High Resolution Land Cover Data
Sector: Water Supply and Storage • Location: United States of America
Source: Grants.gov
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:
- Develop a 1 meter resolution, 8 class (Water; Tree canopy; Scrub-shrub; Herbaceous/Grass; Barren; Impervious surfaces--roads/other; Impervious surfaces--structures; Imperv
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | archived |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
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. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
Article Published Date | Obfuscated Data |
