### The 7 Best Thematic Map Types for Geospatial Data

#### Learn what they are, Understand when and how to use the different thematic mapping techniques

Choropleth maps are widely used in mapping despite their apparent shortcomings. What are other alternative thematic maps that can convey the data more effectively? In this article, we review some of the best thematic mapping techniques out there, their use cases and pros and cons of each type.

But first, what is a thematic map?

Thematic Maps focus on a specific theme. It pulls together relevant information of the subject ( say, health, election, income, etc.) and represents it spatially to understand the relationship between these themes and their locations.

In contrast to navigation maps which we use to find our way from point X to point Z or reference maps which portray features like coastline and terrains, thematic maps focus on specific theme or subject.

There are a different number of thematic map visualisations that have various user applications. Let us have a look at the seven most used thematic map types.

### 1. Choropleth Map

The choropleth map is one of the most frequently used maps in Geospatial data. It is a type of thematic map in which we use colour to represent statistics of an attribute feature we are interested proportionally to its location — for example, the unemployment rate of each county. Choropleths are good at displaying densities using colours.

Choropleth maps are used widely in conveying statistical values in different geographical scale, from global to local. However, they have some limitations. One particular drawback of using choropleth maps is that areas are not uniform, and thus the displayed results might not portray the right results. For example, large geographic areas might dominate the visual.

Beware to normalize the attribute for the choropleth map. Otherwise, the visual map is misleading

Strengths:

• Display densities ( ratios ) of quantities using colour.

Weaknesses:

• The visual tends to generalise
• Not uniform areas

### 2. Dot Distribution Map

A dot distribution map, or dot density map, is a thematic map type that uses dots (variation of marks) to display the presence or absence of a feature. Typically, one point is assigned to represent a larger quantity. For example, in the below map, one dot represents 100 indigenous people in Australie.

This map shows clearly the trend or spatial pattern of where indigenous people live across Australia.

Note that the points are mostly generated randomly.

Strengths:

• A right way visualises spatial patterns.
• An effective way to represent also different categories using colours

Weaknesses:

• Randomly generated points might differ from one iteration to another.
• If shown without borders, we do not know where these points represent.

Graduated maps are an alternative to choropleth maps. The difference is instead of using colour to indicate feature attributes or statistics; Graduated symbol map uses points. The data is likely stored in Polygons and then converted to centroid points for these areas. We use this type of map when we intend to visualise quantities rather than densities in Choropleth map.

We divide the feature attribute quantities into classes using different classification techniques like quantile, natural breaks and equal interval. For example, the graduated symbol map above separates the population for some cities into five classes. Each of these classes has a specific dot size depending on the classification of the population in that city.

Strength:

• It does a better job showing raw quantities rather than densities with choropleth maps.
• It conveys where and how much (quantities).

Weakness:

• They are less exact than distribution maps.
• Needs preprocessing to derive centroids.
• Overlapping circles (Can use transparency)

### 4. Heat Maps

Heat maps display the density of points on a geographic map and can effectively visualise the intensity of the variable through a colour scale. A heat map shows hot spots or concentrations of points. This technique is often used when geographic boundaries are not that much important.

Strengths:

• It makes easy to understand relationships between data points and the overall trend.

Weaknesses:

• If the colour is not used appropriately, it might affect the legibility of the visualisation.
• Colour transitions might depict perceptions that are not present.

### 5. Cartogram

A cartogram is a thematic map type in which the size of an area is rescaled to be proportional to the feature it represents. Therefore, the rescaled size communicates the feature attributes selected. In that case, cartograms distort area sizes.

There are different types of cartograms, and the most used one is what we call contagious cartograms, where the topology is maintained, but the shape distorted dramatically (Shown below).

Strengths:

• Good at showing numbers like the number of people.

Weaknesses:

• Since the geographic areas are distorted, areas might not be recognisable.
• The are intended for map-literate audiences only.

### 6. Bivariate Choropleth Map

Bivariate choropleths are similar to choropleth maps with one exception. Instead of using one variable to display densities, Bivariate choropleth maps use two variables at once. This method compares two dissimilar distributions on the same map.

Best use cases for bivariate choropleth maps are when you have two dissimilar attributes that you want to display at once.

Strengths:

• Visualise two themes at once
• Aesthetically beautiful

Weaknesses:

• Complex and hard to read sometimes
• Hard to have an interactive version of the bivariate map.

### 7. Value by Alpha Map

Another closely related type to Bivariate choropleth map is the value by alpha map. Value-by-alpha is bivariate choropleth technique where we consider two variables that affect each other say, for example, election results and population density. The second variable acts as an equaliser for the other variable of interest.

VBA modifies therefore through the alpha variable (transparency) the background colour. Thus, lower values fade into the background, while higher values pop up. The VBA maps came into existence to reduce the larger size bias in choropleth maps.

Strengths:

• Display bivariate relationships with classes more than 3.
• Aesthetically beautiful

Weaknesses:

• Complex and hard to read sometimes
• Hard to have an interactive version of the bivariate map.

### Conclusion

We have seen 7 of the best-used thematic maps. There are others which are not included in this list but also have other user applications. Let me know your favourite thematic map types.