GIS Data Catalog
Landcover Forest Canopy 2023
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Summary
This high-resolution vector dataset consists of land cover tree canopy derived from countywide multispectral imagery.
This tree canopy layer was extracted by Ecopia by leveraging AI-based classification of aerial imagery collected in 2023 for the area of interest (AOI) in King County, in conjunction land cover classification data.
Random locations were QC’d by King County employees for accuracy.
This dataset is not intended for use as a surveyed product.
King County makes no representations or warranties, expressed or implied, as to accuracy, completeness, timeliness, or rights to the use of such information.
Description
This Landcover Forest dataset contains areas >500 sq.
ft dominated by trees generally greater than 15 ft tall and greater than 20% of the total vegetation cover.
Landcover Forest layer may overlap with underlying land cover classifications and is intended to show the extent of tree canopy during the full foliage season.
Because this imagery was only collected during the leaf-on season, the differentiation between deciduous, evergreen, and mixed forest canopy is unclear.
Layer information
| Layer Name | landcover_forest_2023_area |
| Subject Category | Natural Resources |
| Title | Landcover Forest Canopy 2023 |
| Feature Count | 954958 |
| Feature Type | Polygon |
| Spatial reference | EPSG:2926 |
| Control ID | 3028 |
| Place Keywords | Washington State, King County, WA, Pacific NW |
| Theme Keywords | Natres |
| Supplemental Information | None |
Table Preview
Attribute information
|
OBJECTID
From Esri |
Description
Internal feature number. DomainSequential unique whole numbers that are automatically generated. |
|
Category
From King County |
Description
Not Found Domaindeciduous, evergreen, mixed |
|
DataSource
From King County |
Description
Not Found DomainNot Found |
|
LoadedBy
From King County |
Description
Not Found DomainNot Found |
|
LoadDate
No Source Noted |
Description
Not Found DomainNot Found |
|
LastEditedBy
From King County |
Description
Not Found DomainNot Found |
|
LastEditDate
No Source Noted |
Description
Not Found DomainNot Found |
|
Shape
From Esri |
Description
Feature geometry. DomainCoordinates defining the features. |
|
Shape.STArea()
From SQL Server |
Description
Returns the area of a geometry instance in square units, based on the spatial reference identifier (SRID) of the geometry. DomainDouble |
|
Shape.STLength()
From SQL Server |
Description
Returns the total length of the elements in a geometry instance. DomainDouble |
Contact information
| Maintained by | DNRP - Water and Land Resources |
| Primary |
Harkeerat Kang
Harkeerat.Kang@kingcounty.gov |
Terms of Use
| License | Terms of use and copyright |
Use this Data
|
Links
How to use in ArcGIS Pro |
|
| Sharing Status | Public |
Summary
This high-resolution vector dataset consists of land cover tree canopy derived from countywide multispectral imagery.
This tree canopy layer was extracted by Ecopia by leveraging AI-based classification of aerial imagery collected in 2023 for the area of interest (AOI) in King County, in conjunction land cover classification data.
Random locations were QC’d by King County employees for accuracy.
This dataset is not intended for use as a surveyed product.
King County makes no representations or warranties, expressed or implied, as to accuracy, completeness, timeliness, or rights to the use of such information.
Description
This Landcover Forest dataset contains areas >500 sq.
ft dominated by trees generally greater than 15 ft tall and greater than 20% of the total vegetation cover.
Landcover Forest layer may overlap with underlying land cover classifications and is intended to show the extent of tree canopy during the full foliage season.
Because this imagery was only collected during the leaf-on season, the differentiation between deciduous, evergreen, and mixed forest canopy is unclear.
Contact information
| Maintained by | DNRP - Water and Land Resources |
| Primary |
Harkeerat Kang
Harkeerat.Kang@kingcounty.gov |
Terms of use and copyright
| License | Terms of use and copyright |