com.esri.arcgis.geoprocessing.tools.spatialstatisticstools
Class HighLowClustering
java.lang.Object
com.esri.arcgis.geoprocessing.AbstractGPTool
com.esri.arcgis.geoprocessing.tools.spatialstatisticstools.HighLowClustering
- All Implemented Interfaces:
- GPTool
public class HighLowClustering
- extends AbstractGPTool
Measures the degree of clustering for either high values or low values
The High/Low Clustering (Getis-Ord General G) tool is contained in the Spatial Statistics Tools tool box.
Learn more about how High/Low Clustering: Getis-Ord General G 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 the units associated with 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 General G tool calculates the value of the General G index, associated Z score and p-value for a given input feature class. These values are written to the Command Line message window and passed as derived output.
- The Z score and p-value are measures of statistical significance which tell you whether or not to reject the null hypothesis. For this tool, the null hypothsis states that the values associated with features are randomly distributed.
- 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?;
- The higher (or lower) the Z score; , the stronger the intensity of the clustering. A Z score near zero indicates no apparent clustering within the study area. A positive Z score indicates clustering of high values. A negative Z scores indicates clustering of low values.
- For line and polygon features, true geometric feature centroids are used in computations.
- The input field you select should only contain positive numeric values. The General G statistic was designed to work with non-negative values only.
- 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.
- The "Display Output Graphically" parameter will only work on the Windows operating system. When set to true it will display the results of the tool graphically.
- When output is shown graphically, a separate graphics dialog box will be displayed. If you use the tool in a script, set the Display_Output_Graphically parameter to "false", otherwise your script will not complete until you click"Close" on the popup graphic.
- 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;
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Constructor Summary |
HighLowClustering()
Creates the High/Low Clustering (Getis-Ord General G) tool with defaults. |
HighLowClustering(Object inputFeatureClass,
Object inputField,
String conceptualizationOfSpatialRelationships,
String distanceMethod,
String standardization)
Creates the High/Low Clustering (Getis-Ord General G) tool with the required parameters. |
HighLowClustering
public HighLowClustering()
- Creates the High/Low Clustering (Getis-Ord General G) tool with defaults.
Initializes the array of tool parameters with the default values specified when the tool was created.
HighLowClustering
public HighLowClustering(Object inputFeatureClass,
Object inputField,
String conceptualizationOfSpatialRelationships,
String distanceMethod,
String standardization)
- Creates the High/Low Clustering (Getis-Ord General G) 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 the General G statistic will be calculated.inputField - Field, the numeric field used for analysis (incidents or weights).conceptualizationOfSpatialRelationships - String, specifies how spatial relationships among features are conceptualized.distanceMethod - String, specifies how feature to feature distance are calculated.standardization - String, row standardization is recommended whenever the distribution of your features is potentially biased due to sampling design or an imposed aggregation scheme.
getInputFeatureClass
public Object getInputFeatureClass()
- Returns the Input Feature Class parameter of this tool .
This parameter is Feature Layer, the feature class for which the General G statistic will be calculated.
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 the General G statistic will be calculated.
This is a required parameter.
- Parameters:
inputFeatureClass - Feature Layer, the feature class for which the General G statistic will be calculated.
getInputField
public Object getInputField()
- Returns the Input Field parameter of this tool .
This parameter is Field, the numeric field used for analysis (incidents or weights).
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 used for analysis (incidents or weights).
This is a required parameter.
- Parameters:
inputField - Field, the numeric field used for analysis (incidents or weights).
getDisplayOutputGraphically
public String getDisplayOutputGraphically()
- Returns the Display Output Graphically parameter of this tool .
This parameter is String, specifies whether the tool will display General G results graphically.
This is an optional parameter.
- Returns:
- the Display Output Graphically
setDisplayOutputGraphically
public void setDisplayOutputGraphically(String displayOutputGraphically)
- Sets the Display Output Graphically parameter of this tool .
This parameter is String, specifies whether the tool will display General G results graphically.
This is an optional parameter.
- Parameters:
displayOutputGraphically - String, specifies whether the tool will display General G results graphically.
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 feature to feature distance are calculated.
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 feature to feature distance are calculated.
This is a required parameter.
- Parameters:
distanceMethod - String, specifies how feature to feature distance are calculated.
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 be in units that 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 be in units that 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 be in units that 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 among features in the Input Feature Class.
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 among features in the Input Feature Class.
This is an optional parameter.
- Parameters:
weightsMatrixFile - File, the pathname to a file containing spatial weights that define spatial relationships among features in the Input Feature Class.
getObservedGeneralG
public double getObservedGeneralG()
- Returns the Observed General G parameter of this tool (Read only).
This is an derived parameter.
- Returns:
- the Observed General G
getZScore
public double getZScore()
- Returns the ZScore parameter of this tool (Read only).
This is an derived parameter.
- Returns:
- the ZScore
getPValue
public double getPValue()
- Returns the PValue parameter of this tool (Read only).
This is an derived parameter.
- Returns:
- the PValue
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