Cooperative Ecosystem Studies Unit, Great Lakes Northern Forests | G17AS00065

Frequently Asked Questions (FAQ) - CESU Great Lakes Northern Forests (USGS) Funding Opportunity

What is the name and opportunity number of this grant?

This funding opportunity is the Cooperative Ecosystem Studies Unit (CESU), Great Lakes Northern Forests opportunity with Opportunity Number G17AS00065.

Which federal agency is offering this opportunity?

The opportunity was issued by the U.S. Department of the Interior, U.S. Geological Survey (USGS).

Which USGS office or center is associated with the announcement?

The opportunity is associated with the USGS Earth Resources Observation and Science (EROS) Center.

What type of award is being offered (grant vs. cooperative agreement)?

This is a discretionary award made through a cooperative agreement. That means the project is expected to include collaboration and substantial involvement between USGS and the award recipient, rather than functioning like a hands-off, standard grant.

What is the activity category for this opportunity?

The activity category is science and technology and other research and development.

What CFDA number is listed for this opportunity?

The opportunity is listed under CFDA 15.808.

What is the main purpose of the project funding?

The purpose is to support land cover research that improves how USGS evaluates and reports the quality of its land cover and land cover change products.

What kind of research topics are emphasized in the scope?

The work centers on methods for accuracy assessment and area estimation. A major focus is the statistical design problem of developing sampling approaches and estimation strategies that produce reliable accuracy metrics and defensible area estimates.

Is the project focused only on measuring map accuracy?

No. In addition to measuring whether products are correct, the scope emphasizes understanding how uncertainties in reference data (ground truth or validation labels) influence conclusions about product validity.

What is meant by "reference data uncertainty" in this context?

Reference data uncertainty refers to the fact that validation labels or ground truth data used to evaluate a land cover map can contain errors or ambiguity. Those imperfections can bias or weaken confidence in reported accuracy statements and change estimates, so the project is expected to address how to quantify and account for that uncertainty.

Which land cover products are explicitly mentioned as targets for this research?

The opportunity explicitly mentions the National Land Cover Database (NLCD) and the Land Change Monitoring, Assessment, and Projection (LCMAP) land change products.

Why are NLCD and LCMAP important in relation to this opportunity?

They are major USGS datasets used widely by federal, state, tribal, academic, and private-sector users for environmental monitoring, land management, and policy-relevant analysis. The intent of this award is to strengthen the statistical and methodological foundations behind how these datasets are validated and how uncertainty is communicated.

What kinds of outcomes would a successful project be expected to produce?

Based on the description, a successful project would be expected to contribute research results, analyses, or recommended approaches that help USGS strengthen: (1) sampling designs for validation, (2) statistical estimators for map accuracy and land change area, and (3) methods for evaluating and propagating reference data uncertainty when assessing the validity of NLCD and LCMAP products.

How much funding is available under this opportunity?

The award ceiling is $40,000.

How many awards does USGS anticipate making?

The opportunity anticipates making a single award.

When was the opportunity posted?

The posting was created on May 8, 2017.

What was the original application closing date?

The original closing date listed is May 22, 2017.

What does the short application window suggest about the project?

With a posting date of May 8, 2017 and an original closing date of May 22, 2017, the window appears short, which is consistent with a relatively focused and targeted project scale (also reflected by the $40,000 ceiling and expectation of a single award).

Who is eligible to apply?

Eligibility is described broadly as "Others," with additional eligibility clarification referenced in the full announcement text.

Does "Others" mean anyone can apply?

The description notes that additional eligibility clarification is referenced in the full announcement. Under CESU mechanisms, eligibility commonly indicates that only certain partner institutions (often CESU network members) or specific types of organizations may apply, but the exact requirements are stated as being in the full announcement text.

How does the CESU context relate to who can apply?

The opportunity is issued under the Cooperative Ecosystem Studies Unit (CESU) framework, and the description indicates that eligibility details are clarified in the full announcement. In practice, CESU opportunities often involve specific partner or network participation rules, but the controlling details are those in the full announcement.

What is the core technical challenge the project is meant to address?

The central challenge described is designing sampling and estimation methods for accuracy assessment and area estimation that are statistically reliable, while also accounting for uncertainty and possible error in the reference (validation) data used to evaluate NLCD and LCMAP products.

What is meant by "area estimation" in the opportunity description?

Area estimation refers to producing defensible estimates of the amount of land in particular classes (and the amount of change between classes) derived from land cover and land cover change products, supported by appropriate sampling designs and statistical estimators.

What is meant by "accuracy metrics" in the opportunity description?

Accuracy metrics are quantitative measures used to describe how well a land cover product matches reference data, and the opportunity emphasizes improving how those metrics are produced through better sampling designs and estimation strategies.

How is uncertainty expected to be handled in this project?

The scope highlights evaluating and propagating uncertainty in reference data so that conclusions about product validity, accuracy statements, and land change estimates are more credible, transparent, and statistically defensible.

What is the overall goal for USGS and end users?

The overall intent is to produce more credible, transparent, and statistically defensible statements about land cover and land cover change products that many downstream decisions depend on.