A general-purpose map tries to tell you everything: where the roads are, what the terrain looks like, where the cities sit, where the borders run. A thematic map does the opposite. It picks one subject, like population density, election results, or rainfall, and turns the rest of the geography into a quiet backdrop. Everything on the page exists to make that one dataset legible.
Thematic maps are how journalists explain election outcomes, how epidemiologists track outbreaks, how planners size infrastructure, and how product teams decide which markets to enter. If you have ever looked at a map of something and instantly understood a pattern you would have missed in a spreadsheet, you have looked at a thematic map.
This guide covers what a thematic map is, the main types you will encounter, when to use which, and how to build one with the MapAtlas Maps API.
What Makes a Map "Thematic"
A reference map (think of an atlas page) shows many features at once and treats them as roughly equal. A thematic map demotes the geography to a base layer and promotes a single dataset to the foreground. The base layer is intentionally muted, often greyed-out borders or a soft road network, so the eye is drawn to the colours, dots, or symbols that carry the data.
Two things define a good thematic map. First, a clear subject: one variable, presented well, beats five variables fighting for attention. Second, an honest visual encoding: the choice of colour scheme, classification, and symbol type should reveal the pattern in the data, not invent one.
The Main Types of Thematic Map
Choropleth maps
A choropleth map fills predefined regions, countries, states, postcodes, hex grids, with a colour that encodes a value. They work well when your data is already tied to administrative boundaries and when you have normalised it. Voter turnout per region is a classic example. Always normalise the data, because raw counts in choropleth maps inflate large regions and hide patterns in small ones.
Dot density maps
A dot density map scatters one dot for every N occurrences of a phenomenon. A population dot density map might place one dot per 1,000 people. The eye reads the cloud of dots as density without you having to compute or label numbers. They work well for raw counts and avoid the area-bias problem of choropleths.
Proportional symbol maps
A proportional symbol map places a circle (or other shape) at each location and sizes it by a value. They are excellent for raw counts at point locations: number of customers per store, earthquake magnitudes, population per city. The reader can compare two cities directly by comparing two circles, regardless of how much land area each city happens to cover.
Isarithmic and heat maps
Isarithmic maps (also called contour maps) draw lines or filled bands of equal value across a continuous surface. Topographic contour lines, weather isotherms, and pressure isobars are all isarithmic maps. A web heat map is a closely related visualisation that smooths point data into a continuous coloured surface, useful for showing where activity clusters in a city or website.
Dasymetric and cartogram variations
Dasymetric maps refine a choropleth by using ancillary data (like land use) to push the value into the parts of the region where it actually occurs. Cartograms distort the size of regions to match the data, so a country with a large population becomes large on the map regardless of its physical area. Both are powerful when standard types are misleading.
Choosing the Right Type
Start with the data. If it is a rate or percentage tied to administrative regions, use a choropleth. If it is a raw count tied to point locations, use proportional symbols. If it is a raw count over an area, use dot density. If it is a continuous variable like temperature or elevation, use an isarithmic map. If physical area would distort the message, use a cartogram.
Then pick a colour scheme. Sequential schemes (light to dark) work for ordered data. Diverging schemes (two colours meeting at a midpoint) work for data with a meaningful zero, like change versus a baseline. Categorical palettes are for unordered categories. The ColorBrewer palettes remain the standard reference for any of these.
Building a Thematic Map with MapAtlas
The MapAtlas Maps API gives you vector tiles and styling controls suitable for any of the types above. You load a base style with administrative boundaries, fetch your data as GeoJSON, and add a fill layer (for choropleths), a circle layer (for proportional symbols), or a heatmap layer for density visualisation.
For administrative regions, the easiest workflow is to host your boundaries as GeoJSON, attach the value you want to map as a property on each feature, and add a fill layer with a data-driven colour expression that maps the property to a colour ramp. For point data, attach the value as a property and use a circle-radius expression sized by the value, with a circle-stroke for legibility on busy maps.
If your goal is interactive analysis (clicking a region to see exact numbers, filtering by category, animating over time), pair the Maps API with a small client-side state layer. For one-shot static maps for blog posts or reports, the same API can render a static image you can save as PNG.
You can also turn an address into the lat/lng you need to place a symbol with the coordinates lookup tool, or compute drive-time catchments with the routing API for accessibility-themed maps.
Common Mistakes to Avoid
The most common failure is using raw counts in a choropleth: a region twice as big will look twice as important. The second is over-classifying with too many colour bins, which obscures the pattern; five to seven classes is usually enough. The third is ignoring colour-blindness, the default red-green palette is unreadable for a meaningful slice of users.
A thematic map is a piece of communication. The math should be honest, the encoding should be clear, and the reader should be able to grasp the pattern in seconds. When that happens, a single map can replace a thousand rows of a spreadsheet.
Frequently Asked Questions
What is a thematic map?
A thematic map is a map designed to show the spatial pattern of one specific subject, such as population density, average income, election results, or rainfall. Unlike a general reference map, which tries to show many features at once (roads, rivers, cities, terrain), a thematic map subordinates everything else to a single dataset and uses colour, shading, or symbols to make that dataset easy to read at a glance.
What are the main types of thematic map?
The four most common types are choropleth maps (which colour predefined regions like countries or counties by a value), dot density maps (which place one dot per N occurrences of a phenomenon), proportional symbol maps (which size a circle or square at each location by a value), and isarithmic or contour maps (which draw lines or filled bands of equal value, like temperature isotherms or topographic contours). Heat maps and dasymetric maps are widely used variations.
When should I use a choropleth map and when should I avoid it?
Use a choropleth map when your data is naturally tied to administrative regions and is normalised (rates, percentages, or per-capita values, not raw counts). Avoid it for raw counts, because larger regions will appear more important than smaller ones simply because of their size. For raw counts, a proportional symbol map or dot density map is usually a better choice.
