Maps

Geographic heat / density map

Estimates spatial concentration from point locations and optional weights.

Map
Geography
Density

What it answers

Where do point events concentrate spatially?

Shape: Smooth spatial colour surface
What it shows: Hotspots and density gradients.

Example

The question

Where are delivery complaints concentrated?

Density of delivery complaints, 2025 (heat map)

A smooth colour surface over the map: pink marks the densest complaints, fading through purple to none. The main hot spot is in the north-centre, a second in the south-east.

Illustrative data. It belongs to no company.

When to use it

Use it when

Spatial event concentrations with many points.

Avoid it when

When smoothing or geography creates false precision.

How to read it

Read intensity against the density legend and bandwidth.

Note

Specify bandwidth, units and projection.

The data you need

Layout: Long table
Fields: LocationID: text; Longitude,Latitude: numbers; Value: nonnegative number
One row is: One point location and its value or weight. What is the grain?
Rules: State CRS. For WGS84, longitude is [-180,180] and latitude [-90,90]. Validate coordinate order.
Optional: For unweighted density, each point may have weight 1. Project coordinates appropriately for distance calculations.
Preparation: Validate the input grain and missing values. State CRS. For WGS84, longitude is [-180,180] and latitude [-90,90]. Validate coordinate order.
Units: Specify density units, smoothing bandwidth and weight. Events perarea differs fromraw kernel intensity.

A long table: one row per observation, few columns. New data adds rows.

Worked example

Suppose 10 events lie close together and 2 far away. A fixed-bandwidth density surface is stronger near the cluster; it does not locate unobserved events.

LocationID	Longitude	Latitude	Value
A	18.07	59.33	30
B	11.97	57.71	45

All charts in the library