Smart Mapping: Clustering
Clustering helps to visualize patterns of points without the traditional issues of overlap.
When mapping points datasets that contain many points, it's common to see your points overlap one another. But what happens when most of the points within the map are covering one another? The map starts to look like noise, rather than an informative narrative about the data.
When working with your data in ArcGIS Online and ArcGIS Enterprise, choose the Change Style option to work with smart mapping .
Smart mapping helps you create beautiful and informative maps, quickly. It sets the cartography of your layer based on the significant values within your data. Smart mapping lets anyone quickly discover patterns from attributes in their data and make meaningful maps from them.
ArcGIS offers ways to get around this fundamental spatial issue, such as aggregation methods, heat maps, and statistical analysis. These methods help to lasso the data, but many times require pre-processing.
By applying clustering to point features on-the-fly, you can easily visualize your large point Feature Layers.
Before clustering
After clustering
What is Clustering?
Clustering allows you, as the map maker, to explore and visualize patterns that would have otherwise been hidden. Quickly see your points aggregated into smaller groupings of points. This provides a better understanding of how many points exist within an area.
As you zoom in and out, the clustering will change based on your current extent. Clusters are proportionally sized by the count of features within each cluster. This means that smaller symbols have fewer points clustered within them, and larger symbols have many features clustered within them.
Let's see an example in action:
Here we have a map of public school locations centered on Chicago, IL. As you can see, there are quite a few points trying to be shown at once (18,607 to be exact).
This map, while informative when zoomed in, is not very useful at this scale.
Within the right side toolbar, there is a clustering option.
This button will cluster your point Feature Layers, while maintaining your cartography.
Enable Clustering and the map will translate your existing map symbology into clustered features.
By default, the map will enable cluster labels, which allows us to see how many points are in a cluster by a label that appears on each symbol.
Let's first disable labels as it's making it hard to see our school symbol.
The map by default will suggest a cluster radius and size range. Let's go beyond the defaults and see how changing these settings can improve our narrative.
If we move the cluster radius toward "low", we can see more points and less clusters. Moving the cluster radius toward "high", we can see less points and more clusters. This basic example of public school locations now gives us a better idea of where there are more/less public schools.
Adjusting the size range closer to min will decrease the size of smaller clusters while increases the max size will increase the size of larger clusters.
By default, the popup will tell you the cluster count.
Within a cluster pop-up, you can choose to zoom into the features within that cluster or browse the specific features within a cluster in order to learn more.
Note here we are using the Human Geography map from Living Atlas , which contrasts great with the dark blue of our public schools symbology while also giving us reference labels of the surrounding cities.
Note: If you do not see the Human Geography basemap available under your Basemaps pane, scroll down and click on the Living Atlas magnify glass, and search for 'Human Geography Map.'
The Different Types of Clustering
Clustering allows you to visualize the quantity of points within smaller groupings. But clustering also allows you to maintain your existing cartography.
Clustering Categorical Attributes
We see to the right a map of United Kingdom supermarkets. This is mapped using the Types (Unique Symbols) option. The map shows each color as a distinct supermarket. Unfortunately, there are so many different supermarkets in this area, it is hard to make sense of this map, and no immediate patterns of UK supermarkets are apparent.
When clustering is enabled on this categorical map, the predominant supermarket type will be represented by the feature. The size still represents how many features were clustered. Now, we can see that there are many Tesco Express supermarkets in the London area.
When clustering a categorical map, the default clustering popup will still show the count of features in the cluster, but will also provide the predominant value of the features being clustered.
Clustering Numeric Attributes
On the right, we see a map which shows transit stops in the Los Angeles area. The brighter yellow stops have more hourly trips during the rush hour 7-9 am time slot. Points in blue have fewer stops per hour. Again, there are many overlapping transit stops, so it is hard to decipher a pattern (especially in the downtown area).
When this layer is clustered, the colors retain their meaning, with the spectrum of yellow to blue. But now, we get a better understanding of the amount of transit stops AND the amount of buses that visit those stops during rush hour. The value dictating the color represents an average of the stops being clustered.
In this case, the default clustering popup portrays the average value of the transit stops within each cluster.
*When using clustering, you can set your cartography before or after turning on clustering. Whatever works best in your everyday workflows! These examples showcase what happens when your cartography already exists.
Create your own
In just a few quick steps, you have transformed your map's points data from noise to a informative narrative using the clustering drawing style.
The clustering option in ArcGIS Online Mapviewer allows you to quickly and easily discover new things about your point Feature Layers. Maintain your cartography, arrange the amount of clustering, and watch the patterns unfold!
For more information visit the ArcGIS Online Help Pages .
Try it out today, and when ready share your maps with the hashtag #smartmapping and #ArcGISOnline.
