Calculates a nearest neighbor index based on the average distance from each feature to its nearest neighboring feature.
Learn more about how Average Nearest Neighbor Distance works
The nearest neighbor index is expressed as the ratio of the observed distance divided by the expected distance. The expected distance is the average distance between neighbors in a hypothetical random distribution. If the index is less than 1, the pattern exhibits clustering; if the index is greater than 1, the trend is toward dispersion or competition.
The Z score value is a measure of statistical significance which tells us whether or not to reject the null hypothesis. In this case the null hypothsis states that the points are randomly distributed. In this tool, the Z Score is based on Randomization Null Hypothesis computation. For more information on Z Scores, see What is a Z Score?.
If an area value is not specified, then the area of the minimum enclosing rectangle around the features is used. The nearest neighbor function is very sensitive to the area value (small changes in the area can result in considerable changes in the results).
The units of the area parameter are the input feature class' coordinate system's units squared.
Although this tool will work with polygon or line data, it is really only appropriate for event, incident, or other fixedpoint feature data. For line and polygon features, feature centroids are used in the computations.
When output is shown graphically, a separate graphics dialog box will be displayed. Therefore, the output should not be displayed graphically (set display_output_graphically to FALSE) in batch operations.
When using the tool in scripting, use "false" for the Display Output Graphically parameter. If you do not select false, the popup graphic will appear and your script will not complete until you click"Close".
The nearest neighbor index and associated Z score values are written to the command window and passed as derived output.
Calculations are based on either Euclidean or Manhattan distance and require projected data to accurately measure distances.
Current map layers may be used to define the input feature class. When using layers, only the currently selected features are used.
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.
The environment settings do not have an effect on this tool.
Parameter  Explanation  Datatype 

Input Feature Class (Required) 
The point feature class for which the average nearest neighbor distance will be calculated.

Feature Layer 
Distance Method (Required) 
Specifies how distances are calculated in the nearest neighbor calculation.

String 
Display Output Graphically (Required) 
Specifies whether the tool will display the nearest neighbor index graphically.

Boolean 
Area (Optional) 
The area of the nearest neighbor analysis. The default area value is the area of the minimum enclosing rectangle. The units of this parameter are the input feature class' coordinate system's units squared.

Double 
# Analyze crime data to determine if spatial patterns are statistically significant # Import system modules import arcgisscripting # Create the Geoprocessor object gp = arcgisscripting.create() # Local variables... workspace = "C:/project93/data" crime_data = "burglaries.shp" try: # Set the current workspace (to avoid having to specify the full path to the feature classes each time) gp.workspace = workspace # Obtain Nearest Neighbor Ratio and Z Score # Process: Average Nearest Neighbor... nn_output = gp.AverageNearestNeighbor_stats(crime_data, "Euclidean Distance", "false", "#") nn_values = nn_output.split(";") print "The nearest neighbor index is: " + nn_values[0] print "The z score of the nearest neighbor index is: " + nn_values[1] except: # If an error occurred when running the tool, print out the error message. print gp.GetMessages()