Standard Distance (Spatial Statistics)

Measures the degree to which features are concentrated or dispersed around the geometric mean center.

Learn about how Standard Distance works


Standard Distance illustration

Usage tips


StandardDistance_stats (Input_Feature_Class, Output_Standard_Distance_Feature_Class, Circle_Size, Weight_Field, Case_Field)
Parameter Explanation Datatype
Input Feature Class (Required)

A feature class containing a distribution of features for which the standard distance will be calculated.

Feature Layer
Output Standard Distance Feature Class (Required)

A polygon feature class that will contain a circle polygon for each input center. These circle polygons graphically portray the standard distance at each center point.

Feature Class
Circle Size (Required)

The size of output circles in standard deviations. The default circle size is 1; valid choices are 1, 2, or 3 standard deviations.

Weight Field (Optional)

The numeric field used to weight locations according to their relative importance.

Case Field (Optional)

Field used to group features for separate standard distance calculations. The case field can be of numeric, date, or string type.

Data types for geoprocessing tool parameters

Script Example

# Measure the geographic distribution of auto thefts

# Import system modules
import arcgisscripting

# Create the Geoprocessor object
gp = arcgisscripting.create()

# Local variables...
workspace = "C:/chris/data/"
auto_theft_locations = "AutoTheft.shp"
auto_theft_links = "AutoTheft_links.shp"
auto_theft_sd = "auto_theft_SD.shp"
auto_theft_se = "auto_theft_SE.shp"
auto_theft_ldm = "auto_theft_LDM.shp"

    # Set the workspace (to avoid having to type in the full path to the data every time)
    gp.Workspace = workspace

    # Process: Standard Distance of auto theft locations...
gp.StandardDistance_stats(auto_theft_locations, auto_theft_sd, "1 Standard Deviation", "#", "#") # Process: Directional Distribution (Standard Deviational Ellipse) of auto theft locations... gp.DirectionalDistribution_stats(auto_theft_locations, auto_theft_se, "1 Standard Deviation", "#", "#") # Process: Linear Directional Mean of auto thefts... gp.DirectionalMean_stats(auto_theft_links, auto_theft_ldm, "false", "#") except: # If an error occurred while running a tool, print the messages print gp.GetMessages()

See Also

  • Directional Distribution (Standard Deviational Ellipse) (Spatial Statistics)
  • Mean Center (Spatial Statistics)
  • Central Feature (Spatial Statistics)