WHAT
A Flare Cluster is a spatial visualization pattern used to reveal individual or categorized map points within dense clusters—without losing sight of the overall distribution. Instead of merging overlapping markers into a single dot or a count label, a flare cluster fans out selected data points in a radial layout. This reveals more about what’s inside a cluster while keeping things tidy and explorable.
WHEN
There are times when overlapping map features create noise or ambiguity, especially when multiple items share or nearly share the same location. Similar to the cluster marker, flare cluster add interactivity to help in these scenarios by maintaining the density of your data while still offering clarity on what’s included in each cluster.
Use flare cluster in the following situations:
- When multiple features stack on the same coordinates (e.g. events at a single venue)
- When spatial resolution is low due to scale but users still need quick insights
- When filtering by category or type is common and should be visible in-place, similar to Chart marker
- When conventional clustering hides meaningful distinctions between items
- When zooming isn’t the only (or best) way to explore local detail
Apps that benefit from flare cluster include incident reporting dashboards that show police reports or traffic violations, real estate apps showing multiple listings per building, logistics maps showing overlapping pickups or deliveries, or social or event apps where multiple check-ins happen at the same location.
WHY
Flare clusters aren’t just about aesthetics—they serve a real purpose in enhancing the user’s understanding of dense spatial data. They strike a balance between overview and detail, letting users preview the contents of a cluster without committing to zooming or diving into a detail panel.
Flare cluster include the following benefits:
- Preserves context of clustered data while previewing what’s inside
- Provides immediate access to categories, types, or attributes (e.g. color-coded flares)
- Reduces the need for constant zooming in/out
- Helps users make decisions faster by showing summarized content at a glance
- Supports interactions like hover, tap, or expand-to-drill-down
Flare clusters are especially useful when combined with Attribute filter or MapTip to increase data transparency.
HOW
While flare clusters might look playful on the surface, their implementation requires thoughtful spatial logic and interactive design. From data aggregation to positioning logic and animation, here are some of the key building blocks to implement flare clustering effectively.
- Detect overlapping or tightly packed points: Use spatial clustering or proximity rules.
- Generate radial layout: Compute positions around a center point using polar coordinates.
- Render flares: Represent each item (or category) as a circle, wedge, or icon spaced around the center.
- Enable interaction: Allow hover or tap to reveal item details, trigger popups, or zoom.
- Animate gently: Animate flares outward on hover or click to make the interaction feel smooth and responsive.
- Use visual encoding: Color, size, or icons can help communicate what each flare represents.
Keep the number of flares manageable—too many flares defeat the purpose. Consider grouping by type or time range to summarize. Instead of clustering points by arbitrary areas, consider using geographies such as state boundaries to calculate the flare cluster. In that way, the breakdown becomes more meaningful. Regardless of the clustering method, provide feedback to the user about the clustered area by showing the cluster polygon upon hover.
EXAMPLE
In a mobile app that tracks crowd levels on public transport, multiple reports often cluster at a station or bus stop. Instead of showing a single cluster with a count, the app uses a flare cluster that fans out individual reports by category: “crowded,” “normal,” “empty,” and “delayed.” Each flare is color-coded and tappable, allowing users to explore recent observations without needing to zoom in. This gives commuters quick situational awareness and improves usability during peak hours.
RESOURCES
Flare Cluster Layer (by Nick Cameron)
