EGC_services/IMG_VCGI_TREECANOPY2022_WM_NOCACHE

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Service Description: This Coniferous and Deciduous dataset was derived from high-resolution remotely sensed data -- 2021/2022 NAIP and 2016 LiDAR. Object-based image analysis techniques (OBIA) were employed to extract potential tree canopy and coniferous deciduous 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 ensure 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 1:2500 and all observable errors were corrected.

Name: EGC_services/IMG_VCGI_TREECANOPY2022_WM_NOCACHE_v1

Description: This Coniferous and Deciduous dataset was derived from high-resolution remotely sensed data -- 2021/2022 NAIP and 2016 LiDAR. Object-based image analysis techniques (OBIA) were employed to extract potential tree canopy and coniferous deciduous 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 ensure 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 1:2500 and all observable errors were corrected.

Single Fused Map Cache: false

Extent:

Initial Extent:

Full Extent:

Pixel Size X: 0.5

Pixel Size Y: 0.5

Band Count: 1

Pixel Type: U8

RasterFunction Infos: {"rasterFunctionInfos": [ { "name": "Apply_TreeCanopy2022_colormap", "description": "Apply colormap and legend labels", "help": "" }, { "name": "None", "description": "", "help": "" } ]}

Mensuration Capabilities: Basic

Inspection Capabilities:

Has Histograms: true

Has Colormap: false

Has Multi Dimensions : false

Rendering Rule:

Min Scale: 0

Max Scale: 0

Resampling: false

Copyright Text: VCGI, UVM SAL

Service Data Type: esriImageServiceDataTypeThematic

Min Values: 0

Max Values: 2

Mean Values: 1.7006747432521894

Standard Deviation Values: 0.45796249575519915

Object ID Field: OBJECTID

Fields:

OBJECTID ( type: esriFieldTypeOID, alias: OBJECTID )
Shape ( type: esriFieldTypeGeometry, alias: Shape )
Name ( type: esriFieldTypeString, alias: Name, length: 200 )
MinPS ( type: esriFieldTypeDouble, alias: MinPS )
MaxPS ( type: esriFieldTypeDouble, alias: MaxPS )
LowPS ( type: esriFieldTypeDouble, alias: LowPS )
HighPS ( type: esriFieldTypeDouble, alias: HighPS )
Category ( type: esriFieldTypeInteger, alias: Category , Coded Values: [0: Unknown] , [1: Primary] , [2: Overview] , ...6 more... )
Tag ( type: esriFieldTypeString, alias: Tag, length: 100 )
GroupName ( type: esriFieldTypeString, alias: GroupName, length: 100 )
ProductName ( type: esriFieldTypeString, alias: ProductName, length: 100 )
CenterX ( type: esriFieldTypeDouble, alias: CenterX )
CenterY ( type: esriFieldTypeDouble, alias: CenterY )
ZOrder ( type: esriFieldTypeInteger, alias: ZOrder )
Shape_Length ( type: esriFieldTypeDouble, alias: Shape_Length )
Shape_Area ( type: esriFieldTypeDouble, alias: Shape_Area )

Default Mosaic Method: Northwest

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

SortField:

SortValue: null

Mosaic Operator: First

Default Compression Quality: 75

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: true

Allow Analysis: true

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 Histograms Statistics Key Properties Legend Raster Function Infos

Supported Operations: Export Image Query Identify Measure Compute Histograms Compute Statistics Histograms Get Samples Compute Class Statistics Query GPS Info Find Images Image to Map Map to Image Measure from Image Image to Map Multiray Query Boundary Compute Pixel Location Compute Angles Validate Project

EGC_services/IMG_VCGI_TREECANOPY2022_WM_NOCACHE_v1 (ImageServer)