Segment

inputRaster

(Required)

The complete JSON rft (uri or by value), the complete XML rft (uri or by value), portal item ID, image service URL, cloud raster dataset, or shared raster dataset that will be segmented. If multiple inputs are given, then itemId takes priority. If a complete rft is given, then spectralDetail , spatialDetail , minimumSegmentSizeInPixels , and bandIndexes will not be honored. This option is used by ArcGIS Pro and web apps.

Syntax: A string describes the input raster.

Example:

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//Portal Item ID
{"itemId": <portal item id>}

//Image Service URL
{"url": <image service url}

//Service Properties
{"serviceProperties":{"name":"testrasteranalysis",
  "serviceUrl":"https://<server name>/server/rest/services/Hosted/testrasteranalysis/ImageServer"},
  "itemProperties":{"itemId":"8cfbd3ec25584d0d8f4ed23b8ff7c43b", "folderId", "sdfwerfbd3ec25584d0d8f4",: }}

outputName

(Required)

The location where the service will generate the output raster.

Syntax: JSON object that describes the output raster.

Example:

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//Portal Item ID
{"itemId": <portal item id>}

//Image Service URL
{"url": <image service url}

//Service Properties
{"serviceProperties":{"name":"testrasteranalysis",
  "serviceUrl":"https://<server name>/server/rest/services/Hosted/testrasteranalysis/ImageServer"},
  "itemProperties":{"itemId":"8cfbd3ec25584d0d8f4ed23b8ff7c43b", "folderId", "sdfwerfbd3ec25584d0d8f4",: }}

spectralDetail

Sets the level of importance given to the spectral differences of features in your imagery. Valid values range fro 1.0-20.0. A high value is appropriate when you have features you want to classify separately but have somewhat similar spectral characteristics. Smaller values create spectrally smoother outputs. For example, setting a higher spectral detail value for a forested scene will preserve greater discrimination between the different tree species, resulting in more segments.

Example

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SpectralDetail=15.5

spatialDetail

Sets the level of importance given to the proximity between features in your imagery. Valid values range from 1-20. A high value is appropriate for a scene where your features of interest are small and clustered together. Smaller values create spatially smoother outputs. For example, in an urban scene you could classify an impervious surface using a smaller spatial detail, or you could classify buildings and roads as separate classes using a higher spatial detail.

Example

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SpatialDetail=15

minimumSegmentSizeInPixels

Merges segments smaller than this size with their best fitting neighbor segment. This is related to the minimum mapping unit for a mapping project. Units are in pixels.

Example

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minimumSegmentSizeInPixels=20

bandIndexes

Defines which 3 bands are used in segmentation. Choose the bands that visually discriminate your features of best interest. The value is a string of three numbers separated by three commas.

Example

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bandIndexes: "0, 1, 2"

removeTilingArtifacts

If the value is false or 0, the tool will not run to remove tiling artifacts after segmentation. The result may seem blocky at some tiling boundaries.

Example

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removingTilitingArtifacts="true"