A thematic map is a type of map specifically designed to “show a particular theme connected with a specific geographic area.
Unlike reference maps, which tell us where something is, thematic maps tell us how something is.
There are a number of visualization techniques and thematic map types that have different applications depending on the type of data that you are exploring and the type of spatial analysis that you are looking to do. The methodology and the type of map that you want to create may be different, for example, if you are exploring global shipping data or voter propensity, or environmental disaster impact.
All thematic maps use maps with coastlines, city locations and political boundaries as their base maps. The map’s specific theme is then layered onto this base map via different mapping programs and technologies like a geographic information system (GIS).
History of Thematic Maps
Thematic maps did not develop as a map type until the mid-17th Century because accurate base maps were not present prior to this time. Once they became accurate enough to display coastlines, cities and other boundaries correctly, the first thematic maps were created. In 1686 for example, Edmond Halley, an astronomer from England, developed a star chart. In that same year, he published the first meteorological chart using base maps as his reference in an article he published about trade winds. In 1701, Halley also published the first chart to show lines of magnetic variation- a thematic map that later became useful in navigation.Halley’s maps were largely used for navigation and the study of the physical environment.
In 1854, John Snow, a doctor from London created the first thematic map used for problem analysis when he mapped cholera’s spread throughout the city. He began with a base map of London’s neighborhoods that included all streets and water pump locations. He then mapped the locations where people died from cholera on that base map and was able to find that the deaths clustered around one pump and determined that the water coming from the pump was the cause of cholera.
In addition to these maps, the first map of Paris showing population density was developed by a French engineer named Louis-Leger Vauthier. It used isolines (a line connecting points of equal value) to show population distribution throughout the city and was believed to be the first use of isolines to display a theme that did not have to do with physical geography.
Lets take a look at some popular thematic maps and mapping techniques.
A choropleth map is a thematic map where geographic regions are colored, shaded, or patterned in relation to a value.This type of map is particularly useful when visualizing a variable and how it changes across defined regions or geopolitical areas.
For example, a choropleth map is extremely useful when looking at vote totals by political party per county in the United States, as below. In a choropleth map, color can be used to represent distinct attributes or, as in the example below, to represent weight of a value (a strong or weak party vote-share shown as light or dark colors).
Isarithmic or Isopleth
Isarithmic maps, also known as contour maps or isopleth maps depict smooth continuous phenomena such as precipitation or elevation. Each line-bounded area on this type of map represents a region with the same value. For example, on an elevation map, each elevation line indicates an area at the listed elevation. An Isarithmic map is a planimetric graphic representation of a 3-D surface. Isarithmic mapping requires 3-D thinking for surfaces that vary spatially.
A heat map represents the intensity of an incident’s occurrence within a dataset. A heatmap uses color to represent intensity, though unlike a choropleth map, a heatmap does not use geographical or geo-political boundaries to group data. This technique requires point geometries, as you are looking to map the frequency of an occurrence at a specific point.
Visualizing the intensity of occurrence using a heat map is a technique commonly used when tracking weather and natural phenomena, in which established borders and boundaries are less useful for understanding impact areas. In the heat map below, drought conditions across the United States are visualized based on intensity, giving us a greater understanding of past and potential impact areas.
Proportional symbol maps
A proportional symbol map can represent data tied to a specific geographical point or data that is aggregated to a point from a wider area.
In these maps, a symbol is used to represent the data at that specific or aggregate point, and then scaled by value, so that a larger symbol represents a greater value. The size of each symbol can be proportional to the value you are visualizing or you can set 3 to 5 ‘classes’ of values allowing for comparison and classification of locations.
Dot density maps
A dot density map uses a dot to represent a feature or attribute in your data.
Some dot density maps are ‘one-to-one’ in which each dot represents a single occurrence or data point, or ‘one to many’ in which each dot represents a set of aggregated data, for example one dot may represent 100 individuals with a certain attribute. Both of these types of dot density map visualize the scatter of your data, which can provide insights into where instances of an occurrence are clustered.
Animated time-series maps
More of a technique than a type, if your data has a temporal component (taking place over time), you can transform any of the above visualizations into an animated time-series map. Looking at your data over time can both improve your ability to gain insights and create a stronger and more compelling visual.
Putting your data on an appropriate time scale will allow you to make important business decisions. Mapping foot traffic over the course of a week, for example, may inform hours of operation for a retail location while mapping and animating a century’s worth of sea level measurements can paint a vivid picture on the impact of global climate change.
With many applications from social listening to resource management to demographic projection, animating your data as a time-series map unlocks a new dimension at which to view your data.
A dasymetric map is an alternative to a choropleth map. As with a choropleth map, data are collected by enumeration units. But instead of mapping the data so that the region appears uniform, ancillary information is used to model internal distribution of the phenomenon. For example, population density will be much lower in forested area than urbanized area, so in a common operation, land cover data (forest, water, grassland, urbanization) may be used to model the distribution of population reported by census enumeration unit such as a tract or county.