Thematic mapping techniques

When approaching data visualisation, we need to make sure the correct tools are being used. Most importantly, think about the best way to represent and convey the message that the data is trying to tell. Making a map when a chart or graph would suffice could lead to the data being interpreted incorrectly.

The art of map making (or cartography) is a form of data visualisation and there are a number of mapping techniques we can use to bring data to life. Thematic mapping is how we map a particular theme to a geographic area. It tells us a story about a place and is commonly used to map subjects such as climate issues, population densities or health issues.

When creating a thematic map, it is important that we fully understand the data we are planning to depict and the consequence of representing this data incorrectly. Maps can sometimes misinform people, so choosing the correct map technique is crucial.

Dot density map

A dot density map is a map that uses a dot symbol to represent a feature. For one-to-one dot density maps, each dot is equally sized and each one represents the recording of a single thing. Each dot should be depicted in its correct spatial location to avoid the data being misrepresented and the message lost.

For one-to-many dot density maps, each dot depicts more than one recording of a thing and the amount each dot represents is determined by the cartographer. Dots can be randomly positioned and do not necessarily represent the exact spatial location of something. When creating a one-to-many dot density map, it’s important to include a legend indicating the value that one dot represents.


  • You can map raw data or simple counts

  • Shows density and distribution across a wide area

  • Gives a good visual representation of variations across the data


  • Clustering can make the data difficult to interpret

  • Areas with no dots can give a false sense of emptiness

  • Geography can become hidden

  • Dots on a one-to-many dot density map can be inferred as a single location of something

This method was used to great effect in the 19th Century when English physician John Snow mapped the location of cholera outbreaks. The map was created to help understand the pattern of cholera spread in the 1854 Broad Street cholera outbreak. Snow used this as an example of how cholera spread via the fecal-oral route through water systems as opposed to the miasma theory of disease spread.

Proportional symbol map

A proportional symbol map uses map symbols that vary in size to represent a numeric variable. For example, circles may be used to show the location of cities within your map where each circle is sized proportional to the population of the city. This is one of the best methods for recording instances of something that falls within a geography.


  • Large quantities of data can be interpreted quickly

  • Useful for visualising differences between many places

  • Visually appealing

  • Easier to extract actual numbers than a dot density map (legend required)

  • Can use raw data (totals or counts) and standardised data (ratios or percentages)

  • Smaller geographic regions are not overlooked


  • As values get bigger symbols can begin to overlap

  • Size of symbols can obscure location

  • Map readers do not always estimate area of symbol well

Choropleth map

A choropleth map is a map where geographic areas are coloured or styled in relation to a value. This technique is useful when visualising how a measurement varies across a geographic area. This is commonly used when looking at vote totals by a political party.


  • Easy to understand

  • Depicts spatial distributions of data well

  • Visually effective

  • Works well at virtually all scales


  • Map assumes the whole geographic regions has the same value when in fact they may not

  • Small areas can get lost and bigger areas can appear more important

  • May not work in black and white

  • Not suitable for raw data - normalise!

Heat map

A heat map is a favourite amongst many and is used to represent the density of data in gradients of colour. Through the creation of a hot spot, it allows you to quickly identify areas for further analysis. They are typically used to depict things like crime hot spots or temperature.


  • Hot spots in data can be quickly identified and analysed further

  • Works well for temperature and pollution data


  • Excessive use of colour can affect the legibility of the map

  • Does not always depict data distribution very well

Equal area cartograms

A standard cartogram is a type of map where the shape and size of regions are distorted based on a data value. In an equal area cartogram however, every region is represented by the same shape of the same size, giving equal representation to each area. The spatial relationship between areas remain as close as possible to reality and places which are located adjacent in reality, are adjacent on the cartogram. With this method, the use of colour is important and many people choose to add labelling stating the actual values.


  • Visually appealing

  • Allows for the addition of depicting extra data

  • Regions are all the same size – no risk of small regions getting lost

  • Each area can be labelled equally


  • The location is not 100% accurate

  • Can loose familiarity of the shape of overall area

Ordnance Survey’s Data Viz team have created their own equal area cartogram for Great Britain and the United Kingdom. You can download them in a range of formats and can find out more information here.

Other types of thematic map

There are many more thematic mapping techniques beyond those described above and we’d recommend you do a bit of research on the ones listed below before you start mapping:

  • Flow maps

  • Isarithmic (isoline) maps

  • Standard cartograms

  • Chorochromatic (area class) maps

  • Dasymetric maps

  • Hexbin (grid) maps

Other considerations

When considering your map technique, it’s important to think about other factors too. How will the map be used? Is it an interactive web map or perhaps a static map? Are the connotations of the colour scheme suitable for the dataset type?

Another important consideration when creating a thematic map is the choice of basemap. This includes deciding what information is needed to provide context to your data and also it is styled to create an effective visual hierarchy so that the message of your map is communicated to users clearly.

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