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EGC_services/IMG_VCGI_BASELANDCOVER2016_WM_CACHE_v1 (ImageServer)

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Service Description: High resolution land cover dataset for Vermont. Eight land cover classes were mapped: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, (7) other paved surfaces,and (8) railroads. The primary sources used to derive this land cover layer were 2013-2017 LiDAR data and 2016 NAIP imagery. Ancillary data sources included GIS data provided by the State of Vermont 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 1:3000 and all observable errors were corrected.

Name: EGC_services/IMG_VCGI_BASELANDCOVER2016_WM_CACHE_v1

Description: High resolution land cover dataset for Vermont. Eight land cover classes were mapped: (1) tree canopy, (2) grass/shrub, (3) bare earth, (4) water, (5) buildings, (6) roads, (7) other paved surfaces,and (8) railroads. The primary sources used to derive this land cover layer were 2013-2017 LiDAR data and 2016 NAIP imagery. Ancillary data sources included GIS data provided by the State of Vermont 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 1:3000 and all observable errors were corrected.

Single Fused Map Cache: true

Tile Info: Extent: Initial Extent: Full Extent: Pixel Size X: 0.5

Pixel Size Y: 0.5

Band Count: 3

Pixel Type: U8

RasterFunction Infos: {"rasterFunctionInfos": [{ "name": "None", "description": "A No-Op Function.", "help": "" }]}

Mensuration Capabilities: None

Has Histograms: false

Has Colormap: false

Has Multi Dimensions : false

Rendering Rule:

Min Scale: 1.8489297737236E7

Max Scale: 564.248588

Copyright Text: UVM SAL, VCGI

Service Data Type: esriImageServiceDataTypeThematic

Min Values: N/A

Max Values: N/A

Mean Values: N/A

Standard Deviation Values: N/A

Object ID Field: OBJECTID

Fields: Default Mosaic Method: Northwest

Allowed Mosaic Methods: NorthWest,Center,LockRaster,ByAttribute,Nadir,Viewpoint,Seamline,None

SortField:

SortValue: null

Mosaic Operator: First

Default Compression Quality: 80

Default Resampling Method: Nearest

Max Record Count: 1000

Max Image Height: 4100

Max Image Width: 15000

Max Download Image Count: 20

Max Mosaic Image Count: 20

Allow Raster Function: true

Allow Copy: null

Allow Analysis: null

Allow Compute TiePoints: false

Supports Statistics: true

Supports Advanced Queries: true

Use StandardizedQueries: true

Raster Type Infos: Has Raster Attribute Table: false

Edit Fields Info: null

Ownership Based AccessControl For Rasters: null

Child Resources:   Info   Key Properties   Legend   Raster Function Infos

Supported Operations:   Export Image   Query   Identify   Compute Histograms   Compute Statistics Histograms   Get Samples   Compute Class Statistics   Query Boundary   Compute Pixel Location   Compute Angles   Validate   Project