Heatmap

Fatal car crashes in 2017 represented as a continuous heatmap. Areas with higher concentrations of crashes are yellow.

What is a heatmap?

A Heatmap renders point features as a raster surface, emphasizing areas with a higher density of points along a continuous color ramp.

Why are heatmaps useful?

Heatmaps can be used as an alternative to clustering, opacity, and bloom to visualize overlapping point features. Unlike these alternative techniques for visualizing density, you can use a heatmap to weight the density of points based on a data value. This may reveal a different pattern tha density calculated using location alone.

Location-only heatmapData-weighted heatmap
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Density of car crashes that resulted in a fatality (2017). Yellow areas indicate the highest density of crash incidents.
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Density of fatal car crashes involving drunk drivers (2017). Yellow areas indicate the highest density of crash incidents that involved drunk drivers.

How a heatmap works

Heatmaps are created by setting a HeatmapRenderer instance to the renderer property of the layer. The HeatmapRenderer has several key properties. The radius determines the area of influence surrounding a point. For example, if you set a radius of 10 pixels, each pixel within 10 pixels of a single point will be assigned a density value. The pixel directly on top of the point will have the highest density. Smaller density values are assigned to pixels surrounding the point inversely proportional to the distance from the point. Pixels on the screen that fall outside that 10-pixel radius of all points will have a density value of 0.

The density value of each pixel accumulates based on its proximity to multiple points. For example, a pixel within 10px of 10 points, will have a higher density value than pixels within 10x of only one point.

The colorStops in the renderer determine how to colorize pixels based on the ratio of a pixel's density value to the maxDensity (i.e. pixel density / maxDensity). Pixels with a density value at or above the maxDensity have a density ratio of 1 and should be assigned the brightest color since these represent the hottest areas. The larger the maxDensity, the fewer hot spots will exist in the map.

Examples

Location heatmap

To create a heatmap, you must apply a HeatmapRenderer to a point layer. Set the renderer properties using the guidelines outlined above. Open this example in CodePen and adjust the radius and maxDensity to see how these properties impact the heatmap.

Density of car crashes that resulted in a fatality (2017). Yellow areas indicate the highest density of crash incidents.
ArcGIS JS API
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        const colors = ["rgba(115, 0, 115, 0)", "#820082", "#910091", "#a000a0", "#af00af", "#c300c3", "#d700d7", "#eb00eb", "#ff00ff", "#ff58a0", "#ff896b", "#ffb935", "#ffea00"];

        layer.renderer = {
          type: "heatmap",
          colorStops: [
            { color: colors[0], ratio: 0 },
            { color: colors[1], ratio: 0.083 },
            { color: colors[2], ratio: 0.166 },
            { color: colors[3], ratio: 0.249 },
            { color: colors[4], ratio: 0.332 },
            { color: colors[5], ratio: 0.415 },
            { color: colors[6], ratio: 0.498 },
            { color: colors[7], ratio: 0.581 },
            { color: colors[8], ratio: 0.664 },
            { color: colors[9], ratio: 0.747 },
            { color: colors[10], ratio: 0.83 },
            { color: colors[11], ratio: 0.913 },
            { color: colors[12], ratio: 1 }
          ],
          radius: 18,
          maxDensity: 0.04625,
          minDensity: 0
        };
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Data-weighted heatmap

This example modifies the previous heatmap to weight the surface by a data variable. The crashes layer used in this example has an attribute that tallies the number of drunk drivers involved in the incident. We can visualize where more drunk drivers are involved in fatal accidents by weighting by that field.

When a field is specified, each pixel's density is multiplied by the data value, so you need to adjust the maxDensity accordingly.

Density of car crashes involving drunk drivers that resulted in a fatality (2017). Yellow areas indicate the highest density of crash incidents.
ArcGIS JS API
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        const colors = ["rgba(115, 0, 115, 0)", "#820082", "#910091", "#a000a0", "#af00af", "#c300c3", "#d700d7", "#eb00eb", "#ff00ff", "#ff58a0", "#ff896b", "#ffb935", "#ffea00"];

        layer.renderer = {
          type: "heatmap",

          field: "Number_of_Drinking_Drivers",

          colorStops: [
            { color: colors[0], ratio: 0 },
            { color: colors[1], ratio: 0.083 },
            { color: colors[2], ratio: 0.166 },
            { color: colors[3], ratio: 0.249 },
            { color: colors[4], ratio: 0.332 },
            { color: colors[5], ratio: 0.415 },
            { color: colors[6], ratio: 0.498 },
            { color: colors[7], ratio: 0.581 },
            { color: colors[8], ratio: 0.664 },
            { color: colors[9], ratio: 0.747 },
            { color: colors[10], ratio: 0.83 },
            { color: colors[11], ratio: 0.913 },
            { color: colors[12], ratio: 1 }
          ],
          radius: 18,

          maxDensity: 0.00875,

          minDensity: 0
        };
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Scale-dependent Heatmap

Dynamic heatmaps are only visually appropriate at a few scale levels. As the user zooms out, the heatmap will always appear hotter. As the user zooms in, the heatmap will appear colder. To prevent the user from viewing a heatmap that is too hot, you can set a minScale on the layer or as a view constraint.

As the user zooms in, the heatmap becomes irrelevant. Therefore, you should set a watch on the view to toggle the layer's heatmap to a simple renderer representing individual point locations.

Density of crimes classified as fraud in San Diego California. Zoom in and out on the map to view how the developer can restrict the user from seeing a heatmap that is too hot or too cold. As the user zooms in, the heatmap toggles off and displays the point locations as a simple renderer.
Set a constraint on map view scale to avoid hot heatmaps
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        const view = new MapView({
          container: "viewDiv",
          map: map,
          constraints: {
            minScale: 1155582,
            snapToZoom: false
          }
        });
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Switch to a location renderer after zooming beyond a scale threshold
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          view.watch("scale", (newValue) => {
            layer.renderer = newValue <= 72224 ? simpleRenderer : heatmapRenderer;
          });
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Static heatmaps

Static heatmaps allow you to persist the visual density's of a heatmap from one scale across all scale levels. As the user zooms in and out, the heatmap will consistently show the same hot spots in the view.

As the user zooms in, the heatmap becomes irrelevant, so you may want to set a constraint on the MapView to prevent overzooming.

Density of trees in New York City (2015). Zoom in and out to observe how a static heatmap may be a more attractive solution to highlighting areas of high density.
ArcGIS JS API
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          maxDensity: 0.319,
          minDensity: 0,
          // settings for heatmap apply only to this scale
          // so renderer will look consistent without
          // dynamically updating on zoom

          referenceScale: 36111,

          radius: 6,
          legendOptions: {
            minLabel: "Low tree density",
            maxLabel: "High tree density"
          }
        };
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Image preview of related sample Visualize points with a heatmap

Visualize points with a heatmap

Visualize points with a heatmap

Image preview of related sample Create a scale-dependent visualization

Create a scale-dependent visualization

Create a scale-dependent visualization

Image preview of related sample Visualize points in a scene with a heatmap

Visualize points in a scene with a heatmap

Visualize points in a scene with a heatmap

Image preview of related sample Create a static heatmap

Create a static heatmap

Create a static heatmap that doesn't adjust based on scale

HeatmapRenderer

Read the API Reference for more information.

API support

The following table describes the geometry and view types that are suited well for each visualization technique.

2D3DPointsLinesPolygonsMeshClient-sideServer-side
Clustering
Heatmap
Opacity
Bloom
Aggregation
Thinning11123
Visible scale range
Full supportPartial supportNo support
  • 1. Feature reduction selection not supported
  • 2. Only by feature reduction selection
  • 3. Only by scale-driven filter

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