Identity (Analysis)

Summary

Computes a geometric intersection of the input features and identity features. The input features or portions thereof that overlap identity features will get the attributes of those identity features.

Illustration

Identity illustration

Usage

  • Input Features can be point, multipoint, line, or polygon. The inputs cannot be annotation features, dimension features, or network features.

  • Identity Features must be polygons or have the same geometry type as the Input Features.

  • When using this tool with point input and polygon Identity Features, points that fall directly on a polygon boundary will be added to the output twice, once for each polygon that is part of the boundary. Running the Intersect tool on the output of this scenario will identify the duplicate points so you can decide which one to keep.

  • When the Input Features are lines and the Identity Features are polygons, and the Keep relationships parameter is checked (relationship set to KEEP_RELATIONSHIPS in Python), the output line feature class will have two additional fields, LEFT_poly and RIGHT_poly. These fields contain the feature ID of the Identity Features on the left and right side of the line feature.

  • Attribute values from the input feature classes will be copied to the output feature class. However, if the input is a layer or layers created by the Make Feature Layer tool and a field's Use Ratio Policy is checked, then a ratio of the input attribute value is calculated for the output attribute value. When Use Ratio Policy is enabled, whenever a feature in an overlay operation is split, the attributes of the resulting features are a ratio of the attribute value of the input feature. The output value is based on the ratio in which the input feature geometry was divided. For example, if the input geometry was divided equally, each new feature's attribute value is assigned one-half of the value of the input feature's attribute value. Use Ratio Policy only applies to numeric field types.

    Caution:

    Geoprocessing tools do not honor geodatabase feature class or table field split policies.

  • This tool will use a tiling process to handle very large datasets for better performance and scalability. For more details, see Geoprocessing with large datasets.

  • This tool may generate multipart features in the output even if all inputs were single part. If multipart features are not desired, use the Multipart to Singlepart tool on the output feature class.

  • This tool honors the Parallel Processing Factor environment. If the environment is not set (the default) or is set to 0, parallel processing will be disabled. Setting the environment to 100 will cause parallel processing to be enabled.

Syntax

arcpy.analysis.Identity(in_features, identity_features, out_feature_class, {join_attributes}, {cluster_tolerance}, {relationship})
ParameterExplanationData Type
in_features

The input feature class or layer.

Feature Layer
identity_features

The identity feature class or layer. Must be polygons or the same geometry type as the input features.

Feature Layer
out_feature_class

The feature class that will be created and to which the results will be written.

Feature Class
join_attributes
(Optional)

Determines what attributes will be transferred to the output feature class.

  • ALLAll the attributes (including FIDs) from the input features, as well as the identity features, will be transferred to the output features. If no intersection is found the identity feature values will not be transferred to the output (their values will be set to empty strings or 0) and the identity feature FID will be -1. This is the default.
  • NO_FIDAll the attributes except the FID from the input features and identity features will be transferred to the output features. If no intersection is found the identity feature values will not be transferred to the output (their values will be set to empty strings or 0).
  • ONLY_FIDAll the attributes from the input features but only the FID from the identity features will be transferred to the output features. The identity features FID attribute value in the output will be -1 if no intersection is found.
String
cluster_tolerance
(Optional)

The minimum distance separating all feature coordinates (nodes and vertices) as well as the distance a coordinate can move in X or Y (or both).

Caution:

Changing this parameter's value may cause failure or unexpected results. It is recommended that this parameter not be modified. It has been removed from view in the tool dialog. By default, the input feature class's spatial reference x,y tolerance property is used.

Linear Unit
relationship
(Optional)

Determines if additional spatial relationships between the in_features and the identity_features are to be written to the output. This only applies when the in_features are lines and the identity_features are polygons.

  • NO_RELATIONSHIPSNo additional spatial relationship will be determined.
  • KEEP_RELATIONSHIPSThe output line features will contain two additional fields, LEFT_poly and RIGHT_poly. These fields contain the feature ID of the identity_features on the left and right side of the line feature.
Boolean

Code sample

Identity example 1 (Python window)

The following Python window script demonstrates how to use the Identity function in immediate mode.

import arcpy
from arcpy import env
env.workspace = "c:/data/data.gdb"
arcpy.Identity_analysis("wells", "counties", "wells_w_county_info")
Identity example 2 (stand-alone Python script)

The following stand-alone Python script is a simple example of how to apply the Identity function in scripting.

# IdentityWells.py
# Description: Simple example showing use of Identity tool
 
# Import system modules
import arcpy
from arcpy import env

# Set the workspace
env.workspace = "C:/data/data.gdb"

# Set local parameters
inFeatures = "wells"
idFeatures = "counties"
outFeatures = "wells_w_county_info"

# Process: Use the Identity function
arcpy.Identity_analysis (inFeatures, idFeatures, outFeatures)

Licensing information

  • Basic: No
  • Standard: No
  • Advanced: Yes

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