Cartography touched on the science behind drawing maps, on how maps can be used as visual tools to convey messages. In here, I learnt how maps are a powerful way to visualise data that can be easily translated onto maps – from identifying dengue hotspots, to determining the best location to launch a bicycle sharing system.

I touched a little on cartography in my final year at SUTD with Prof. Ate Poorthuis in the module Making Maps I. The objective was to use maps as a data visualisation tool and convey messages. The contents of this page is based on “A Visual Guide to Map Design for GIS” by John Krygier and Denis Wood, published by The Guilford Press (2011).

Maps are used in a myriad of ways: the one that we are most familiar with and have used for the longest time is for navigation. Nowadays, many of us have access to navigational maps at our fingertips. Some may even recall when we had to stop mid-drive to check our street directory books. Maps even date back to the stone age where our ancestors marked the position of stars and landscapes.

A rebbelib mapped the ocean waves and wind patterns between islands used by islanders in the Pacific and Polynesia (Wikimedia Commons)
Other than navigation, maps are also popular political tools used to demarcate and claim national borders and rousing a nation in war propaganda. Despite being a fascinating debate topic, this article shall keep in line with the discussion of the art and science behind creating these maps.

When creating a map, a goal must first be set. What is the one thing that your map wants to highlight the most? Once defined, the map must be designed to bring out that aspect, and tune out non-essential information. For example, when highlighting the shortest path between 2 buildings, one could increase the width of roads along the path and decrease the width of all other roads.

What then, are the other ways you can highlight a certain detail in a map? To keep things simple and straight-forward, here are a few key concepts to take note of when creating a map:

  • Map Pieces
  • Visual Differences
  • Map Generalization and Classification
  • Map Symbolisation

I will touch on each subject briefly, then sum it up with the cartographic work that I had done. If you would like more details, I would suggest you check out the book “A Visual Guide to Map Design for GIS” by John Krygier and Denis Wood, published by The Guilford Press (2011).

Map Pieces

There are multiple map pieces which contain information of variable importance: its title, scale, legend, explanation, direction, borders, sources and credits, and insets. One must consider the font, size, position, and orientation of the above pieces to capture the attention of the reader. As a guide, the title is usually the largest and boldest text in the map, placed either in the center or around the top of the map where the reader’s attention will be drawn to first. In contrast, the credits will usually be the smallest, placed at the bottom, and possibly faded to avoid unnecessary attention.

Visual Differences

Here, we deal with the depth and contrast of different objects in the map, called the figure-ground. A 2D map is reimagined as a 3D panel where you have a background (ground), and figures that progressively stand out at each layer, with the top most layer the figure that you wish to highlight the most. There are certain attributes that you can tweak to alter the position of your object in the figure-ground:

  • Contrast: The darker your object is to the background, the greater it stands out.
  • Detail: The more edges your object has, the denser it will look, and the more it will stand out.
  • Edges: The sharper the edge, the more it will stand out. One can fade it out by removing its border and create a gradient from the object to the background.
  • Texture: coarse texture tends to stand out on a smooth background.
  • Layering: Objects that overlap others will tend to stand out more.
  • Shape and size: Large, simple shapes tend to stand out more.
  • Closure: When shapes are closed, the objects will jump out from the ground.
  • Proximity: Objects close together draw more attention.
  • Simplicity: Simple objects tend to stand out more.
  • Direction: Objects aligned in the same orientation tend to form the figure.
  • Familiarity: Recognisable objects tend to jump out
  • Colour: High contrast hues are stronger figures.

Map Generalization and Classification

Maps can contain a lot of details, many of which will draw attention away from your main purpose. A map of a city can contain the contour of its terrain, the multiple roads and buildings, and every little bend in the road. Are all these information necessary in your objective? Can they be simplified, or perhaps, enhanced to fit your needs? A study of road connectivity between to locations may choose to omit buildings, trees, contours and even minor roads from the map, and simplify the lines (2 45 degree angles at a bend may be simplified to a single 90 degree) to make things more readable.

Data can be classified into more recognisable objects. Ever seen a map where train tracks are alternating black and white rectangular boxes, and forest areas are signified by icons of trees stacked adjacent to each other? These are ways to allow the reader to quickly identify the different areas of the maps. In addition, the way you split your data is also important. When mapping household income, one can use a binary classification to indicate people under the poverty line, or use a natural break classification to identify the income gaps.

Map Symbolism

In classifying your map objects, symbols are often required to indicate them. One must consider the familiarity of a symbol to the reader so that the reader is able to identify the classification without looking at the legend. Most mappable data can be mapped as points, lines or areas. Map symbols can even be varied as a river may be a line or an area!

An image taken from “A Visual Guide to Map Design for GIS” by John Krygier and Denis Wood, published by The Guilford Press (2011) highlighting the use of points, lines and areas varied with other attributes

With that out of the way, let’s take a look at some of the work I did. Most of the data displayed in these maps were found from data.gov.sg.

 

What was the objective?

I wanted to know where the dengue hotspots in Singapore were.

Map Pieces

The title is placed at the upper left hand corner, where the reader’s eyes will commonly start at. The legend is placed at the bottom right, when the reader would like to understand in more details the colour in the map.

Visual Differences

The background is white, with the data highlighted in different hues of red, the most severe being the most contrasting to white. The outlines of Singapore could have been made simpler and faded in order to allow the data to stand out more.

Map Generalization and Classification

A simple map outlines was used, more more can be done to simplify the edges and remove non-essential islands (southern islands). Data was classified using natural breaks to identify the regions with the most severe dengue cases.

Map Symbolisation

A hex map is used to display the data as hexagons are easily tiled (as compared to octagons) and are equidistant to adjacent tiles (as compared to squares). This allows the reader to visualise the space better and for every data point to be included.

What was the objective?

I wanted to understand the different map projections.

Map Pieces

Explanatory texts are placed beside each map to indicate the projection used, the attribute it preserves, and what it can be used for. A map title should have been placed at the top.

Visual Differences

Contrast was made between the sea, land, and indicatrix circles, but more contrast could have been better. Indicatrix circles are placed as the top most layer as they are the most important figure to assess the map projection. Borders are placed to divide between the 4 projections.

Map Generalization and Classification

The map is simple enough to be understood, and no data is displayed.

 

What was the objective?

I want to understand different class breaks.

Map Pieces

Map title is the biggest and placed at the top. Each quadrant has its own subtitle which is bigger than the explanatory text. The class break title is the same size as the subtitle to indicate equal importance. Credits are placed at the bottom right to draw the least attention. Legend of each map is placed at the left in the pacific, as it was the largest, unobtrusive space. Borders divide the maps to add clarity, but not around them to reduce distraction.

Visual Differences

The land and sea is now clearly contrasted, as with the sea to the white background. This allows us to see the shape of the projection: the Robinson projection, where aesthetics were more important than area, shape, or distance. Different hues of red were used to indicate how rich a country was, with the richer counties standing out from the poorer ones. In the unique class break, the darker hue was used instead as I wanted to bring attention to countries with 30% of the population under the poverty line. Border lines could have been faded more as they weren’t as important.

Map Generalization and Classification

The outlines of the countries were simplified to lessen the edges but keep the shape of each country recognisable. This brings attention away from the borders and towards the hues of red instead. Data classification is explained in each quadrant.

 

What was the objective?

I want to understand the shift in twitter location data over the years.

Map Pieces

Again, location, size and font of title, explanatory text, credits, and legend was important. We have a new map element that circles a particular area of the map and runs a leader line to the name of the area. The thickness of the lines are kept similar to that of the font, the leader line followed towards the coastline, and the text placed left and right to balance out each other.

Visual Differences

Grey background borders the entire work, with the white landmass as contrast, with a thin coastline to avoid attention. Orange and purple hues were different enough to understand the binary difference between tweets in 2015 and 2012. The darker hue was used to signify a greater extent and allowed us to focus on clusters of areas where these changes happened. The circles used to indicate the different areas were the foremost layer as it was important to understand the general area where the event occurred.

Map Generalization and Classification

Singapore coastline was simplified and central catchments removed. Southern islands could have been removed too. Data was broken into equal breaks to highlight the extent of the change in number of tweets.

 

What was the objective?

I wanted to find out where violent conflicts were happening in Africa.

Map Pieces

Title is large, placed at the top, and has a dark red hue. ‘Nigeria’ as number one is as large and as dark to signify its significance, while ‘Egypt’ is smaller and lighter, but not as ground as the other countries highlighted. Explanatory texts are the next biggest and contrasting to draw the reader’s attention to, followed by the legends, and finally sources. Insets were used to further break down the location of these conflicts in Nigeria and Egypt.

Visual Differences

Hues of red were used to signify bloodshed, contrasted with the grey background from the prior map. Green and blue are complementary colours to red, to stand out and differentiate from each other, stating that they were data on a different scale. Again, darker hues signify greater severity.

Map Generalization and Classification

African borders and coastline were made simpler so as not to distract the reader. Data was broken down using natural breaks to find the areas most affected by the violent conflicts.

Interested to know more? Have questions? You can contact me here.

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