed creation date (February 5, 2019) and original closing date (February 12, 2019), the application window was very short, consistent with a focused opportunity.
Who is eligible to apply?
Eligibility is listed broadly as "Others," but the description specifies that the eligible applicant for this particular opportunity is the University of New Mexico, indicating it is effectively directed to a single institution.
Is this an open competition for multiple organizations?
No. While the eligibility field is broad, the opportunity description identifies the University of New Mexico as the eligible applicant, implying a single-organization competition or a directed award.
What is the expected scope of this award?
The opportunity describes a narrowly scoped, collaborative USGS-supported study designed to quantify the decision and economic value of Landsat-enabled LANDFIRE information, augmented by subsurface geologic attributes, for managing forest risks.
What is the main deliverable implied by the opportunity?
The description indicates the main deliverable is an applied VOI impact assessment demonstrating where and how Landsat and related datasets provide decision-support value in forest risk management, including an economic interpretation of that value.
What is the central question the project is trying to answer?
At its core, the project aims to answer how much Landsat-derived LANDFIRE information (and related Earth science datasets, including subsurface geologic attributes) improves forest risk management decisions and what that improvement is worth in measurable and economic terms.
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