Aggregate Points (Cartography)
Summary
Creates polygon features around clusters of proximate point features.
Usage
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Polygons are created around clusters of three or more points within the aggregation distance.
A one-to-many relationship table—named the same as the output feature class appended with _Tbl—will be created that links the aggregated polygons to their source point features. This table is in the same location as the output feature class and contains two fields, OUTPUT_FID and INPUT_FID, storing the aggregated feature IDs and their source feature IDs, respectively. The link can become incorrect when any of the input or output features are modified. With this table, you can derive necessary attributes for the output features from their source features using appropriate geoprocessing tools.
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Point aggregation may introduce polygon holes or areas where adjacent polygon boundaries meet at one vertex.
Syntax
Parameter | Explanation | Data Type |
in_features |
The input point features that will be assessed for proximity and clustering. | Feature Layer |
out_feature_class |
The feature class created to hold the polygons that represent the point clusters. | Feature Class |
aggregation_distance |
The distance between points that will be clustered. | Linear unit |
Code Sample
The following Python Window script demonstrates how to use the AggregatePoints tool in immediate mode.
import arcpy from arcpy import env env.workspace = "C:/data" arcpy.AggregatePoints_cartography("C:/data/cartography.gdb/crime/robberies", "C:/data/cartography.gdb/crime/clustered_robberies", "100 meters")
This stand-alone script shows an example of using the AggregatePoints tool.
# Name: AggregatePoints_standalone_script.py # Description: Creates polygon features around clusters of proximate point features. # Import system modules import arcpy from arcpy import env # Set environment settings env.workspace = "C:/data" # Set local variables in_point_features = "C:/data/cartography.gdb/crime/robberies" out_feature_class = "C:/data/cartography.gdb/crime/clustered_robberies" aggregation_distance = "100 meters" # Execute Aggregate Points arcpy.AggregatePoints_cartography(in_point_features, out_feature_class, aggregation_distance)