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Compute Segment Attributes

Available with Spatial Analyst license.

  • Summary
  • Usage
  • Syntax
  • Code sample
  • Environments
  • Licensing information

Summary

Computes a set of attributes associated with the segmented image. The input raster can be a single-band or 3-band, 8-bit segmented image.

Usage

  • This tool generates the attributes for each segment that exists in the image. Attributes include mean, standard deviation, segment size, converged color (from the Segment Mean Shift tool), and compactness.

  • See Analysis environments and Spatial Analyst for additional details on the geoprocessing environments that apply to this tool.

Syntax

ComputeSegmentAttributes(in_segmented_raster, {in_additional_raster}, {used_attributes})
ParameterExplanationData Type
in_segmented_raster

The input segmented raster dataset, where all the pixels belonging to a segment have the same converged RGB color. Usually, it is an 8-bit, 3-band RGB raster, but it can also be a 1-band grayscale raster.

Raster Layer; Mosaic Layer
in_additional_raster
(Optional)

Incorporate ancillary raster datasets, such as a multispectral image or a DEM, to generate attributes and other required information for the classifier. This raster will be needed when calculating attributes such as mean or standard deviation. This parameter is optional.

Raster Layer; Mosaic Layer
used_attributes
[used_attributes,...]
(Optional)

Specifies the attributes to be included in the attribute table associated with the output raster.

  • COLOR —The RGB color values are derived from the input raster, on a per-segment basis.
  • MEAN —The average digital number (DN), derived from the optional pixel image, on a per-segment basis.
  • STD —The standard deviation, derived from the optional pixel image, on a per-segment basis.
  • COUNT —The number of pixels comprising the segment, on a per-segment basis.
  • COMPACTNESS —The degree to which a segment is compact or circular, on a per-segment basis. The values range from 0 to 1, where 1 is a circle.
  • RECTANGULARITY —The degree to which the segment is rectangular, on a per-segment basis. The values range from 0 to 1, where 1 is a rectangle.

If the only input into the tool is a segmented image, the default attributes are COLOR, COUNT, COMPACTNESS, and RECTANGULARITY. If an in_additional_raster is also included as an input along with a segmented image, then MEAN and STD are available as options.

String

Return Value

NameExplanationData Type
out_index_raster_dataset

The output segment index raster, where the attributes for each segment are recorded in the associated attribute table.

Raster

Code sample

ComputeSegmentAttributes example 1 (Python window)

This example computes segment attributes for a TIFF raster.

import arcpy
from arcpy.sa import *

compute_att = ComputeSegmentAttributes(
                  "c:/test/moncton_seg.tif", "c:/test/moncton.tif", 
                  "COLOR;MEAN;STD;COUNT;COMPACTNESS;RECTANGULARITY")

compute_att.save("c:/test/moncton_computeseg.tif")
ComputeSegmentAttributes example 2 (stand-alone script)

This example computes segment attributes for a TIFF raster.

# Import system modules
import arcpy
from arcpy.sa import *


# Set local variables
inSegRaster = "c:/test/moncton_seg.tif"
in_additional_raster = "c:/test/moncton.tif"
attributes = "COLOR;MEAN;STD;COUNT;COMPACTNESS;RECTANGULARITY"

# Check out the ArcGIS Spatial Analyst extension license
arcpy.CheckOutExtension("Spatial")

# Execute 
compute_att = ComputeSegmentAttributes(inSegRaster, in_additional_raster, 
                                       attributes)
#save output 
compute_att.save("c:/test/moncton_computeseg.tif")

Environments

  • Compression
  • Current Workspace
  • Extent
  • Geographic Transformations
  • Output Coordinate System
  • NoData
  • Parallel Processing Factor
  • Pyramid
  • Scratch Workspace
  • Snap Raster
  • Tile Size

Licensing information

  • Basic: Requires Spatial Analyst
  • Standard: Requires Spatial Analyst
  • Advanced: Requires Spatial Analyst

Related topics

  • An overview of the Segmentation and Classification toolset
  • What is image classification?

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