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ItemDescription
Paige Brochu
University of Vermont Spatial Analysis Laboratory
Director
802-656-3324
802-656-8683
81 Carrigan Drive
Aiken Center Room 205
Burlington
VT
05405
US
Paige.Brochu@uvm.edu
20260415
ArcGIS Metadata
1.0
Land_Cover_2024
2026-03-27
University of Vermont Spatial Analysis Laboratory
remote sensing image
<div style='text-align:Left;'><div><p><span>High resolution land cover dataset for Virginia Beach, Virginia (vector format produced from 0.5 Foot raster land cover). Seven land cover classes were mapped: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, and (7) other paved surfaces. The primary sources used to derive this land cover layer were 2024 LiDAR data and 2023 NAIP imagery. Ancillary data sources included GIS data provided by Virginia Beach, Virginia or created by the UVM Spatial Analysis Laboratory. Object-based image analysis techniques (OBIA) were employed to extract land cover information using the best available remotely sensed and vector GIS datasets. OBIA systems work by grouping pixels into meaningful objects based on their spectral and spatial properties, while taking into account boundaries imposed by existing vector datasets. Within the OBIA environment a rule-based expert system was designed to effectively mimic the process of manual image analysis by incorporating the elements of image interpretation (color/tone, texture, pattern, location, size, and shape) into the classification process. A series of morphological procedures were employed to insure that the end product is both accurate and cartographically pleasing. Following the automated OBIA mapping a detailed manual review of the dataset was carried out at a scale of 2500 and all observable errors were corrected.</span></p></div></div>
This dataset was developed as part of the Virginia Beach Urban Tree Canopy Assessment 2018-2024. As such, it represents a 'top down' mapping perspective in which tree canopy over hanging other features is assigned to the tree canopy class. At the time of its creation this dataset represents the most detailed and accurate land cover dataset for the area.
University of Vermont Spatial Analysis Laboratory in collaboration with Virginia Beach.
Paige Brochu
University of Vermont Spatial Analysis Laboratory
Director
802-656-3324
802-656-8683
Aiken Room 205
81 Carrigan Drive
Burlington
VT
05405
US
Paige.Brochu@uvm.edu
Virginia Beach
Virginia Beach
Virginia
2023
tree canopy
Urban
UTC
Land cover
ISO 19115 Topic Categories
imageryBaseMapsEarthCover
tree canopy
Urban
UTC
Land cover
imageryBaseMapsEarthCover
Virginia Beach
Virginia Beach
Virginia
2024
Virginia Beach, Virginia; 2023
2024-10-09
This assessment was completed by the University of Vermont's Spatial Analysis Laboratory with funding from the Virginia Beach. The methods used were developed by the University of Vermont Spatial Analysis Laboratory in partnership with the USDA Forest Service. Tree canopy assessments have been conducted for numerous communities throughout the U.S. where the results have been instrumental in helping to establishing tree canopy goals.
Esri ArcGIS 13.4.0.55405
1
-76.236400
-75.854415
36.936467
36.545087
No accuracy assessment was conducted, but the dataset was subject to a thorough manual quality control (QC). Accuracy assessments from previous UTC land cover datasets indicate that the use OBIA techniques in combination with a detailed QC yield an overall accuracy of 95% or better.
Valid raster dataset.
Complete coverage for the study area using the most recent boundary data.
Vector
Planimetric data
Planimetric data
4-band, leaf-on aerial imagery
12000
National Agricultural Imagery Program 4-band data
NAIP
LiDAR point clouds
LiDAR
LiDAR
Object based image analysis (OBIA) using a rule-based expert system
2026-01-30
Manual corrections to land cover classification
2026-02-17
LandCover7Class_2024_VirginaBeach_VA.tif
UTC
UVM Spatial Analysis Laboratory
OID
Internal feature number.
ESRI
Sequential unique whole numbers that are automatically generated.
Count
# pixels per land cover class
Internal
Number of pixels per land cover class
Value
Land cover code
UTC
1
Tree Canopy
Spatial Analysis Lab, University of Vermont
2
Grass/Shrub
Spatial Analysis Lab, University of Vermont
3
Bare Soil
Spatial Analysis Lab, University of Vermont
4
Water
Spatial Analysis Lab, University of Vermont
5
Building
Spatial Analysis Lab, University of Vermont
6
Road/Railroad
Spatial Analysis Lab, University of Vermont
7
Other Paved Surfaces
Spatial Analysis Lab, University of Vermont
Seven land cover classes were mapped: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads/railroads, and (7) other paved surfaces.
Raster Dataset
dataset
EPSG
8.2.10(10.3.1)
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