A Beginner’s Guide to Map Making

I’m going to start this off by asking a very simple question: What is a map? My personal answer is that it’s that piece of paper in my glovebox that I scramble for when my cell phone dies. Pithy jokes aside, a map is a 2D representation of a 3D object that symbolically displays the spatial relationship of objects. While many will probably think of a road or trail map, a map can represent any space. For the purposes of this post I’m going focus exclusively on geographic maps.

Subway map of Seoul and surrounding areas. This must be a lot of fun to navigate during rush hour.

Cartography is the art and science of making geographic maps. From the humble “You are Here” maps in shopping malls, up to the intricately detailed geologic map of Mars, geographic maps tell you where you are in the world in relation to other objects. As mentioned previously, they are purpose built to convey spatial information.

In general, geographic mapping is divided into two broad categories: General, and Thematic. General maps are, as the name implies, constructed for a generalized, non-technical audience. Topographic relief (or ‘Topo Maps” for short) are one the most prevalent examples of general maps and are often produced as part of a series (for example, the full topographic map of Alberta might be composed of several smaller topographic maps). Thematic maps are designed are the representation of a particular theme. Examples of thematic maps include a dot map showing textile production in Ontario, or a choropleth map of California showing levels of smog. A choropleth map, incidentally, is a map in which geographic regions are shaded in relation to given data statisitic. Chorpleth maps are commonly termed “heat maps”, however this is technically incorrect as heat maps refers to a specific type of a map in which shading intensity/color is INDEPENDENT of geographic relationships.

Now that we have the basic information of what a map is, it’s time to actually start laying out all the things you’ll need to make a map. Before we go on to projections, it might be a good idea to define what basic elements a work needs in order to qualify as a map. In general a map must have:

• Data Frame: The substance of the map itself. This is the information that you are trying to communicate
• A Legend: The legend tells what each symbol/data category represents. An accurate legend is vital to properly communicating you information. A choropleth map of say, Oregon, without a legend, could represent anything. It could represent amount of lead in drinking water per geographic region, or it could be looking at how many laser-armed sharks exist in each region. These examples assume you don’t have a title, but the sentiment remains the same. Speaking of which…
• Title: A title should give the viewer a quick, succinct description of your map. Without a title, deciphering what information you’re trying to convey becomes a lot more difficult.
• A Compass Rose/North Arrow: A compass rose/north arrow provides a reference direction for orientation. Without one, a user who has no previous information of your area has no way of knowing in what direction objects lie in relation to one another.
• A Scale Bar: A scale bar gives you the relationship of the extent of your data to real-world distances. A scale bar is typically expressed as a ratio (1:10,000) or as a graphical, black/white bar. The ratio format tends to be more common as it is dimensionless. No matter what object you use to measure with, be it erasers or salmon, the ratio of distances remains the same.

Before delving into map projections, a quick note about data. When take in data from the real world (elevation, longitude/latitude data, etc.), our data is in a polar format. In a polar co-ordinate system, our location is determined relative to some pole P. We need to convert are data in a linear, (X,Y,Z) format. This is known as a Cartesian co-ordinate system, and it shows distance and relationships of data points on a 2D plane.

Once you have all these elements, and the data you wish to represent, the final thing you’ll need is to do is choose your projection type. The projection type you choose can make or break your map as certain projections work well with certain types of data, but others may misrepresent your data or even flat out distort it. Speaking of which, let’s talk about distortion. Carl Friedrich Gauss showed that you will always have distortion when modeling a 3D object (like a sphere) with a 2D map. As such there is no “perfect” projection. You will always end up with distortion, no matter which projection you choose. Therefore, the trick is finding the projection that maximizes data conveyance, while minimizing data distortion. You’ll have to experiment with your data and map projections to get the one that best suits your needs.

This is a very VERY general overview of maps, and the fundamentals of map making in general. On the next installment, we’ll be delving into the wide world of Geographic Information Systems.