- Download and install Inkscape
- Export a map you made in ArcMap as an .svg
- Open Inkscape
- File > Import > yourmap.svg
- Use shift + in Inkscape to zoom in
- If you had more than one layer in your map, view the different layers using the Layer > layer dialog
- Use Path > Trace bitmap with a layer selected if you want to smooth lines. For example, if I have some really detailed river lines that I want to smooth for a lower resolution map, I use the layer dialog to select the river lines (alternatively you can try selecting them via point, click but sometimes you end up selecting the wrong layer), then use Path > simplify
- Experiment with the filters menu on the entire finished map to produce unusual visual effects.
Map Making Tips, Tricks, and Inspiration
Some Friday reading for you.
- 18 Maps from when the world though California was an island. From Wired’s Map Lab.
- State of the Map US 2014 presentation videos. Each talk link leads you to the abstract and video.
- Map Worlds: A History of Women in Cartography. Published in 2013 but just coming to my attention now via @rosemarydaley.
- Daniel Huffman’s Blender Video Tutorial. A method for building shaded relief. Hat tip @rrlash.
- Thoughts from State of the Map US 2014. My thoughts, published over on the Boundless blog.
I was staring at some carpet in my house this morning as I drank my morning tea. I like this particular carpet. However, if you look at it really closely and actually think about that carpet, it wouldn’t be obvious that it would be a nice carpet. Somebody, at some carpet design studio (is there such a thing?) would have had to think, “a light tan with some specks of black will look good,” and then this person or team would have had to present it to the boss.
Can you imagine thinking that a light tan color with specks of black in it would look good as a floor covering? The immediate thought, when in a logical mindset, would be to say that nobody in their right mind would install that on their floor because it would appear as if it were dirty right from the start! But when you do install it, logic defies and it actually looks very good.
So my take-away is to try to see a design from all angles, be broad minded, test in real life situations, and realize that what might seem perfectly logical might end up perfectly wrong.
On my mind today were two little nuggets from Inc Magazine’s April 2014 issue that got me thinking.
Keeping Those Mapping Skills Fresh
The first is a question, or actually, part of a question that goes like this, “Which customers can’t participate in our market because they lack skills?” It struck me as both a very obvious question to ask yourself as a business owner and a completely novel concept. It should be obvious to ask this question but it just isn’t asked very often.
I wouldn’t normally even write about this question on a blog about cartography except for one thing: it’s a question that hits home to traditional cartographers. Do we lack a skill that’s necessary for making maps in the modern era? If I’m adept at finding data, analyzing data, using a GIS program, and perhaps even in manipulating the GIS output in a graphics software, shouldn’t that be enough? Why should I invest my time learning new tools, which are heavily focused on web design, that are being developed? Because if you don’t, you won’t be able to participate in the new cartographic market, that’s why.
Safe or Stifling?
Another bit in the magazine espoused the ideals of providing a safe environment for exchanging ideas within your workgroup. Two articles describe how to produce this “safe environment” and, surprise surprise, they contradict one another. One of the articles talks about never knocking down the ideas of others. Another article talks about making it so people know they won’t be taken to task for what they say. If you have a culture of never questioning ideas then you have a culture where nobody knows if something’s actually good or if your peers are simply putting on a polite facade. If nobody’s ever taken to task then things could get ugly.
And what does all that have to do with cartography? It poses the possibility that there are multiple ways to allow critical feedback on a map design, an analysis, data inputs, and the like. As a profession, we are in desperate need of critical feedback. Some of that happens in social media today, such as on twitter. (If you want to know how people really feel about that map, post it on twitter but have a thick skin.) What seems to the designer like a fabulous idea–renaming every U.S. state for a beer brand let’s say–might be met with derision from the crowd.
Some say that criticism kills innovation. If you have too many people telling you that beer map is terrible then you might never come up with another map idea in your life. But if we never allow criticism in the workplace then we risk putting out a bunch of beer maps. Is there a way to win here?
Geogit is a tool made just for me. Despite my best intentions, there are times when data file names get the best of me. These times are lamentable because when the inevitable moment arrives when I have to comb through a series of files in order to find the one that is the most correct or the most current, I’ll find something like this:
Or worse. Maybe later on down the line, during that complex interpolation project last year, I decided that this analytical method was sub-optimum and went with natural neighbor instead. So then there’s a series of “natural_neighbor” prefixed datasets in the same vein to sort through. After a year goes by it’s hard to know which one was the end result. Which one had the fewest errors. Which one is the most authoritative.
And with multi-person teams things get more complex. Maybe the intern added 5,000 septic system points to the wrong database and you don’t have an easy way to undo it.
It has more benefits than solving the above problems but these are the ones that hit home to me the most at this, the beginning stages of my geogit learning journey.
Hey, guess what? I started a new position this week at Boundless. I’m absolutely thrilled to be a part of such a great team. Learning about geogit is one of the first things I get to do. I can’t complain.
I bill myself as a data scientist. After all, 50% of any GIS or cartography project, in general, involves data wrangling. Knowledge of statistics and geo-specific analytics is imperative to getting complex maps right. Of course, as with many tech fields, tools are always changing and there always seems to be something new to learn.
However, I take issue with this little snippet in Sunday’s NY Times from David J. Hand. When speaking about geographic clusters* he wags his finger at us and pontificates, “…if you do see such a cluster, then you should work out the chance that you would see such a cluster purely randomly, purely by chance, and if it’s very low odds, then you should investigate it carefully.” See the short article here.
Granted, he’s probably reacting to the surfeit of maps that have been circulating the internet claiming to prove this, that or the other, when in fact they are mostly bogus. For example, Kenneth Fields tweeted this abomination this morning:
— Kenneth Field (@kennethfield) February 24, 2014
Jonah Atkins has created a github location for sharing remedies to bad maps like the above called Amazing-Er-Maps (this is itself in reaction to the name “Amazing Maps,” which has been given to a twitter account that showcases maps of questionable quality at times.)
Amazing-Er-Maps, as I understand it, is a place for you to upload a folder that contains the link to a bad map and a new map that is similar but does a better job. You include the data and the map as well as any code that goes with it. It’s a fabulous idea. Don’t just complain about bad maps, seek to make them better in a way that the whole community can gain inspiration from and learn from. Check it out, Jonah’s already got it going with several fun examples. Super warm-fuzzies.
Circling back to Mr. Hand, he has a point: we need to apply sound statistical and mathematical reasoning to our datasets and the maps we make from them. For example, when I was helping the Hood Canal Coordinating Council map septic system points, I didn’t just provide maps for them to visually inspect for clusters of too-old septics, I produced a map of statistically significant clusters of the too-old septics using hierarchical nearest neighbor clustering, which provides a confidence level for the chance that the cluster could be random.
The point is, those who are already practicing sound data mapping practices don’t like to be lumped in with the creators of maps that are produced–let’s face it–as sensational products. Our little map community is challenging those bad maps out there, creating great ones for our clients and bosses, and continuing to learn to make them better. Give us a bit more credit here and check out some of the really amazing things we’ve done.
*On an exciting note, “geographic clusters” makes main-stream news media!