ArcGIS REST Services Directory Login
JSON

Layer: Tree_Canopy_2014_2018_Chg_Py (ID: 1)

Name: Tree_Canopy_2014_2018_Chg_Py

Display Field: CLASS_NAME

Type: Feature Layer

Geometry Type: esriGeometryPolygon

Description: This layer is a high-resolution tree canopy change-detection layer for Prince George's County, Maryland. It contains three tree-canopy classes for the period 2014-2018: (1) No Change; (2) Gain; and (3) Loss. It was created by mapping the change from the source LiDAR and imagery for the two time periods. Tree canopy that existed during both time periods was assigned to the No Change category while trees removed, felled in storms, or canopy to disease were assigned to the Loss class. New tree canopy, either the result of natural growth or new plantings was assigned to the Gain class . Change was mapped using object-based image analysis (OBIA) techniques and included similar source datasets (LiDAR-derived surface models, multispectral imagery, and thematic GIS inputs) for the two time periods. 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 ensure that the end product is both accurate and cartographically pleasing. No accuracy assessment was conducted, but the dataset was subjected to a detailed manual review and correction. A minimum mapping unit of 40 square feet was enforced on isolate areas. Data was retained for areas smaller than 40 square feet where a border was shared with another area, making the combined area greater than the minimum mapping unit of 40 square feet.

Service Item Id: 1fc5eeeed72f4333b8ad38c90c04ff81

Copyright Text: The University of Vermont Spatial Analysis Laboratory created this datasets in collaboration with Sanborn.

Default Visibility: true

MaxRecordCount: 2000

Supported Query Formats: JSON, geoJSON, PBF

Min Scale: 0

Max Scale: 0

Supports Advanced Queries: true

Supports Statistics: true

Has Labels: false

Can Modify Layer: true

Can Scale Symbols: false

Use Standardized Queries: true

Supports Datum Transformation: true

Extent:
Drawing Info: Advanced Query Capabilities:
HasZ: false

HasM: false

Has Attachments: false

HTML Popup Type: esriServerHTMLPopupTypeAsHTMLText

Type ID Field: null

Fields:
Supported Operations:   Query   Query Attachments   Query Analytic   Generate Renderer   Return Updates

  Iteminfo   Thumbnail   Metadata