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Imagery/Orthoimagery_Latest_NDVI (ImageServer)

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View Footprint In:   ArcGIS Online Map Viewer

Service Description:
The imagery has a pixel resolution of 6 inches with a RMSE of 1.0 ft X and Y. Processing has been minimized to preserve the ability to use this data for raster analysis.
 
The normalized difference vegetation index (NDVI) is useful for measuring the quality, density, and amount of vegetation in a particular area. It is a single band dataset that represents vegetation health, based on the difference between the red and near infrared bands. Red and orange pixels represent areas with no vegetation. Yellow pixels represent areas with low to moderate vegetation. Green pixels represent areas with high vegetation density and health. This data is provided as a web service only (no download).
 
 
To view the latest imagery for any location in the state, customers should always use the "Orthoimagery_Latest" image service which can be found at https://nconemap.gov.
 
 
To find specific dates the images were captured use the imagery dates app or download the data.
 


Name: Imagery/Orthoimagery_Latest_NDVI

Description:
The imagery has a pixel resolution of 6 inches with a RMSE of 1.0 ft X and Y. Processing has been minimized to preserve the ability to use this data for raster analysis.
 
The normalized difference vegetation index (NDVI) is useful for measuring the quality, density, and amount of vegetation in a particular area. It is a single band dataset that represents vegetation health, based on the difference between the red and near infrared bands. Red and orange pixels represent areas with no vegetation. Yellow pixels represent areas with low to moderate vegetation. Green pixels represent areas with high vegetation density and health. This data is provided as a web service only (no download).
 
 
To view the latest imagery for any location in the state, customers should always use the "Orthoimagery_Latest" image service which can be found at https://nconemap.gov.
 
 
To find specific dates the images were captured use the imagery dates app or download the data.
 


Single Fused Map Cache: false

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

Pixel Size Y: 0.5

Band Count: 4

Pixel Type: U8

RasterFunction Infos: {"rasterFunctionInfos": [ { "name": "NDVI3", "description": "Creates a single band dataset that represents vegetation health, based on the difference between the red and near infrared bands. The negative values represent clouds, water, and snow, and values near zero represent rock and bare soil.", "help": "" }, { "name": "None", "description": "Make a Raster or Raster Dataset into a Function Raster Dataset.", "help": "" } ]}

Mensuration Capabilities: Basic

Has Histograms: false

Has Colormap: false

Has Multi Dimensions : false

Rendering Rule:

Min Scale: 0

Max Scale: 0

Copyright Text: NCCGIA, NC911 Board

Service Data Type: esriImageServiceDataTypeProcessed

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: ByAttribute

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

SortField: date

SortValue: 3000/01/01

Mosaic Operator: First

Default Compression Quality: 10000

Default Resampling Method: Nearest

Max Record Count: 1000

Max Image Height: 4100

Max Image Width: 15000

Max Download Image Count: 10

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   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 Boundary   Compute Pixel Location   Compute Angles   Validate   Project