com.esri.arcgis.geoprocessing.tools.spatialstatisticstools
Class HotSpots
java.lang.Object
com.esri.arcgis.geoprocessing.AbstractGPTool
com.esri.arcgis.geoprocessing.tools.spatialstatisticstools.HotSpots
- All Implemented Interfaces:
- GPTool
public class HotSpots
- extends AbstractGPTool
The Hot Spot Analysis (Getis-Ord Gi*) tool is contained in the Spatial Statistics Tools tool box.
Usage tips:
- This tool identifies statistically significant spatial clusters of high values (hot spots) and low values (cold spots). Itcreates a new Output Feature Class with a Z score and p-value for each feature in the Input Feature Class. It also returns the Z score and p-valueu field names as derived output values.
- 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. In effect, they indicate whether the observed spatial clustering of high or low values is more pronounced than one would expect in a random distribution of those same values.
- A high Z score and small p-value for a feature indicates a spatial clustering of high values. A low negative Z score and small p-value indicates a spatial clustering of low values. The higher (or lower) the Z score, the more intense the clustering. A Z score near zero indicates no apparent spatial clustering.
- The Z score is based on the Randomization Null Hypothesis computation. For more information on Z scores, see .
- Calculations based on either Euclidean or Manhattan distance require to accurately measure distances.
- For line and polygon features, feature true geometric centroids are used in distance computations. For multipoint, polyline or polygons with multiple parts, the centroid is computed using the weighted mean center of all feature parts. The weighting for point features is 1, for line features is length, and for polygon features is area.
- 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 prior to analysis in order improve performance.
- Map layers may be used to define the Input Feature Class. When using layers, only the selected features are included in the analysis.
- 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 want to use this tool to analyze the spatial pattern of incident data, consider .
- This tool computes the Gi* statistic where each feature is its own neighbor; however, if you specify a Self Potential field in which all values are zero, the tool performs the Gi statistic (local calculations for a feature exclude the feature's own value).
- Your choice for the Conceptualization of Spatial Relationships parameter should reflect inherent relationships among the features you are analyzing. The more realistically you can model how features interact with each other in space, the more accurate your results will be. . Here are some additional tips:
- Fixed Distance Band
- Inverse Distance or Inverse Distance Squared
- 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 the template layer symbology.
- The help topic provides additional information about this tool's parameters.
- 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.
- 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.
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Constructor Summary |
HotSpots()
Creates the Hot Spot Analysis (Getis-Ord Gi*) tool with defaults. |
HotSpots(java.lang.Object inputFeatureClass,
java.lang.Object inputField,
java.lang.Object outputFeatureClass,
java.lang.String conceptualizationOfSpatialRelationships,
java.lang.String distanceMethod,
java.lang.String standardization)
Creates the Hot Spot Analysis (Getis-Ord Gi*) tool with the required parameters. |
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Method Summary |
java.lang.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 . |
java.lang.String |
getDistanceMethod()
Returns the Distance Method parameter of this tool . |
java.lang.Object |
getInputFeatureClass()
Returns the Input Feature Class parameter of this tool . |
java.lang.Object |
getInputField()
Returns the Input Field parameter of this tool . |
java.lang.Object |
getOutputFeatureClass()
Returns the Output Feature Class parameter of this tool . |
java.lang.Object |
getProbabilityField()
Returns the Probability Field parameter of this tool (Read only). |
java.lang.Object |
getResultsField()
Returns the Results Field parameter of this tool (Read only). |
java.lang.Object |
getSelfPotentialField()
Returns the Self Potential Field parameter of this tool . |
java.lang.String |
getStandardization()
Returns the Standardization parameter of this tool . |
java.lang.String |
getToolboxAlias()
Returns the alias of the tool box containing this tool. |
java.lang.String |
getToolboxName()
Returns the name of the tool box containing this tool. |
java.lang.String |
getToolName()
Returns the name of this tool. |
java.lang.Object |
getWeightsMatrixFile()
Returns the Weights Matrix File parameter of this tool . |
void |
setConceptualizationOfSpatialRelationships(java.lang.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(java.lang.String distanceMethod)
Sets the Distance Method parameter of this tool . |
void |
setInputFeatureClass(java.lang.Object inputFeatureClass)
Sets the Input Feature Class parameter of this tool . |
void |
setInputField(java.lang.Object inputField)
Sets the Input Field parameter of this tool . |
void |
setOutputFeatureClass(java.lang.Object outputFeatureClass)
Sets the Output Feature Class parameter of this tool . |
void |
setSelfPotentialField(java.lang.Object selfPotentialField)
Sets the Self Potential Field parameter of this tool . |
void |
setStandardization(java.lang.String standardization)
Sets the Standardization parameter of this tool . |
void |
setWeightsMatrixFile(java.lang.Object weightsMatrixFile)
Sets the Weights Matrix File parameter of this tool . |
| Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
HotSpots
public HotSpots()
- Creates the Hot Spot Analysis (Getis-Ord Gi*) tool with defaults.
Initializes the array of tool parameters with the default values specified when the tool was created.
HotSpots
public HotSpots(java.lang.Object inputFeatureClass,
java.lang.Object inputField,
java.lang.Object outputFeatureClass,
java.lang.String conceptualizationOfSpatialRelationships,
java.lang.String distanceMethod,
java.lang.String standardization)
- Creates the Hot Spot Analysis (Getis-Ord Gi*) 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 - the feature class for which hot spot analysis will be performed.inputField - the numeric count field (number of victims, crimes, jobs, and so on) to be evaluated.outputFeatureClass - the output feature class to receive the Results field and Gi z score.conceptualizationOfSpatialRelationships - specifies how spatial relationships among features are conceptualized.distanceMethod - specifies how distances are calculated from each feature to its nearest neighboring feature.standardization - row standardization is recommended whenever the distribution of your features is potentially biased due to sampling design or an imposed aggregation scheme.
getInputFeatureClass
public java.lang.Object getInputFeatureClass()
- Returns the Input Feature Class parameter of this tool .
This parameter is the feature class for which hot spot analysis will be performed.
This is a required parameter.
- Returns:
- the Input Feature Class
setInputFeatureClass
public void setInputFeatureClass(java.lang.Object inputFeatureClass)
- Sets the Input Feature Class parameter of this tool .
This parameter is the feature class for which hot spot analysis will be performed.
This is a required parameter.
- Parameters:
inputFeatureClass - the feature class for which hot spot analysis will be performed.
getInputField
public java.lang.Object getInputField()
- Returns the Input Field parameter of this tool .
This parameter is the numeric count field (number of victims, crimes, jobs, and so on) to be evaluated.
This is a required parameter.
- Returns:
- the Input Field
setInputField
public void setInputField(java.lang.Object inputField)
- Sets the Input Field parameter of this tool .
This parameter is the numeric count field (number of victims, crimes, jobs, and so on) to be evaluated.
This is a required parameter.
- Parameters:
inputField - the numeric count field (number of victims, crimes, jobs, and so on) to be evaluated.
getOutputFeatureClass
public java.lang.Object getOutputFeatureClass()
- Returns the Output Feature Class parameter of this tool .
This parameter is the output feature class to receive the Results field and Gi z score.
This is a required parameter.
- Returns:
- the Output Feature Class
setOutputFeatureClass
public void setOutputFeatureClass(java.lang.Object outputFeatureClass)
- Sets the Output Feature Class parameter of this tool .
This parameter is the output feature class to receive the Results field and Gi z score.
This is a required parameter.
- Parameters:
outputFeatureClass - the output feature class to receive the Results field and Gi z score.
getConceptualizationOfSpatialRelationships
public java.lang.String getConceptualizationOfSpatialRelationships()
- Returns the Conceptualization of Spatial Relationships parameter of this tool .
This parameter is specifies how spatial relationships among features are conceptualized.
This is a required parameter.
- Returns:
- the Conceptualization of Spatial Relationships
setConceptualizationOfSpatialRelationships
public void setConceptualizationOfSpatialRelationships(java.lang.String conceptualizationOfSpatialRelationships)
- Sets the Conceptualization of Spatial Relationships parameter of this tool .
This parameter is specifies how spatial relationships among features are conceptualized.
This is a required parameter.
- Parameters:
conceptualizationOfSpatialRelationships - specifies how spatial relationships among features are conceptualized.
getDistanceMethod
public java.lang.String getDistanceMethod()
- Returns the Distance Method parameter of this tool .
This parameter is specifies how distances are calculated from each feature to its nearest neighboring feature.
This is a required parameter.
- Returns:
- the Distance Method
setDistanceMethod
public void setDistanceMethod(java.lang.String distanceMethod)
- Sets the Distance Method parameter of this tool .
This parameter is specifies how distances are calculated from each feature to its nearest neighboring feature.
This is a required parameter.
- Parameters:
distanceMethod - specifies how distances are calculated from each feature to its nearest neighboring feature.
getStandardization
public java.lang.String getStandardization()
- Returns the Standardization parameter of this tool .
This parameter is 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(java.lang.String standardization)
- Sets the Standardization parameter of this tool .
This parameter is 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 - 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 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 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 - 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.
getSelfPotentialField
public java.lang.Object getSelfPotentialField()
- Returns the Self Potential Field parameter of this tool .
This parameter is the field representing self-potential: The distance or weight between a feature and itself.
This is an optional parameter.
- Returns:
- the Self Potential Field
setSelfPotentialField
public void setSelfPotentialField(java.lang.Object selfPotentialField)
- Sets the Self Potential Field parameter of this tool .
This parameter is the field representing self-potential: The distance or weight between a feature and itself.
This is an optional parameter.
- Parameters:
selfPotentialField - the field representing self-potential: The distance or weight between a feature and itself.
getWeightsMatrixFile
public java.lang.Object getWeightsMatrixFile()
- Returns the Weights Matrix File parameter of this tool .
This parameter is 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(java.lang.Object weightsMatrixFile)
- Sets the Weights Matrix File parameter of this tool .
This parameter is the pathname to a file containing spatial weights that define spatial relationships between features.
This is an optional parameter.
- Parameters:
weightsMatrixFile - the pathname to a file containing spatial weights that define spatial relationships between features.
getResultsField
public java.lang.Object getResultsField()
- Returns the Results Field parameter of this tool (Read only).
This is an derived parameter.
- Returns:
- the Results Field
getProbabilityField
public java.lang.Object getProbabilityField()
- Returns the Probability Field parameter of this tool (Read only).
This is an derived parameter.
- Returns:
- the Probability Field
getToolName
public java.lang.String getToolName()
- Returns the name of this tool.
- Returns:
- the tool name
getToolboxName
public java.lang.String getToolboxName()
- Returns the name of the tool box containing this tool.
- Returns:
- the tool box name
getToolboxAlias
public java.lang.String getToolboxAlias()
- Returns the alias of the tool box containing this tool.
- Returns:
- the tool box alias