Penrose Binning

Some months ago, I came up with a little joking idea: what if, instead of hexagonal or square bins, cartographers used Penrose tiles?

A Penrose tiling is a form of tessellation. It’s fun and unique in that it fills the entire plane, but has no repeats. Wikipedia has more detail about how these things are cool. Mostly, I thought of them because they look interesting and are sort of regular, without being too regular.

So for fun, I made a couple of maps using Penrose bins.

Density [Converted]-01

Population Density

US/Canada Atlas of Design sales

US/Canada Atlas of Design sales

Land Cover

Land Cover

I can think of no proper cartographic use for Penrose binning, but it’s fun to look at, and so that’s good enough for me.

To create the tiles, I found an SVG of a Penrose tiling here: Then I pulled it into QGIS and resized it to fit appropriately on the US and part of Canada when in an Albers Equal Area conic (CM: -96º, SP1: 20º, SP 2: 60º). Then I did zonal statistics in ArcMap (for population density and land cover) or a spatial join in QGIS (for the point data of Atlas of Design sales).

If you want to give it a try yourself, I’ve put the shapefile here:

While I can’t think of a use for this presently, who knows what the future will hold? Silly little experiments like this sometimes become valuable later on.

The Immanent Textbook

I use Twitter mostly, so this is my only medium in which to share thoughts that exceed 140 characters. I usually only put self-contained, finished pieces here, but today I’m going to just toss out a few random musings (also I’m sick and have not slept much for 4 days, so forgive any incoherence).

What if we made a cartography “textbook” based almost entirely on existing online content?

Most days, I find some cool mapping-related thing on my Twitter feed. Practical mapmaking advice, bigger-picture criticism/analysis of cartography, etc. Something which aims to educate and enlighten (I like to think that a few of the posts on this blog could likewise be described this way, too).

There’s all kinds of good sharable stuff out there, and it got me to thinking: what if we compiled it all into an intro cartography guide? I get emails from people who ask me how they can get started learning mapping, and I never have a useful answer other than, “go to a university like I did.” But that should not be the only answer, especially when we look at, for example, how many people learn coding by reading free online resources.

The advantage to using existing content is it means that no one really has to write anything new. I suspect that, scattered around the Web (blogs, free online journals like Cartographic Perspectives, Wikipedia, etc.), there’s pretty much everything someone needs to know to get a decent start to quality mapmaking. It just needs to be curated and compiled.

Specifically, it needs experts from the community to:

  1. decide what subjects should go in the textbook, in what order;
  2. track down existing writings that address these subjects;
  3. occasionally flesh out the skeleton by writing a small amount of material to connect pieces together, or introduce broad themes; and
  4. maybe come up with some practical exercises so that people can put this stuff into practice.

I don’t know, maybe this has all already been thought through and is underway somewhere else. There are certainly various useful lists of map resources out there that I’ve seen, but I don’t think any of them cover everything needed to go from zero to “capable of making a variety of decent maps.”

Certainly, the end result won’t be the same as a coherent text written by a focused author (or group of authors), and the student must be willing to put up with the patchwork nature of the guide, but I think it would fulfill a need nonetheless. Plenty of people want to learn mapping but don’t have access to formal channels.

Also, this idea seems like a lot of work, and I am overburdened already and likely can’t do most of the lifting myself. Maybe just provide counsel and big-picture input. But someone awesome should take this on and perhaps brand it as a revival of my forgotten NACIS Initiative for Cartographic Education. I feel like if we all get together on this, it wouldn’t be a lot of work.

Anyway, scattered thoughts from the mind of a convalescent.

Adding Shaded Relief in Photoshop

I’ve had occasion, from time to time, to show my colleagues in the UW Cartography Lab the technique I use to combine shaded relief with other map layers in Photoshop. After a recent request to share the technique again, I decided to make a video, so that people can watch at their own convenience. So, if you’re interested in this:


then watch this:

(make sure to view in HD, so you can see the details I’m talking about). If you’d like, you can also follow along with the same file I’m using:

Tricks from the Historical Atlas of Canada

I’m constantly assembling, in my mind, a toolkit built out of little tricks that I see other cartographers pull off. I take pleasure in the small things. The big picture is important, and certainly we need to focus on telling a clear story that looks great, but it is the details that always interest me most: a well-done coastal effect, great typography, or a smart tweak to an old, standard symbology.

In that spirit, I’d like to take a minute to promote a couple of nice ideas which come from the Historical Atlas of Canada. Geoffrey Matthews served as the Cartographic Editor for its three volumes, the last of which was published in 1993. During my introductory cartography course, the instructor pointed to it as an example of one of the final great works of the manual cartography era, and I have found things to appreciate in it ever since.

There are three nice things I’d like to share…

In-Situ Insets

In-Situ 1
In-Situ 2

In-Situ 3

In-situ insets” is a term I just made up to explain what’s going on above. Maybe it has a real, accepted term already. Perhaps you could call it “lensing” instead? It is as a magnifying glass, dropped over the terrain. Instead of separate inset maps that zoom in on areas like Vancouver or Toronto, the authors expand these areas and then plop them right down in the middle of the map, covering part of the basemap. For comparison, here’s a map of Canada all at the same scale that I swiped from Wikipedia.


Admittedly, the geography of Canada helps the authors here. There’s not much going on nearby that needs to be shown for the stories they’re trying to tell, so it can be safely covered up. Creating in-situ insets requires some fortunate circumstances, but when they come together, I think it’s a fabulous idea. I think forcing people’s eyes to shift to a separate inset map is disruptive and reduces their appreciation for the spatial context you’re trying to show. Keeping everything in one place, on one map, is more coherent.

Non-boxed Insets

Sometimes, instead of an in-situ inset, the authors do something like this:

Inset 1

Inset 2

The greyed out section of the main map and the arrow to the inset create a strong, nice-looking connection. So often, when we want to make an inset map, we end up putting it in a box, separated from the main map by a line. But I’m wary of introducing extra dividing lines into a map layout; I think it’s done way too often, and it prevents the various page elements from being seen as a coherent whole. The setup above is a nice way to have an inset without having to separate it from the main map. It is seen more clearly in its spatial context.

I’m not sure how I feel about the extruded, pseudo-3D perspective, but I expect this idea would work just as well in 2D.

Gridded Proportional Symbols

Finally, something nice that has nothing to do with insets. I like the Historical Atlas of Canada‘s use of proportional symbols that are gridded, so that they can be be easily broken down into countable units. Here’s an example:


In many maps, these would simply be treated as proportional squares or lines, but in the Atlas, they’re broken up into units (I’ve seen the New York Times do similar). So, a reader can look at the whole and make a quick comparison, or they can take a moment to actually start counting if they’d like to dig out the actual number. Normally it’s very difficult for a reader to get an estimated value from a proportional symbol, but the grid makes it much easier. I like to call these “aggregate symbols,” as they’re proportional symbols built out of many individual pieces.

Here’s a second example, which we saw in the last section:


This map takes things a step farther and color-codes the units, adding another layer of data that, importantly, doesn’t interfere with the big picture. If you want to see the overall pattern, you can just look for the tallest stacks. If you want to dig deeper, more data are there, but they’re not in the way. It can be read at multiple levels, which is quite an excellent goal to aim for.

So there you go! A few nice tricks from a great product. They’re little things, but I think that small details is what a lot of good mapmaking comes down to.


Atlas of Design 2014

Friends, as many of you know, I am one of the Editors of the Atlas of Design, which is a book which NACIS publishes every two years. It’s a showcase of some of the best and most beautiful cartography around the world. We’ve recently opened submissions for the 2014 edition, and I very much hope you’ll think about submitting your work to us. Visit for more details.

Also, I hope you’ll help us in spreading the word. The more people we reach, the better sample of maps we’ll have, and the better final volume we’ll produce. I would also especially like to ask for your help in reaching people outside the English-speaking world. We’d like this to be a book about great cartography throughout the globe. Our call for submissions and our submissions form are, thanks to some awesome volunteers, available in a dozen other languages.  While our volunteers make it possible to communicate outside of English,  we need help in reaching out to mapmakers who speak those languages. I and my fellow editors are based in the US, and our colleagues and professional contacts are primarily in the English-speaking world. If you can help us expand beyond that sphere by alerting your colleagues, posting in non-English forums, etc., we’d be much appreciative. We know it’s going to take time, but we’d like the Atlas of Design to represent the maps all of us make, no matter where we are.

Blender Tutorial

As promised several months ago, I’ve finally put together some instructions on how to create shaded relief using Blender. I’ve created a 72-minute, six-part video series that walks you through the process (don’t worry; it doesn’t take that long to do it every time, just your first time). Please share it around! I’d love to see other people making use of this technique, and extending it beyond what I’ve done.

NOTE 1: This video series picks up with the assumption that you have a DEM ready to go. If you need help first getting your DEM ready, you should follow this tutorial by Katie Kowalsky.

NOTE 2: Since I put together this video series, some of my colleagues have made some great contributions that you should be aware of. First off, Ryan Lash (@RRLash) has put together an awesome step-by-step explanation of everything that goes on in the videos, so that you don’t have to hunt around to find the step you missed: Second, check out the comments below. Morgan Hite has been using BlenderGIS to ease some of the issues with Blender not handling spatial data natively, and he’s put together a description of his basic workflow. I’m very happy that people are using and, more importantly, extending the material I’ve put together her.

Make sure you’re watching these in HD, otherwise you may have trouble following along when I click buttons. If you want to follow along with the DEM I am using, get it here:

Meanwhile, if you just want to look at pretty things, here’s the relief I made during the tutorials:


Blending my Way to Relief

Throughout my brief cartographic career, I’ve been a fan of shaded relief, but I’ve also struggled to create one that I found satisfactory. I haven’t had the time to learn how to draw relief manually, and so I rely on the old standard digital hillshade algorithm, plus the judicious application of Photoshop (having learned from folks like Tom Patterson and Tanya Buckingham how big of a difference it can make). I’ve also posted here on some efforts to do a bit of spatial analysis to improve the end result. But, I am still often dissatisfied with the final product.

Lately, though, I’ve been experimenting with something that I think could represent a substantial improvement over the standard techniques for doing a digital hillshade. I’ve been messing around with Blender, a free 3D modeling program.

I got started with Blender because I wanted to do some oblique terrain maps (a la Natural Scene Designer), and because I also wanted to do some 3D printing for a project I’m working on. But I also realized it might be the solution for shaded relief. So, I used a DEM to create a 3D terrain mesh inside Blender, then positioned my camera directly above it, and started doing some rendering. Here’s what I’ve gotten so far.

First off, here’s one that mimics what you’d get out of ArcMap or some other standard GIS algorithm. Nothing special, but it’s a good starting point for comparison.


A fairly plain effort that looks much like a standard hillshade

It’s pretty plain. The standard hillshade algorithm looks at each pixel, determines its slope and aspect, and uses that to figure out how bright it should be. That’s about it. It doesn’t look at where each pixel sits in the context of its surroundings, or figure out how light bounces around or causes shadows. It produces decent results, but it’s pretty simple and unrealistic. So, let’s add some more realism:

With some basic lighting effects added

With some basic lighting effects added

This one is much better. All I’ve done here is turn on two things: shadows and light bounces. Places facing away from the sun are now in shadow, with the shadow length depending on the height of the terrain. The light bounces allow us to still see the shadowed areas, though. Blender figures out that the backside of the mountain, while not receiving direct sun, will still be illuminated by light striking nearby ridges and scattering around. So, it traces the path of the light rays and determines how light moves around the scene to create a much more realistic result. In ArcMap, you can turn on shadows in your shaded relief, but it just makes everything black if it’s caught in a shadow; it’s not equipped to re-light those shadows by looking at light scattering.

We can also change our light angle, or strength, to simulate different times of day. Here’s one with a low sun angle, coming from the west.

Mount Rainier at dusk

Mount Rainier at dusk

Again, you could aim for something like this in a GIS program, but it’s not likely to turn out quite so nicely, because it doesn’t have the ability to calculate the way light bounces around and dimly illuminates those east-facing slopes. They’d just be in a solid black shadow. Or, if you didn’t turn on shadows, they’d be lit as though the mountain isn’t in the way.

There are a lot of parameters you can change in Blender that simply aren’t available in a GIS program, as well. We can, for example, add a second light source. Here’s the same image as above, except with some moonlight coming from the southwest:

With moonlight

With moonlight

We can also do things like adjust the “size” of the sun, giving us more of a point-light effect, as though we’re on a planet without an atmosphere to spread out the incoming rays:


A harshly-lit landscape

Now it’s as though we’re on the moon, or some other harshly-lit place, with much sharper shadows.

Finally, my favorite is probably this one:

A more sketched look

A softer, more sketched look

I think it looks the closest to a handmade relief. It’s still not the same, but it’s probably the closest I’ve seen an automated algorithm come to something human-produced. It’s got a nice fuzziness that comes from turning down the number of light paths that Blender calculates. I’ve also made the surface smoother, which gives it a bit more specular reflectivity and produces an interesting effect that I quite like. Since we’re working in a 3D modeling program, we can change what material the surface is made from, if we want to try interesting things. Here’s one more where I’ve made the terrain out of a glossy material, instead:

A shinier terrain

A shiny world

In the end, I think this could be the way to go for a lot of my future shaded relief needs. It does, admittedly, take longer to accomplish. Each test render can take several minutes. But I think the quality is a lot higher. I don’t think this is necessarily the be-all, end-all, last word in doing automated relief. It could probably be improved further via some of the same techniques people use to improve standard GIS hillshades. But I think it’s a better foundation than the standard algorithm, and I’m looking forward to playing around with it more.

At some point in the future, I’m hoping to put together instructional materials on using Blender for shaded relief. But I don’t think I’m quite ready yet. I don’t know the program well enough to be able to say that I’m doing things in the most efficient and effective manner, and I haven’t quite pieced together the best way to explain everything clearly. In the meanwhile, I encourage you all to experiment with it, and to tell me if you’ve tried anything similar in the past. I imagine I’m not the first to think of this.