Opportunity Information: Apply for E11AC60574
Apply for E11AC60574
- The National Park Service in the other (see text field entitled explanation of other category of funding activity for clarification) sector is offering a public funding opportunity titled "Analysis of Concordance between Lidar Vegetation Classification of Vicksburg National Military Park and Ground Truthing Data" and is now available to receive applicants.
- Interested and eligible applicants and submit their applications by referencing the CFDA number(s): 15.945 Cooperative Research and Training Programs Resources of the National Park System.
- This funding opportunity was created on Jun 28, 2011 and posted on Jun 28, 2011.
- Applicants must submit their applications by Jul 5, 2011. (Agency may still review applications by suitable applicants for the remaining/unused allocated funding in 2026.)
- The funding agency has allocated a total of $25,284.00 to eligible and selected applicants.
- Each selected applicant is eligible to receive up to $25,285.00 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).
- This is a Notice of Intent of a single source task agreement award to Southern Illinois University, Edwardsville, IL under the Great Rivers Cooperative Ecosystem Studies Unit (CESU). The Cooperator has been working with the Gulf Coast Inventory and Monitoring Network (GULN), conducting the analyses in support of the development of the GULN vegetation monitoring protocol through a sub agreement with Louisiana State University (LSU). Because this is a unique approach combining field data with lidar derived vegetation classes, the data analysis approaches are exploratory in nature. Starting this process over with a new investigator would be costly to the NPS in both time and money.
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Opportunity Summary:
This grant opportunity, titled "Analysis of Concordance between Lidar Vegetation Classification of Vicksburg National Military Park and Ground Truthing Data" (Funding Opportunity Number E11AC60574), was issued by the National Park Service as a discretionary funding action using a cooperative agreement. The work falls under biological and technical assistance and is intended to support the Gulf Coast Inventory and Monitoring Network (GULN) in improving how it monitors vegetation across its parks. The project is centered on Vicksburg National Military Park (VICK) and focuses on evaluating how well vegetation maps or classes created from lidar data match what is actually observed on the ground through field-based vegetation community surveys (ground truthing). In practical terms, the project is meant to measure the level of agreement between remotely sensed classifications and real-world vegetation communities, and to determine whether lidar-based products can reliably predict those communities for monitoring purposes.
A key element of the work is that both datasets, the lidar-derived vegetation classifications and the ground truthing observations, exist in two seasonal or phenological conditions: leaf-on and leaf-off. That matters because vegetation structure and detectability can change substantially depending on whether trees and shrubs have leaves, which in turn can influence lidar returns and classification performance. By comparing lidar classifications to field-derived vegetation community assignments under both leaf-on and leaf-off conditions, the project aims to identify when and how lidar is most effective, where it tends to misclassify vegetation, and what factors may be driving mismatches. The results are intended to directly inform GULN decisions about the best approach for network-wide vegetation monitoring, including how to design protocols, what datasets to prioritize, and how to interpret or validate lidar-based vegetation products in the future.
The opportunity was structured as a single expected award with an estimated total funding amount of $25,284, an award ceiling of $25,285, and no required cost sharing or matching. The program is associated with CFDA 15.945, Cooperative Research and Training Programs - Resources of the National Park System. The posting date and creation date were June 28, 2011, with an original and current closing date of July 5, 2011, and it was archived on August 4, 2011. While the listing appears in a grants format, the eligibility details make clear it was a Notice of Intent for a single-source task agreement award rather than an open competition. The identified recipient was Southern Illinois University, Edwardsville, operating under the Great Rivers Cooperative Ecosystem Studies Unit (CESU).
The justification for limiting eligibility to this single recipient was based on continuity, specialized expertise, and efficiency. According to the announcement, the cooperator had already been working with GULN on the relevant analyses through a subagreement with Louisiana State University, and the analytic approach was described as exploratory because it combines field data with lidar-derived vegetation classes in a way that is considered unique for this application. The agency noted that restarting the work with a new investigator would be costly in time and money, implying that the existing team already had familiarity with the datasets, the park context, and the evolving vegetation monitoring protocol needs, which would help ensure timely and consistent results.
Overall, the opportunity can be understood as a targeted, applied research and analysis effort meant to test and quantify the reliability of lidar-based vegetation classification for real management use. Instead of creating new lidar acquisitions or conducting new field campaigns as the primary deliverable, the core value is in the comparative analysis: determining concordance between remote sensing classifications and ground-truthed vegetation communities across different canopy conditions, then translating those findings into practical guidance for GULN monitoring strategy. The listed point of contact for access issues was Tonya Bradley, Contract Specialist, reachable by phone at 402-661-1656.
Frequently Asked Questions (FAQ)
What is the title of this grant opportunity?
The opportunity is titled "Analysis of Concordance between Lidar Vegetation Classification of Vicksburg National Military Park and Ground Truthing Data."
What is the Funding Opportunity Number?
The Funding Opportunity Number is E11AC60574.
Which federal agency issued this opportunity?
The opportunity was issued by the National Park Service (NPS).
What type of funding instrument is being used?
This was issued as a discretionary funding action using a cooperative agreement.
What program area does the work fall under?
The work falls under biological and technical assistance.
Which program is this opportunity associated with (CFDA)?
This opportunity is associated with CFDA 15.945, Cooperative Research and Training Programs - Resources of the National Park System.
What is the overall purpose of the project?
The purpose is to support the Gulf Coast Inventory and Monitoring Network (GULN) by improving how vegetation is monitored across its parks, using an analysis that compares lidar-based vegetation classifications to field-based vegetation community survey data (ground truthing).
Which park is the focus of the project?
The project is centered on Vicksburg National Military Park (VICK).
What does "concordance" mean in the context of this project?
In this context, concordance refers to the level of agreement between vegetation classes or maps produced from lidar data and the vegetation communities observed on the ground through field-based surveys.
What are the two datasets being compared?
The analysis compares (1) lidar-derived vegetation classifications and (2) field-derived vegetation community assignments from ground truthing surveys.
Why is the comparison important for vegetation monitoring?
The comparison is meant to determine whether lidar-based products can reliably predict real-world vegetation communities for monitoring purposes, and to identify when and where lidar classifications tend to match or mismatch field observations.
Does the project involve different seasons or canopy conditions?
Yes. Both the lidar-derived classifications and the ground truthing observations exist in two phenological conditions: leaf-on and leaf-off.
What do "leaf-on" and "leaf-off" mean here?
They describe whether trees and shrubs have leaves at the time data were collected or represented. Vegetation structure and detectability can change substantially between leaf-on and leaf-off conditions, which can influence lidar returns and classification performance.
How will leaf-on vs. leaf-off conditions be used in the analysis?
The project compares lidar classifications to field-derived vegetation communities under both leaf-on and leaf-off conditions to identify when lidar is most effective, where it tends to misclassify vegetation, and what factors may be driving mismatches.
Is the project focused on collecting new lidar data or doing new fieldwork?
The description emphasizes that the core value is the comparative analysis of existing lidar-derived classifications and existing ground-truth observations, rather than new lidar acquisitions or new field campaigns as the primary deliverable.
What are the expected practical outcomes for GULN?
The results are intended to directly inform GULN decisions about vegetation monitoring strategy, including how to design protocols, what datasets to prioritize, and how to interpret or validate lidar-based vegetation products in the future.
How many awards were expected under this opportunity?
The opportunity was structured as a single expected award.
What was the estimated total funding amount?
The estimated total funding amount was $25,284.
What was the award ceiling?
The award ceiling was $25,285.
Was cost sharing or matching required?
No. There was no required cost sharing or matching.
Was this an open competition?
No. Although it appears in a grants format, the eligibility details indicate it was a Notice of Intent for a single-source task agreement award rather than an open competitive opportunity.
Who was the identified recipient?
The identified recipient was Southern Illinois University, Edwardsville, operating under the Great Rivers Cooperative Ecosystem Studies Unit (CESU).
Why was eligibility limited to a single recipient?
The justification cited continuity, specialized expertise, and efficiency. The cooperator had already been working with GULN on relevant analyses through a subagreement with Louisiana State University, and restarting with a new investigator was described as costly in time and money.
What made the analytic approach notable according to the announcement?
The approach was described as exploratory because it combines field data with lidar-derived vegetation classes in a way considered unique for this application.
What were the posting and closing dates for the opportunity?
The posting date and creation date were June 28, 2011. The original and current closing date was July 5, 2011.
When was the opportunity archived?
The listing was archived on August 4, 2011.
Who is the listed point of contact for access issues?
The listed point of contact for access issues was Tonya Bradley, Contract Specialist.
How can the point of contact be reached?
Tonya Bradley was listed with the phone number 402-661-1656.
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