Generate Network Spatial Weights (Spatial Statistics)

Available with Network Analyst license.

Summary

Constructs a spatial weights matrix file (.swm) using a Network dataset, defining feature spatial relationships in terms of the underlying network structure.

Legacy:

This is a deprecated tool. A new tool has been created with enhancements and new functionality including accepting networks from portal services. See the updated Generate Network Spatial Weights Matrix tool.

Illustration

Generate Network Spatial Weights illustration

Usage

  • Output from this tool is a spatial weights matrix file (.swm). Tools that require you to specify a Conceptualization of Spatial Relationships option will accept a spatial weights matrix file; select GET_SPATIAL_WEIGHTS_FROM_FILE for the Conceptualization of Spatial Relationships parameter and, for the Weights Matrix File parameter, specify the full path to the spatial weights file created using this tool.

  • This tool is designed to work with point Input Feature Class data only.

  • A spatial weights matrix quantifies the spatial relationships that exist among the features in your dataset. Many tools in the Spatial Statistics toolbox evaluate each feature within the context of its neighboring features. The spatial weights matrix file defines those neighbor relationships. For this tool, neighbor relationships are based on the time or distance between features, in the case where travel is restricted to a network. For more information about spatial weights and spatial weights matrix files, see Spatial weights.

  • Tip:

    Many organizations maintain their own street network datasets that you may already have access to. As an alternative, Street Map Premium for ArcGIS includes prebuilt network datasets in SDC format that include North America, Latin America, Europe, the Middle East Africa, Japan, Australia, and New Zealand. These network datasets can be used directly by this tool.

  • The Unique ID field is linked to feature relationships derived from running this tool. Consequently, the Unique ID values must be unique for every feature and typically should be in a permanent field that remains with the feature class. If you don't have a unique ID field, you can create one by adding a new integer field (Add Field) to your feature class table and calculating the field values to be equal to the FID or OBJECTID field (Calculate Field). Because the FID and OBJECTID field values may change when you copy or edit a feature class, you cannot use these fields directly for the Unique ID parameter.

  • The Maximum Number of Neighbors parameter specifies the exact number of neighbors that will be associated with each feature. The Impedance Cutoff overrides the number of neighbors parameter, so some features may have fewer neighbors if the number of neighbors specified cannot be found within the cutoff distance or time.

  • You can define spatial relationships using the hierarchy in the network dataset, if it has one, using the Use Hierarchy in Analysis parameter. The hierarchy classifies network edges into primary, secondary, and local roads. When using the hierarchy of the network to create spatial relationships among features, preference will be given to travel on primary roads more than secondary roads and secondary roads more than local roads.

  • If you are using prebuilt network datasets from Street Map Premium for ArcGIS that use a travel mode, some parameter options may be prepopulated and cannot be changed.

  • This tool does not honor the output coordinate system environment setting. All feature geometry is projected to match the spatial reference associated with the network dataset prior to analysis. The resultant spatial weights matrix file created by this tool will reflect spatial relationships defined using the Network Dataset spatial reference. It is recommended that when performing analyses using a network spatial weights matrix file, the input feature class be projected to match the coordinate system of the network dataset used to create the network SWM.

  • Caution:

    When using shapefiles, keep in mind that they cannot store null values. Tools or other procedures that create shapefiles from nonshapefile inputs may store or interpret null values as zero. In some cases, nulls are stored as very large negative values in shapefiles. This can lead to unexpected results. See Geoprocessing considerations for shapefile output for more information.

Parameters

LabelExplanationData Type
Input Feature Class

The point feature class for which network spatial relationships among features will be assessed.

Feature Class
Unique ID Field

An integer field containing a different value for every feature in the input feature class. If you don't have a Unique ID field, you can create one by adding an integer field to your feature class table and calculating the field values to equal the FID or OBJECTID field.

Field
Output Spatial Weights Matrix File

The output network spatial weights matrix (.swm) file.

File
Input Network

The network dataset for which spatial relationships among features in the input feature class will be defined. Network datasets most often represent street networks but may represent other kinds of transportation networks as well. The network dataset needs at least one time-based and one distance-based cost attribute.

Network Dataset Layer
Impedance Attribute

The type of cost units to use as impedance in the analysis.

String
Impedance Cutoff
(Optional)

Specifies a cutoff value for Inverse and Fixed conceptualizations of spatial relationships. Enter this value using the units specified by the Impedance Attribute parameter.

A value of zero indicates that no threshold is applied. When this parameter is left blank, a default threshold value is computed based on input feature class extent and the number of features.

Double
Maximum Number of Neighbors
(Optional)

An integer reflecting the maximum number of neighbors to find for each feature.

Long
Barriers
(Optional)

The name of a point feature class with features representing blocked intersections, road closures, accident sites, or other locations where travel is blocked along the network.

Feature Layer
U-turn Policy
(Optional)

Specifies optional U-turn restrictions.

  • Allow U-turns — U-turns will be allowed anywhere. This is the default.
  • No U-turns — No U-turns will be allowed during navigation.
  • Allow U-turns at dead ends only — U-turns will be allowed only at dead ends (that is, single-valent junctions).
  • Allow U-turns at dead ends and intersections only —U-turns will be allowed only at dead ends and intersections.
String
Restrictions
(Optional)

A list of restrictions. Check the restrictions to be honored in spatial relationship computations.

String
Use Hierarchy in Analysis
(Optional)

Specifies whether to use a hierarchy in the analysis.

  • Checked—The network dataset's hierarchy attribute will be used in a heuristic path algorithm to speed analysis.
  • Unchecked—An exact path algorithm will be used instead. If there is no hierarchy attribute, this option does not affect analysis.
Boolean
Search Tolerance
(Optional)

The search threshold used to locate features in the Input Feature Class onto the network dataset. This parameter includes a search value and the units for the tolerance.

Linear Unit
Conceptualization of Spatial Relationships
(Optional)

Specifies how the weighting associated with each spatial relationship is specified.

  • Inverse — Features farther away have a smaller weight than features nearby.
  • Fixed — Features within the Impedance Cutoff are neighbors (weight of 1); features outside the Impedance Cutoff are not weighted (weight of 0).
String
Exponent
(Optional)

Parameter for the Inverse Conceptualization of Spatial Relationships calculation. Typical values are 1 or 2. Weights drop off quicker with distance as this exponent value increases.

Double
Row Standardization
(Optional)

Specifies whether row standardization is applied. Row standardization is recommended whenever feature distribution is potentially biased due to sampling design or to an imposed aggregation scheme.

  • Checked—Spatial weights are standardized by row. Each weight is divided by its row sum.
  • Unchecked—No standardization of spatial weights is applied.
Boolean
Travel Mode
(Optional)

The mode of transportation for the analysis. Custom is always a choice. For other travel modes to appear, they must be present in the network dataset specified in the Network Dataset parameter.

A travel mode is defined on a network dataset and provides override values for parameters that model car, truck, pedestrian, or other modes of travel.

String
Time of Day
(Optional)

Specifies whether travel times should consider traffic conditions. Especially in urbanized areas, traffic conditions can significantly impact the area covered within a specified travel time. If no date or time is specified, the distance covered during a specified travel time will not be impacted by traffic.

Date

arcpy.stats.GenerateNetworkSpatialWeights(Input_Feature_Class, Unique_ID_Field, Output_Spatial_Weights_Matrix_File, Input_Network, Impedance_Attribute, {Impedance_Cutoff}, {Maximum_Number_of_Neighbors}, {Barriers}, {U-turn_Policy}, {Restrictions}, {Use_Hierarchy_in_Analysis}, {Search_Tolerance}, {Conceptualization_of_Spatial_Relationships}, {Exponent}, {Row_Standardization}, {Travel_Mode}, {Time_of_Day})
NameExplanationData Type
Input_Feature_Class

The point feature class for which network spatial relationships among features will be assessed.

Feature Class
Unique_ID_Field

An integer field containing a different value for every feature in the input feature class. If you don't have a Unique ID field, you can create one by adding an integer field to your feature class table and calculating the field values to equal the FID or OBJECTID field.

Field
Output_Spatial_Weights_Matrix_File

The output network spatial weights matrix (.swm) file.

File
Input_Network

The network dataset for which spatial relationships among features in the input feature class will be defined. Network datasets most often represent street networks but may represent other kinds of transportation networks as well. The network dataset needs at least one time-based and one distance-based cost attribute.

Network Dataset Layer
Impedance_Attribute

The type of cost units to use as impedance in the analysis.

String
Impedance_Cutoff
(Optional)

Specifies a cutoff value for INVERSE and FIXED conceptualizations of spatial relationships. Enter this value using the units specified by the Impedance_Attribute parameter.

A value of zero indicates that no threshold is applied. When this parameter is left blank, a default threshold value is computed based on input feature class extent and the number of features.

Double
Maximum_Number_of_Neighbors
(Optional)

An integer reflecting the maximum number of neighbors to find for each feature.

Long
Barriers
(Optional)

The name of a point feature class with features representing blocked intersections, road closures, accident sites, or other locations where travel is blocked along the network.

Feature Layer
U-turn_Policy
(Optional)

Specifies optional U-turn restrictions.

  • ALLOW_UTURNSU-turns will be allowed anywhere. This is the default.
  • NO_UTURNSNo U-turns will be allowed during navigation.
  • ALLOW_DEAD_ENDS_ONLYU-turns will be allowed only at dead ends (that is, single-valent junctions).
  • ALLOW_DEAD_ENDS_AND_INTERSECTIONS_ONLYU-turns will be allowed only at dead ends and intersections.
String
Restrictions
[Restriction,...]
(Optional)

A list of restrictions. Check the restrictions to be honored in spatial relationship computations.

String
Use_Hierarchy_in_Analysis
(Optional)

Specifies whether to use a hierarchy in the analysis.

  • USE_HIERARCHYThe network dataset's hierarchy attribute will be used in a heuristic path algorithm to speed analysis.
  • NO_HIERARCHYAn exact path algorithm will be used instead. If there is no hierarchy attribute, this option does not affect analysis.
Boolean
Search_Tolerance
(Optional)

The search threshold used to locate features in the Input_Feature_Class onto the network dataset. This parameter includes a search value and the units for the tolerance.

Linear Unit
Conceptualization_of_Spatial_Relationships
(Optional)

Specifies how the weighting associated with each spatial relationship is specified.

  • INVERSEFeatures farther away have a smaller weight than features nearby.
  • FIXEDFeatures within the Impendance_Cutoff are neighbors (weight of 1); features outside the Impendance_Cutoff are not weighted (weight of 0).
String
Exponent
(Optional)

Parameter for the INVERSE Conceptualization_of_Spatial_Relationships calculation. Typical values are 1 or 2. Weights drop off quicker with distance as this exponent value increases.

Double
Row_Standardization
(Optional)

Specifies whether row standardization is applied. Row standardization is recommended whenever feature distribution is potentially biased due to sampling design or to an imposed aggregation scheme.

  • ROW_STANDARDIZATIONSpatial weights are standardized by row. Each weight is divided by its row sum.
  • NO_STANDARDIZATIONNo standardization of spatial weights is applied.
Boolean
Travel_Mode
(Optional)

The mode of transportation for the analysis. Custom is always a choice. For other travel modes to appear, they must be present in the network dataset specified in the Network Dataset parameter.

A travel mode is defined on a network dataset and provides override values for parameters that model car, truck, pedestrian, or other modes of travel.

String
Time_of_Day
(Optional)

Specifies whether travel times should consider traffic conditions. Especially in urbanized areas, traffic conditions can significantly impact the area covered within a specified travel time. If no date or time is specified, the distance covered during a specified travel time will not be impacted by traffic.

Date

Code sample

GenerateNetworkSpatialWeights example 1 (Python window)

The following Python window script demonstrates how to use the GenerateNetworkSpatialWeights tool.

import arcpy
arcpy.env.workspace = "c:/data"
arpcy.GenerateNetworkSpatialWeights_stats("Hospital.shp", "MyID",
                                          "network6Neighs.swm", "Streets_ND",
                                          "MINUTES", 10, 6, "#", "ALLOW_UTURNS",
                                          "#", "USE_HIERARCHY", "#", "INVERSE", 
                                          1, "ROW_STANDARDIZATION")
GenerateNetworkSpatialWeights example 2 (stand-alone script)

The following stand-alone Python script demonstrates how to use the GenerateNetworkSpatialWeights tool.

# Create a Spatial Weights Matrix based on Network Data 

# Import system modules
import arcpy

# Set the environment property to overwrite existing output
arcpy.env.overwriteOutput = True

# Check out the ArcGIS Network Analyst extension (required for the Generate Network Spatial Weights tool)
arcpy.CheckOutExtension("Network")

# Local variables...
workspace = r"C:\Data"

try:
    # Set the current workspace (to avoid having to specify the full path to 
    # the feature classes each time)
    arcpy.env.workspace = workspace

    # Create Spatial Weights Matrix based on Network Data 
    # Process: Generate Network Spatial Weights... 
    nwm = arcpy.GenerateNetworkSpatialWeights_stats("Hospital.shp", "MyID",
                        "network6Neighs.swm", "Streets_ND",
                        "MINUTES", 10, 6, "#", "ALLOW_UTURNS",
                        "#", "USE_HIERARCHY", "#", "INVERSE",
                        1, "ROW_STANDARDIZATION")

    # Create Spatial Weights Matrix based on Euclidean Distance
    # Process: Generate Spatial Weights Matrix... 
    swm = arcpy.GenerateSpatialWeightsMatrix_stats("Hospital.shp", "MYID",
                        "euclidean6Neighs.swm",
                        "K_NEAREST_NEIGHBORS",
                        "#", "#", "#", 6) 

    # Calculate Moran's Index of Spatial Autocorrelation for 
    # average hospital visit times using Network Spatial Weights 
    # Process: Spatial Autocorrelation (Morans I)...       
    moransINet = arcpy.SpatialAutocorrelation_stats("Hospital.shp", "VisitTime",
                        "NO_REPORT", "GET_SPATIAL_WEIGHTS_FROM_FILE", 
                        "EUCLIDEAN_DISTANCE", "NONE", "#", 
                        "network6Neighs.swm")

    # Calculate Moran's Index of Spatial Autocorrelation for 
    # average hospital visit times using Euclidean Spatial Weights   
    # Process: Spatial Autocorrelation (Morans I)...       
    moransIEuc = arcpy.SpatialAutocorrelation_stats("Hospital.shp", "VisitTime",
                        "NO_REPORT", "GET_SPATIAL_WEIGHTS_FROM_FILE", 
                        "EUCLIDEAN_DISTANCE", "NONE", "#", 
                        "euclidean6Neighs.swm")

except:
    # If an error occurred when running the tool, print out the error message.
    print arcpy.GetMessages()

Licensing information

  • Basic: Requires Network Analyst
  • Standard: Requires Network Analyst
  • Advanced: Requires Network Analyst