Directional Distribution (Standard Deviational Ellipse) (Räumliche Statistiken)

Zusammenfassung

Creates standard deviational ellipses to summarize the spatial characteristics of geographic features: central tendency, dispersion, and directional trends.

Learn about how Directional Distribution (Standard Deviational Ellipse) works

Abbildung

Verwendung

• The Standard Deviational Ellipse tool creates a new Output Feature Class containing elliptical polygons, one for each Case (Case Field parameter). The attribute values for these ellipse polygons include X and Y coordinates for the mean center, two standard distances (long and short axes), and the orientation of the ellipse. The fieldnames are CenterX, CenterY, XStdDist, YStdDist, and Rotation. When a Case Field is provided, this field is added to the Output Feature Class, as well.

• Für Berechnungen, die auf der euklidischen Entfernung oder der Manhattan-Distanz basieren, sind zur genauen Messung von Entfernungen projizierte Daten erforderlich.

• When the underlying spatial pattern of features is concentrated in the center with fewer features toward the periphery (a spatial normal distribution), a one standard deviation ellipse polygon will cover approximately 68 percent of the features; two standard deviations will contain approximately 95 percent of the features; and three standard deviations will cover approximately 99 percent of the features in the cluster.

• The value in the output Rotation field represents the rotation of the long axis measured clockwise from noon.

• The Case Field is used to group features prior to analysis. When a Case Field is specified, the input features are first grouped according to case field values, and then a standard deviational ellipse is computed for each group. The case field can be of integer, date, or string type.

• The standard deviational ellipse calculation may be based on an optional Weight Field (to get the ellipses for traffic accidents weighted by severity, for example). The Weight Field should be numeric.

• Für Linien- und Polygon-Features werden bei Entfernungsberechnungen Feature-Schwerpunkte verwendet. Für Multipoints, Polylinien oder Polygone mit mehreren Teilen wird der Schwerpunkt mithilfe des gewichteten arithmetischen Mittelpunkts aller Feature-Teile berechnet. Die Gewichtung für Punkt-Features ist 1, für Linien-Features "Länge" und für Polygon-Features "Fläche".

• Sie können Karten-Layer verwenden, um die Eingabe-Feature-Class zu definieren. Beim Verwenden eines Layers mit einer Auswahl sind nur die ausgewählten Features in der Analyse enthalten.

Vorsicht:

Denken Sie beim Verwenden von Shapefiles daran, dass diese keine Nullwerte speichern können. Werkzeuge oder andere Verfahren, die Shapefiles aus Nicht-Shapefile-Eingaben erstellen, speichern bzw. interpretieren Nullwerte ggf. als Wert 0. Dies kann zu unerwarteten Ergebnissen führen. Weitere Informationen finden Sie unter Überlegungen zur Geoverarbeitung für die Shapefile-Ausgabe.

Syntax

DirectionalDistribution_stats (Input_Feature_Class, Output_Ellipse_Feature_Class, Ellipse_Size, {Weight_Field}, {Case_Field})

Parameter	Erläuterung	Datentyp
Input_Feature_Class	A feature class containing a distribution of features for which the standard deviational ellipse will be calculated.	Feature Layer
Output_Ellipse_Feature_Class	A polygon feature class that will contain the output ellipse feature.	Feature Class
Ellipse_Size	The size of output ellipses in standard deviations. The default ellipse size is 1; valid choices are 1, 2, or 3 standard deviations. 1_STANDARD_DEVIATION — 2_STANDARD_DEVIATIONS — 3_STANDARD_DEVIATIONS —	String
Weight_Field (optional)	The numeric field used to weight locations according to their relative importance.	Field
Case_Field (optional)	Field used to group features for separate directional distribution calculations. The case field can be of integer, date, or string type.	Field

Codebeispiel

DirectionalDistribution Example (Python Window)

The following Python Window script demonstrates how to use the DirectionalDistribution tool.

import arcpy
arcpy.env.workspace = r"C:\data"
arcpy.DirectionalDistribution_stats("AutoTheft.shp", "auto_theft_SE.shp", "1_STANDARD_DEVIATION", "#", "#")

DirectionalDistribution Example (stand-alone Python script)

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

# Measure the geographic distribution of auto thefts
 
# Import system modules
import arcpy
 
# Local variables...
workspace = "C:/data"
locations = "AutoTheft.shp"
links = "AutoTheft_links.shp"
standardDistance = "auto_theft_SD.shp"
stardardEllipse = "auto_theft_SE.shp"
linearDirectMean = "auto_theft_LDM.shp"
 
try:
    # Set the workspace (to avoid having to type in the full path to the data every time)
    arcpy.env.workspace = workspace
 
    # Process: Standard Distance of auto theft locations...
    arcpy.StandardDistance_stats(locations, standardDistance, "1_STANDARD_DEVIATION", "#", "#")
 
    # Process: Directional Distribution (Standard Deviational Ellipse) of auto theft locations...
    arcpy.DirectionalDistribution_stats(locations, standardEllipse, "1_STANDARD_DEVIATION", "#", "#")
 
    # Process: Linear Directional Mean of auto thefts...
    arcpy.DirectionalMean_stats(links, linearDirectMean, "DIRECTION", "#")
 
except:
    # If an error occurred while running a tool, print the messages 
    print arcpy.GetMessages()

Umgebungen

Ausgabe-Koordinatensystem, Aktueller Workspace, Scratch-Workspace, Ausgabe hat M-Werte, Ausgabe hat Z-Werte, Standard-Ausgabe-Z-Werte, Vollständig spezifizierte Feldnamen

Ausgabe-Koordinatensystem

Feature geometry is projected to the Output Coordinate System prior to analysis. All mathematical computations are based on the Output Coordinate System spatial reference.

Lizenzinformationen

ArcView: Ja

ArcEditor: Ja

ArcInfo: Ja