In ArcGIS Pro, you can aggregate point or multipoint feature classes. If you have a point feature class, you can apply feature binning to the layer to dynamically aggregate features into bins at multiple scales.
You can also aggregate values from a group of related features and display those features based on the result.
Feature binning
Feature binning is a process that aggregates large amounts of point features into dynamic polygons called bins. A single bin represents all features within its boundaries and appears wherever at least one feature lies within it. As a method of feature reduction, feature binning vastly improves the drawing performance of layers that contain thousands or millions of point features.
There are several ways to draw the bins to represent the aggregated features. Feature binning is dynamic, meaning that bins will change in size and value depending on the map's scale. You can also use feature binning to display values based on the number of aggregated features in a single bin. As point features are updated, the values—referred to as summary statistics—for each bin are updated.
ArcGIS Pro creates an arbitrary framework to generate the bins over the data at multiple scales, which are not based on preexisting geographies or political boundaries. Thus, considerations must be made for the projected coordinate system used for the bins on the map, as projections that do not conserve area may contain data bias. For more information, see Work with binned feature layers.
Bins base their value on the summary statistics of their contents, such as the sum or maximum value of any feature contained within the bin. Bins are then symbolized to represent their relative value. The color of the bin is dependent on the symbology used and the range in values of other bins. There are some restrictions on the type of symbology that can be used for bins. For more information, see Symbolize binned feature layers.
Aggregation considerations
ArcGIS Pro provides two aggregation methods for point data: feature binning, and feature clustering. Both methods achieve similar goals but are visually and behaviorally different. Consider the following when choosing which aggregation method to apply.
Feature binning is the more predictable approach to feature aggregation when compared to feature clustering. The alignment of the bins is consistent, and the point features they represent fall within the bounds of their bin. This improves data interpretation and reduces data noise. Clusters may change location as you pan and zoom around the map,depending on the centroid of their represented features. The exact location of a cluster's features is not always clear.
However, the default symbolized bins obscure much of the map, while clustering allows other features or the basemap to remain partially visible. With feature binning, a single point is drawn as a bin, whereas single point features are not clustered.
Using heat map symbology to show densely populated features is another way to visualize dense point information. Binning features may better represent the data for sparsely distributed groups of points and may be preferable for multiscale maps in which the level of detail frequently changes or requires insets.
Database driven feature binning
Prior to ArcGIS Pro 3.1, a point feature class must be stored in a relational database management system (RDBMS) and have feature binning enabled to draw the layer with bins in a map or scene. You can determine whether the point feature class is enabled for database driven feature binning by checking its status in the layer's Source tab in the Layer Properties window.
Starting at ArcGIS Pro 3.1, database-driven feature binning is recommended but not required. Computing and processing bins at the database level takes advantage of performance improvements with point datasets. To get started, run the Enable Feature Binning tool to compute bins for your point feature class. For more information, see Work with binned feature layers.