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Geospatial Heatmap

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  • Encoding Channels
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Geospatial heatmap charts are useful for displaying how geographical areas of a map compare to one another based on a given criterion.


Heatmap charts can use a maximum of 10,000 documents. If you create a heatmap with a collection of more than 10,000 documents, turn on Sample Mode or use a filter. Otherwise, your chart may use incomplete or misleading data.

To create a geospatial heatmap chart:

  1. On the chart editing screen, select Geospatial from the Chart Type dropdown menu.
  2. Select Heatmap from the three available geospatial chart types.

A geopoint encoding channel which defines the map area of the chart. See the Geopoint reference page for more information about what types of data you can use in this channel.

An aggregation encoding channel that changes the shading of the colors in different chart regions to reflect the aggregated values of this field. More intense colors in the visualization reflect greater aggregated values.

The radius customization option dictates the size of the data markers in Geospatial Heatmaps. The color of each data marker reflects the aggregated value of all data points within that marker's radius. Radius is measured in pixels, and defaults to 30.


If ten data points exist within the specified radius, the color displayed is based on the aggregated value of those ten data points.


Intensity shading is local to the map's current view. The most intense color is displayed for the most extreme aggregated values currently visible on the map, even if there are points outside the current view that are more extreme.

Unlike other types of charts, the legend and the chart colors on geospatial heatmaps change when the view changes. The color range is based on the data in the current view, and may change when you pan or zoom the map.

The following chart is based on AirBnB data for the Seattle area. It shows rental rate hot spots in a geospatial heatmap.

Geospatial heatmap example

The Coordinates channel uses the location database field, which contains arrays of latitude-longitude pairs. The Intensity field uses the monthly_price database field, which contains monthly rental rates for each property in the database.

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