com.esri.arcgis.geoprocessing.tools.spatialstatisticstools
Class ClustersOutliers

java.lang.Object
  com.esri.arcgis.geoprocessing.AbstractGPTool
      com.esri.arcgis.geoprocessing.tools.spatialstatisticstools.ClustersOutliers

All Implemented Interfaces:

GPTool

public class ClustersOutliers
extends AbstractGPTool

Given a set of weighted features, identifies where high or low values cluster spatially, and features with values that are very different from surrounding feature values. The Cluster and Outlier Analysis (Anselin Local Morans I) tool is contained in the Spatial Statistics Tools tool box.
Learn more about how Cluster and Outlier Analysis: Anselin Local Moran's I works

Software restrictions: none

Illustration:

Usage tips:

• This tool honors the environment output coordinate system; . Feature geometry; is projected to the output coordinate system prior to analysis, so values entered for the Distance Band/Threshold Distance parameter should match those specified in the output coordinate system. All mathematical computations are based on the output coordinate system spatial reference;
• Calculations based on either Euclidean or Manhattan distance require projected data; to accurately measure distances.
• If you will be running several analyses on a single dataset (e.g., analyzing several different fields) or if you have a dataset with more than 3000 features, it is recommended that you construct the spatial weights matrix file; prior to analysis.
• The cluster and outlier analysis output is a Local Moran's I index value, Z score and P-value for each feature.
• This function creates as derived output the names of the index, z score, and p-value result fields.
• The Z scores and p-values are measures of statistical significance which tell you whether or not to reject the null hypothesis, feature by feature. They, in effect, indicate whether the apparent similarity (or dissimilarity) in values for a feature and its neighbors is greater than one would expect in a random distribution.
• The Z Score is based on the Randomization Null Hypothesis computation. For more information on Z Scores, see What is a Z Score? What is a p-value?;
• A high positive Z score for a feature indicates that the surrounding features have similar values (either high values or low value). The COType field indicates HH for a cluster of high values and LL for a cluster of low values.
• A low negative Z score for a feature indicates a spatial outlier. The COType field indicates if the feature has high value and is surrounded by features with low values (HL) or if the feature has a low value and is surrounded by features with high values (LH).
• For line and polygon features, true feature geometric centroids are used in computations.
• The input field should contain a variety of values. The math for this statistic requires some variation in the variable being analyzed; it cannot solve if all input values are 1, for example. If you have incident data, and want to analyze incident intensity, consider aggregating your incident data or using the Collect Events; tool prior to analysis.
• Whenever using shapefiles keep in mind that they cannot store null values. Tools or other procedures that create shapefiles from non-shapefile inputs may store or interpret null values as zero. This can lead to unexpected results.
• The Conceptualization of Spatial Relationships used for analysis should be based on your understanding of spatial interaction among the features being analyzed.
• For the Fixed Distance option, the distance band used for analysis should be based on your understanding of spatial interaction among the features being analyzed. Alternatively, features may be evaluated for a range of distance values or at the specific distance; where spatial autocorrelation is maximized.
• For Inverse Distance conceptualization options: when zero is entered for the "Distance Band or Threshold Distance" parameter all features are considered neighbors of all other features; when this parameter is left blank, a default threshold distance will be applied.
• When the spatial conceptualization is an Inverse Distance method (Inverse Distance, Inverse Distance Squared, or Zone of Indifference) any two points that are coincident will be given a weight of one to avoid zero division. This assures features are not excluded from analysis.
• With inverse distance conceptualizations, weights for distances less than 1 become unstable. The weighting for features separated by less than 1 unit of distance (common with Geographic Coordinate System; projections), are given a weight of 1.
• Analysis on features with a Geographic Coordinate System projection is not recommended with any of the inverse distance based spatial conceptualization methods.
• In ArcGIS version 9.2, the "Global" standardization option was removed. Global standardization returns the same results as no standardization. Models built with previous versions of ArcGIS that use the Global standardization option may need to be rebuilt.
• See the Modeling Spatial Relationships; help page for further explanation of this tool's parameters.
• Current map layers may be used to define the input feature class. When using layers, only the currently selected features are included in the analysis.
• Learn more about working with layers and table views;
• When this tool runs in ArcMap, the output feature class is automatically added to the Table of Contents (TOC) with default rendering applied to the Z Score field. The hot to cold rendering applied is defined by a layer file in /ArcToolbox/Templates/Layers. You can reapply the default rendering, if needed, by importing; the template layer symbology.

Field Summary

Fields inherited from class com.esri.arcgis.geoprocessing.AbstractGPTool

vals

Constructor Summary

ClustersOutliers()
Creates the Cluster and Outlier Analysis (Anselin Local Morans I) tool with defaults.

ClustersOutliers(Object inputFeatureClass, Object inputField, Object outputFeatureClass, String conceptualizationOfSpatialRelationships, String distanceMethod, String standardization)
Creates the Cluster and Outlier Analysis (Anselin Local Morans I) tool with the required parameters.

Method Summary

Object	getClusterOutlierType() Returns the Cluster-Outlier Type parameter of this tool (Read only).
String	getConceptualizationOfSpatialRelationships() Returns the Conceptualization of Spatial Relationships parameter of this tool .
double	getDistanceBandOrThresholdDistance() Returns the Distance Band or Threshold Distance parameter of this tool .
String	getDistanceMethod() Returns the Distance Method parameter of this tool .
Object	getIndexFieldName() Returns the Index Field Name parameter of this tool (Read only).
Object	getInputFeatureClass() Returns the Input Feature Class parameter of this tool .
Object	getInputField() Returns the Input Field parameter of this tool .
Object	getOutputFeatureClass() Returns the Output Feature Class parameter of this tool .
Object	getProbabilityField() Returns the Probability Field parameter of this tool (Read only).
String	getStandardization() Returns the Standardization parameter of this tool .
String	getToolboxAlias() Returns the alias of the tool box containing this tool.
String	getToolboxName() Returns the name of the tool box containing this tool.
String	getToolName() Returns the name of this tool.
Object	getWeightsMatrixFile() Returns the Weights Matrix File parameter of this tool .
Object	getZScoreFieldName() Returns the ZScore Field Name parameter of this tool (Read only).
void	setConceptualizationOfSpatialRelationships(String conceptualizationOfSpatialRelationships) Sets the Conceptualization of Spatial Relationships parameter of this tool .
void	setDistanceBandOrThresholdDistance(double distanceBandOrThresholdDistance) Sets the Distance Band or Threshold Distance parameter of this tool .
void	setDistanceMethod(String distanceMethod) Sets the Distance Method parameter of this tool .
void	setInputFeatureClass(Object inputFeatureClass) Sets the Input Feature Class parameter of this tool .
void	setInputField(Object inputField) Sets the Input Field parameter of this tool .
void	setOutputFeatureClass(Object outputFeatureClass) Sets the Output Feature Class parameter of this tool .
void	setStandardization(String standardization) Sets the Standardization parameter of this tool .
void	setWeightsMatrixFile(Object weightsMatrixFile) Sets the Weights Matrix File parameter of this tool .

Methods inherited from class com.esri.arcgis.geoprocessing.AbstractGPTool

getParameterValues, toString

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Constructor Detail

ClustersOutliers

public ClustersOutliers()

Creates the Cluster and Outlier Analysis (Anselin Local Morans I) tool with defaults.

Initializes the array of tool parameters with the default values specified when the tool was created.

ClustersOutliers

public ClustersOutliers(Object inputFeatureClass,
                        Object inputField,
                        Object outputFeatureClass,
                        String conceptualizationOfSpatialRelationships,
                        String distanceMethod,
                        String standardization)

Creates the Cluster and Outlier Analysis (Anselin Local Morans I) tool with the required parameters.

Initializes the array of tool parameters with the values as specified for the required parameters and with the default values for the other parameters.

Parameters:

inputFeatureClass - Feature Layer, the feature class for which cluster/outlier analysis will be performed.

inputField - Field, the numeric field to be evaluated.

outputFeatureClass - Feature Class, the output feature class to receive the results fields.

conceptualizationOfSpatialRelationships - String, specifies how spatial relationships among features are conceptualized.

distanceMethod - String, specifies how distances are calculated when measuring spatial autocorrelation.

standardization - String, row standardization is recommended whenever the distribution of your features is potentially biased due to sampling design or an imposed aggregation scheme.

Method Detail

getInputFeatureClass

public Object getInputFeatureClass()

Returns the Input Feature Class parameter of this tool . This parameter is Feature Layer, the feature class for which cluster/outlier analysis will be performed. This is a required parameter.

Returns:

the Input Feature Class

setInputFeatureClass

public void setInputFeatureClass(Object inputFeatureClass)

Sets the Input Feature Class parameter of this tool . This parameter is Feature Layer, the feature class for which cluster/outlier analysis will be performed. This is a required parameter.

Parameters:

inputFeatureClass - Feature Layer, the feature class for which cluster/outlier analysis will be performed.

getInputField

public Object getInputField()

Returns the Input Field parameter of this tool . This parameter is Field, the numeric field to be evaluated. This is a required parameter.

Returns:

the Input Field

setInputField

public void setInputField(Object inputField)

Sets the Input Field parameter of this tool . This parameter is Field, the numeric field to be evaluated. This is a required parameter.

Parameters:

inputField - Field, the numeric field to be evaluated.

getOutputFeatureClass

public Object getOutputFeatureClass()

Returns the Output Feature Class parameter of this tool . This parameter is Feature Class, the output feature class to receive the results fields. This is a required parameter.

Returns:

the Output Feature Class

setOutputFeatureClass

public void setOutputFeatureClass(Object outputFeatureClass)

Sets the Output Feature Class parameter of this tool . This parameter is Feature Class, the output feature class to receive the results fields. This is a required parameter.

Parameters:

outputFeatureClass - Feature Class, the output feature class to receive the results fields.

getConceptualizationOfSpatialRelationships

public String getConceptualizationOfSpatialRelationships()

Returns the Conceptualization of Spatial Relationships parameter of this tool . This parameter is String, specifies how spatial relationships among features are conceptualized. This is a required parameter.

Returns:

the Conceptualization of Spatial Relationships

setConceptualizationOfSpatialRelationships

public void setConceptualizationOfSpatialRelationships(String conceptualizationOfSpatialRelationships)

Sets the Conceptualization of Spatial Relationships parameter of this tool . This parameter is String, specifies how spatial relationships among features are conceptualized. This is a required parameter.

Parameters:

conceptualizationOfSpatialRelationships - String, specifies how spatial relationships among features are conceptualized.

getDistanceMethod

public String getDistanceMethod()

Returns the Distance Method parameter of this tool . This parameter is String, specifies how distances are calculated when measuring spatial autocorrelation. This is a required parameter.

Returns:

the Distance Method

setDistanceMethod

public void setDistanceMethod(String distanceMethod)

Sets the Distance Method parameter of this tool . This parameter is String, specifies how distances are calculated when measuring spatial autocorrelation. This is a required parameter.

Parameters:

distanceMethod - String, specifies how distances are calculated when measuring spatial autocorrelation.

getStandardization

public String getStandardization()

Returns the Standardization parameter of this tool . This parameter is String, row standardization is recommended whenever the distribution of your features is potentially biased due to sampling design or an imposed aggregation scheme. This is a required parameter.

Returns:

the Standardization

setStandardization

public void setStandardization(String standardization)

Sets the Standardization parameter of this tool . This parameter is String, row standardization is recommended whenever the distribution of your features is potentially biased due to sampling design or an imposed aggregation scheme. This is a required parameter.

Parameters:

standardization - String, row standardization is recommended whenever the distribution of your features is potentially biased due to sampling design or an imposed aggregation scheme.

getDistanceBandOrThresholdDistance

public double getDistanceBandOrThresholdDistance()

Returns the Distance Band or Threshold Distance parameter of this tool . This parameter is Double, specifies a cutoff distance for Inverse Distance and Fixed Distance options. Features outside the specified cutoff for a target feature are ignored in analyses for that feature. However, for Zone of Indifference, the influence of features outside the given distance is reduced with distance while those inside the distance threshold are equally considered. The value entered should match those of the Output Coordinate System. For the Inverse Distance conceptualizations of spatial relationships: A value of zero for this parameter indicates that no threshold distance is applied; when this parameter is left blank, a default threshold value will be computed and applied. This parameter has no effect when "Polygon Contiguity" or "Get Spatial Weights From File" spatial conceptualizations are selected. This is an optional parameter.

Returns:

the Distance Band or Threshold Distance

setDistanceBandOrThresholdDistance

public void setDistanceBandOrThresholdDistance(double distanceBandOrThresholdDistance)

Sets the Distance Band or Threshold Distance parameter of this tool . This parameter is Double, specifies a cutoff distance for Inverse Distance and Fixed Distance options. Features outside the specified cutoff for a target feature are ignored in analyses for that feature. However, for Zone of Indifference, the influence of features outside the given distance is reduced with distance while those inside the distance threshold are equally considered. The value entered should match those of the Output Coordinate System. For the Inverse Distance conceptualizations of spatial relationships: A value of zero for this parameter indicates that no threshold distance is applied; when this parameter is left blank, a default threshold value will be computed and applied. This parameter has no effect when "Polygon Contiguity" or "Get Spatial Weights From File" spatial conceptualizations are selected. This is an optional parameter.

Parameters:

distanceBandOrThresholdDistance - Double, specifies a cutoff distance for Inverse Distance and Fixed Distance options. Features outside the specified cutoff for a target feature are ignored in analyses for that feature. However, for Zone of Indifference, the influence of features outside the given distance is reduced with distance while those inside the distance threshold are equally considered. The value entered should match those of the Output Coordinate System. For the Inverse Distance conceptualizations of spatial relationships: A value of zero for this parameter indicates that no threshold distance is applied; when this parameter is left blank, a default threshold value will be computed and applied. This parameter has no effect when "Polygon Contiguity" or "Get Spatial Weights From File" spatial conceptualizations are selected.

getWeightsMatrixFile

public Object getWeightsMatrixFile()

Returns the Weights Matrix File parameter of this tool . This parameter is File, the pathname to a file containing spatial weights that define spatial relationships between features. This is an optional parameter.

Returns:

the Weights Matrix File

setWeightsMatrixFile

public void setWeightsMatrixFile(Object weightsMatrixFile)

Sets the Weights Matrix File parameter of this tool . This parameter is File, the pathname to a file containing spatial weights that define spatial relationships between features. This is an optional parameter.

Parameters:

weightsMatrixFile - File, the pathname to a file containing spatial weights that define spatial relationships between features.

getIndexFieldName

public Object getIndexFieldName()

Returns the Index Field Name parameter of this tool (Read only). This is an derived parameter.

Returns:

the Index Field Name

getZScoreFieldName

public Object getZScoreFieldName()

Returns the ZScore Field Name parameter of this tool (Read only). This is an derived parameter.

Returns:

the ZScore Field Name

getProbabilityField

public Object getProbabilityField()

Returns the Probability Field parameter of this tool (Read only). This is an derived parameter.

Returns:

the Probability Field

getClusterOutlierType

public Object getClusterOutlierType()

Returns the Cluster-Outlier Type parameter of this tool (Read only). This is an derived parameter.

Returns:

the Cluster-Outlier Type

getToolName

public String getToolName()

Returns the name of this tool.

Returns:

the tool name

getToolboxName

public String getToolboxName()

Returns the name of the tool box containing this tool.

Returns:

the tool box name

getToolboxAlias

public String getToolboxAlias()

Returns the alias of the tool box containing this tool.

Returns:

the tool box alias