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Name: Tree Canopy Forest Patches

Display Field: OBJECTID

Type: Feature Layer

Geometry Type: esriGeometryPolygon

Description: Tree canopy was derived from high-resolution remotely sensed data -- 2018 NAIP and 2019 LiDAR. Object-based image analysis techniques (OBIA) were employed to extract potential tree canopy and trees 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 1:2000 and all observable errors were corrected.

Service Item Id: 0f8d7b4d6ee74f7c8b23a84bd562a9fc

Copyright Text: University of Vermont Spatial Analysis Laboratory in collaboration with the City of Boston.

Default Visibility: true

MaxRecordCount: 2000

Supported Query Formats: JSON, geoJSON, PBF

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Spatial Reference: 102686  (2249)  LatestVCSWkid(0)

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Type ID Field:

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• OBJECTID ( type: esriFieldTypeOID, alias: OBJECTID, editable: false, nullable: false, defaultValue: null, modelName: OBJECTID )
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Templates:

• Name: Tree Canopy Forest Patches
  Description:
  Prototype:
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Child Resources:   Field Groups   Contingent Values

Supported Operations:   Query   Query Analytic   Validate SQL   Generate Renderer   Return Updates   Iteminfo   Thumbnail   Metadata   Update Metadata