ArcGIS Tutorial: Iso Clustering

　　Summary

Use the Isodata clustering algorithm to determine the characteristics of a natural grouping of cells in a multidimensional attribute space and store the results in an output ASCII signature file.

　　Usage

· The Iso clustering tool performs clustering of multivariate data grouped in the input bands list. The resulting feature file can be used as input to the classification tool that generates the unsupervised classification raster.

· The minimum valid value for the number of classes is two. There is no maximum number of clusters. Typically, the more clustering you have, the more iterations you need.

· To provide sufficient statistical data to generate a feature file for future categorization, each cluster should contain enough cells to accurately represent the cluster. The value entered for the minimum class size should be approximately 10 times times larger than the number of layers in the input raster band.

· The value entered for the sampling interval indicates that a cell is used in the cluster calculation for every n multiply n blocks of cells.

· You should not merge or remove classes, nor should you change any of the statistics for an ASCII signature file.

· Typically, the more cells that are included in the intersection range of the input bands, the greater the value specified for the minimum class size and sampling interval. The value entered for the sampling interval should be small enough to reasonably sample the smallest ideal category that exists in the input data.

· The class ID value in the output signature file starts with a start and then increases sequentially to the number of input classes. You can allocate any number of classes.

· If all the input bands have the same data range, the results will be more desirable. If the data range of the bands varies widely, you can use map algebra to perform the following equations to convert the various data ranges to the same range.

· where

· Z is the output raster with new data ranges.

· X is the input raster.

· Oldmin is the minimum value of the input raster.

· Oldmax is the maximum value of the input raster.

· Newmin is the desired minimum value for the output raster.

· Newmax is the desired maximum value for the output raster.

· If you enter a layer created from a multiband raster (more than three bands), the operation takes into account all the bands associated with the source dataset, not just the three bands loaded (symbolized) by the layer.

· You can specify a subset of bands for a multiband raster as input to the tool in several ways.

· If you want to use the tool dialog box, navigate to the multi-band raster by the button next to the input raster bands, open the grid, and select the desired band.

· If the multiband raster is a layer in the table of contents, you can use the Create Raster Layer tool to create a new multiband layer that contains only the desired bands.

· You can also use band compositing to create a new dataset that contains only the desired bands and use the resulting dataset as input to the tool.

· In Python, you can specify the desired bands directly in the tool parameters as a list.

　Grammar

Isocluster (In_raster_bands, Out_signature_file, number_classes, {number_iterations}, {min_class_size}, {Sample_ Interval})

　　Code instance

　　Iso cluster (Isocluster) Example 1 (Python window)

This example creates a signature file that divides the input multiband raster into five categories.

Import arcpy

From arcpy Import env

From ARCPY.SA Import *

Env.workspace = "C:/sapyexamples/data"

Isocluster ("Redlands", "C:/SAPYEXAMPLES/OUTPUT/ISOSIG.GSG", 5, 20, 50, 15)

　　Iso cluster (Isocluster) Example 2 (stand-alone script)

This example creates a signature file that divides the input multiband raster into five categories.

# Name:IsoCluster_Ex_02.py

# description:uses an isodata clustering algorithm to determine the

# Characteristics of the natural groupings of cells in multidimensional

# attribute space and stores the results in an output ASCII signature file.

# requirements:spatial Analyst Extension

# Import System Modules

Import arcpy

From arcpy Import env

From ARCPY.SA Import *

# Set Environment settings

Env.workspace = "C:/sapyexamples/data"

# Set Local Variables

Inraster = "Redlands"

Outsig = "REDLNDISO.GSG"

Classes = 5

Cycles = 20

Minmembers = 50

Sampinterval = 15

# Check out the ArcGIS Spatial Analyst extension License

arcpy. Checkoutextension ("Spatial")

# Execute Isocluster

Isocluster (Inraster, Outsig, classes, cycles, minmembers, Sampinterval)

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ArcGIS Tutorial: Iso Clustering