Opportunity ID: 275652

General Information

Document Type: Grants Notice
Funding Opportunity Number: NPS-15-NERO-0023
Funding Opportunity Title: High Resolution Land Cover 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: This is NOT a request for application. This is just an announcement that the Chesapeake Conservancy has already received an award for their work with High Resolution Land Data.
Expected Number of Awards: 1
Assistance Listings: 15.935 — National Trails System Projects
Cost Sharing or Matching Requirement: No
Version: Synopsis 1
Posted Date: Apr 03, 2015
Last Updated Date:
Original Closing Date for Applications: Apr 12, 2015 This is NOT a request for application. This is just an announcement that the Chesapeake Conservancy has already received an award for their work with High Resolution Land Data.
Current Closing Date for Applications: Apr 12, 2015 This is NOT a request for application. This is just an announcement that the Chesapeake Conservancy has already received an award for their work with High Resolution Land Data.
Archive Date: Apr 13, 2015
Estimated Total Program Funding: $1,307,953
Award Ceiling: $1,307,953
Award Floor: $1,307,953

Eligibility

Eligible Applicants: Nonprofits having a 501(c)(3) status with the IRS, other than institutions of higher education
Additional Information on Eligibility: This is NOT a request for application. This is just an announcement that the Chesapeake Conservancy has already received an award for their work with High Resolution Land Data.

Additional Information

Agency Name: National Park Service
Description: This is NOT a request for application. This is just an announcement that the Chesapeake Conservancy has already received an award for their work with High Resolution Land Data. Specifically, the Chesapeake Conservancy will:
1. Develop a 1 meter resolution, 8 class (Water; Tree canopy; Scrub-shrub; Herbaceous/Grass; Barren; Impervious surfaces–roads/other; Impervious surfaces–structures; Impervious surfaces–obscured by tree canopy) land cover dataset, with complete coverage for all counties that intersect the Chesapeake Bay watershed in New York, Pennsylvania, Maryland, Delaware, West Virginia, and the District of Columbia. This data will be produced as a seamless dataset covering the entire project area as well as separated individually by county to make it more accessible to local and state partners.
2. Develop accuracy assessments for each county in the project area that describe the overall and in-class accuracy. The accuracy of land cover will be assessed through the visual interpretation of aerial imagery using a stratified random sampling design (stratified by county and class) with a variable point density based on the heterogeneity of the land cover.
3. Deliver mosaic datasets of the source imagery, DEM data, DSM data derived from the LiDAR point cloud, and canopy/structure height layer used in the classification process. Each data product will be provided as a mosaic dataset composed of the individual tiles processed to the extent of the NAIP imagery footprints.
4. Document the methodologies followed in each step—e.g., data acquisition, processing, quality assurance, and accuracy confirmations—followed in the generation of the resultant land cover dataset.
5. Work with the Virginia Geographic Information Network (VGIN) to ensure the intended accuracy and eight classes of land cover data are fully consistent with VGIN’s work being conducted in parallel to acquire land cover data for all of Virginia.
Link to Additional Information:
Grantor Contact Information: If you have difficulty accessing the full announcement electronically, please contact:

Jen Fleming

Awarding Officer

Phone 2155976476
Email:Jennifer_Fleming@nps.gov

Version History

Version Modification Description Updated Date

Folder 275652 Full Announcement-1 -> noi -draft.pdf

Packages

2025-07-09T11:08:11-05:00

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