This GULN grant is for assessing the effectiveness of lidar-based vegetation classifications at Vicksburg National Military Park (VICK) by comparing them with ground truthing data. The project’s primary objective is to determine how well lidar vegetation data predicts actual ground-level communities. Both lidar and ground truth datasets are available in leaf-on and leaf-off conditions, allowing for comprehensive analysis. The findings from this research will be crucial in shaping the GULN’s methodology for future vegetation monitoring efforts across its entire network, ensuring accurate and reliable ecological assessments. This initiative aims to refine remote sensing techniques for environmental management.
Opportunity ID: 102134
General Information
| Document Type: | Grants Notice |
| Funding Opportunity Number: | E11AC60574 |
| Funding Opportunity Title: | Analysis of Concordance between Lidar Vegetation Classification of Vicksburg National Military Park and Ground Truthing Data |
| Opportunity Category: | Discretionary |
| Opportunity Category Explanation: | – |
| Funding Instrument Type: | Cooperative Agreement |
| Category of Funding Activity: | Other (see text field entitled “Explanation of Other Category of Funding Activity” for clarification) |
| Category Explanation: | Biological/Technical Assistance |
| Expected Number of Awards: | 1 |
| Assistance Listings: | 15.945 — Cooperative Research and Training Programs – Resources of the National Park System |
| Cost Sharing or Matching Requirement: | No |
| Version: | Synopsis 1 |
| Posted Date: | Jun 28, 2011 |
| Last Updated Date: | – |
| Original Closing Date for Applications: | Jul 05, 2011 |
| Current Closing Date for Applications: | Jul 05, 2011 |
| Archive Date: | Aug 04, 2011 |
| Estimated Total Program Funding: | $25,284 |
| Award Ceiling: | $25,285 |
| Award Floor: | $0 |
Eligibility
| Eligible Applicants: | Others (see text field entitled “Additional Information on Eligibility” for clarification) |
| Additional Information on Eligibility: | 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. |
Additional Information
| Agency Name: | National Park Service |
| Description: | The primary objective of this project is to assess the degree to which vegetation classifications of Vicksburg National Military Park (VICK) based on lidar data are predictive of vegetation communities derived from ground truthing data. Both lidar and ground truth data are available in both leaf-on and leaf-off condition. These analyses will inform the approach taken by the GULN for monitoring vegetation across the network. |
| Link to Additional Information: | – |
| Grantor Contact Information: | If you have difficulty accessing the full announcement electronically, please contact:
Tonya Bradley
Contract Specialist Phone 402-661-1656 Email:tonya_bradley@nps.gov |
Version History
| Version | Modification Description | Updated Date |
|---|---|---|
Related Documents
There are no related documents on this grant.
Packages
| Agency Contact Information: | Tonya Bradley Contract Specialist Phone 402-661-1656 Email: tonya_bradley@nps.gov |
| Who Can Apply: | Organization Applicants |
| Assistance Listing Number | Competition ID | Competition Title | Opportunity Package ID | Opening Date | Closing Date | Actions |
|---|---|---|---|---|---|---|
| 15.945 | PKG00061632 | Jun 28, 2011 | Jul 05, 2011 | View |
Package 1
Mandatory forms
102134 SF424-2.0.pdf
102134 GG_LobbyingForm-1.1.pdf
102134 SF424A-1.0.pdf
102134 SF424B-1.1.pdf
Share This Post, Choose Your Platform!
About the Author: osnqt
