Central Feature (Spatial Statistics)

Identifies the most centrally located feature in a point, line, or polygon feature class.

Learn more about how Central Feature works


Central Feature illustration

Usage tips


CentralFeature_stats (Input_Feature_Class, Output_Feature_Class, Distance_Method, Weight_Field, Self_Potential_Weight_Field, Case_Field)
Parameter Explanation Datatype
Input Feature Class (Required)

The feature class containing a distribution of features from which to identify the most centrally located feature.

Feature Layer
Output Feature Class (Required)

The feature class that will contain the most centrally located feature in the input feature class.

Feature Class
Distance Method (Required)

Specifies how distances are calculated when measuring concentrations.

  • Euclidean (as the crow flies)—The straight-line distance between two points.
  • Manhattan (city block)—The distance between two points measured along axes at right angles. Calculated by summing the (absolute) differences between point coordinates.

Weight Field (Optional)

The numeric field used to weight distances in the origin-destination distance matrix.

Self Potential Weight Field (Optional)

The field representing self-potential—The distance or weight between a feature and itself.

Case Field (Optional)

Field used to group features for separate central feature computations. The case field can be of numeric, date, or string type.

Data types for geoprocessing tool parameters

Script Example

# Measure geographic distribution characteristics of coffee house locations weighted by the number of employees

# Import system modules
import arcgisscripting

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

# Local variables...
workspace = "C:/data"
input_FC = "coffee_shops.shp"
CF_output = "coffee_CF.shp"
MC_output = "coffee_MC.shp"
weight_field = "NUM_EMP"

    # Set the workspace to avoid having to type out full path names
    gp.workspace = workspace

    # Process: Central Feature...
    gp.CentralFeature_stats(input_FC, CF_output, "Euclidean Distance", weight_field, "#", "#")

    # Process: Mean Center...
    gp.MeanCenter_stats(input_FC, MC_output, weight_field, "#", "#")

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

See Also

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