Clusters visualize and summarize overlapping features in an intuitive, concise way. Use the swipe widget to compare an unclustered layer of power plants with a clustered version.
High density dataLarge, dense datasets are difficult to visualize well. These datasets typically involve overlapping features, which makes it difficult or even impossible to see spatial patterns in raw data. The following topics demonstrate various ways you can visualize high density data in a more meaningful way.
NoteThe density of a layer's features is always relative to the map scale. For example, a set of points may be dense at a small scale (zoomed out) but appear dispersed at a very large scale (zoomed in). When determining the best way to represent dense data, you should first understand the scale levels at which users will typically view it.
Client-side techniquesThe following topics describe how you can visualize high density data client-side. These are ideal for dense datasets where all features can be loaded to the browser.
ClusteringLearn how to visualize high density data using clusters.
BinningLearn how to visualize high density data using clusters.
HeatmapLearn how to visualize high density point data as a continuous heatmap surface.
OpacityLearn how to visualize high density data using opacity.
BloomLearn how to visualize high density data using a bloom layer effect.
Server-side techniquesThe following topics describe techniques ideal for representing very large layers that cannot be reliably loaded to the browser. These should also be considered for reducing the size of datasets that need to be viewed on mobile devices. Note that the techniques mentioned here may be used in combination with the techniques mentioned above.
Aggregation analysis toolsLearn how to visualize high density data by aggregating points to polygons.
ThinningLearn how to reduce the number of features in the view by thinning data from very large layers.
Visible scale rangeLearn how to leverage visible scale ranges in layers to avoid downloading too many features at small scales.
API supportThe following table describes the geometry and view types that are suited well for each visualization technique.
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