Cartography and an Making Good Maps

Outline of Cartography and an Making Good Maps

1. Why making maps is hard 
2. Parts of a map
3. Good cartographic practice
4. General principles
5. The consequences of maps

Making Maps is Hard!

• The combination of good analysis and good visualisation.
• One without the other makes for a bad map.
• Poor analysis with good visualisation is probably more dangerous.
• It is very easy to make a very bad map!
• QGIS is particularly good for helping you decide on the breaks in your data – Natural Breaks
• https://censusgis.wordpress.com/students/lesson-5- visualisation-cartographic-practice/

• Making Maps is Hard: Krygier and Wood’s Checklist

• What is the map trying to accomplish?
• Do you really need a map?
• Is the map suited to the audience?
• Have you included sufficient attribution information for data sources etc.?
• What are the likely impressions of the map?
• Are the data appropriate for the map’s purpose?
• Does the symbolisation reflect the character of the phenomenon/ data?
• Is the level of generalisation appropriate?
• Implications of the origins of the data?
• Is the map suited to the audience? Have you included sufficient attribution information for data sources etc.?
• What are the likely impressions of the map?
• Are the data appropriate for the map’s purpose?Does the symbolisation reflect the character of the phenomenon/ data?

Making Maps is Hard: Krygier and Wood’s Checklist

• Data quality/ accuracy.
• Copyright or copyleft?
• Appropriate projection and Coordinate reference system?
• Does title indicate what, when where?
• Does textual information add anything?
• Does the legend include symbols that are not self-explanatory?
• North arrow?
• Do variations in design reflect variations in data?
• Context of the map clear?
• Is the typeface appropriate?
• Is colour being used effectively?

Good Cartographic Practice - Map Scale and Orientation

• Numerical: 1:100,000
• Visual: 10km
• Verbal: 1cm= 10km
• Always good to show direction (conventionally North).
• Can be implied by graticule (lat long grid).

Good Cartographic Practice - Text & Legends

• Title
• Data source
• Attribution
• Copyright
• Labels
• Extra context

Cartograms

• Good for multivariate data
• Can emphasise areas of the map of interest (often where people live).
• Use one variable for colour, the other for scaling
• Gastner-Newman a popular algorithm
• Can be hard to interpret
• Alternatives can be the graphical legend shown earlier

Faceting

• Good for multivariate data eg temporal.
• Facilitates display of large volumes of information.
• Allows visual comparison between maps.
• Can produce v. large plots.
• Should avoid cramming too much on a page.

General Principles

• Less can be more.
• But avoid over-simplification.

General Principles

• It is sometimes acceptable to break the rules
• How does your map compare to maps you admire or have been impressed by?
• The ultimate question to ask is “does it look right?”

Consequences of Mapping

• Being able to create a map places you in a position of power.
• This comes with responsibility.
• How will the map be (mis)interpreted?

Conclusions

• Good maps expand minds, improve perceptions and have a positive impact.
• Good maps demonstrate your data and analysis.
• Poor maps render them irrelevant.
• Maps place you in a position of power...so get them right!