Maps and mappers of the 2019 calendar: Kenneth Field, Cover

Q: Tell us about yourself.

A: I’m Ken, I’m a bit of a cartonerd. For the last 8 years I’ve allowed Esri to pay me to work for them. Technically I’m a ‘Senior Software Product Engineer’ but more informally I make maps, write about maps, talk about maps, teach about making maps and generally make myself a nuisance wherever there’s an opinion to be shared about, you guessed it, maps. Prior to working for the California-based Geogoliathon I spent around 20 years as an academic in UK universities teaching cartography, GIS, and geography. I’ve recently had a book published called (wait for it) Cartography. And developed a free Massive Open Online Course (#cartoMOOC) on the same subject which we’ve taught to 70,000 people and counting. My passion and profession align in my geo-lifestyle. I blog at cartonerd, and the ICA Commission on Map Design, and tweet @kennethfield. I play the drums (badly), like riding my snowboard in the mountains (with map-themed helmet, goggles and jacket of course), and for my sins I am an avid supporter of Nottingham Forest FC.

Q: Tell us the story behind your map (what inspired you to make it, what did you learn while making it, or any other aspects of the map or its creation you would like people to know).

A: I’m always looking for interesting mapping themes. Normally these would involve the search for digital data that has to be persuaded and cajoled into some sort of map. I like to show people how to make great maps, sometimes just solid techniques done well, other times something a bit weird and wonderful to push the envelope, break a few rules and get creative. But I also like to use different mediums for making a map whether using Lego, pen and ink or…cheese. And these sort of maps are the ones that tend to stick in the memory because they’re different. They don’t conform. I was inspired by a map of English biscuits made by Chris Wesson a couple of years ago. It was a map of the UK with pictures of all sorts of tasty biscuits, where they were from and a little of their history. It was a great map but I couldn’t help think Chris might have actually made a large map as some sort of tablecloth and put real biscuits on top. And that’s when I thought of taking the basic idea and applying the concept to the UK cheese. Cartography is often about stealing ideas and then fashioning something new or interesting out of them and, so, I set about thinking through the map. It was an obvious approach really – I’d need a cheese board. I’d need it in the shape of the UK. And on top I’d place a selection of fine, rare, important or bizarre cheese. I’d take a picture and then people will eat the map…and the map would disappear. It’d be a one-time edible map. I researched the history of UK cheese production. I sought to identify a good geographical mix and from a list of around 400 cheeses I whittled it down to around 30 which would fit on a map.

Q: Tell us about the tools, data, etc., you used to make the map.

A: The map was fairly simple in design – just ceremonial counties of the UK. I made it in ArcGIS Pro and exported it as an svg file. By now I’d realised that I didn’t have the tools or experience to whittle the wood myself. I found a great craftsman called Andrew Abbott who had a CNC router and laser engraver. He took my design and made the map out of laminated blocks of Maple. We discussed all sorts of design aspects. He advised on what would work typographically at the scale of the final board. I was also planning on making the Isle of Man into a hole in the board but he suggested bits of cheese would simply fall through and get stuck…so I adapted the design accordingly. I also needed to do some really hefty generalisation on the coastline and internal boundaries so the laser engraver would work well – there simply wasn’t the space for overly complicated linework. It was a really good process to work together to ensure the design would work in the medium he was crafting.

I ended up with a cheese board around a metre tall and nearly as wide. Space for around 30-40 pieces of cheese. Sourcing the cheese wasn’t as simple as nipping to the local supermarket. The selection simply isn’t broad enough and some of the hard to get cheeses had to be sourced from niche artisanal suppliers. Some cheese was out of production (being seasonal), some impossible to source and some just not available in a quantity that would work. I eventually used a series of suppliers, had the cheese sent to my brother’s house in the UK as close to its eventual use as possible. I boarded a flight to the UK with my cheese board well packaged as excess baggage. It arrived in the UK undamaged. My brother drove the cheese to London from his home in Lincolnshire the day before it was to be displayed and I got the board and cheese across London to the Geovation hub one evening in September 2018 to display at the #geomob event. Cheese unwrapped, positioned according to a geographical list I’d prepared to ensure I didn’t make a mess of locating each piece, added a few labels and some context and sat back to watch a hungry crowd devour it. I wrote up a more extensive blog about the map here and there’s a bit on the GeoHipster blog here.

What next? Well, I quite like craft beer and there’s definitely geo in that. And someone suggested whiskey, except I can’t stand the stuff. Never have been able to drink it after a very unfortunate incident in my younger days. That’s another story entirely.

 

Maps and mappers of the 2018 calendar: Kate Keeley

Q: Tell us about yourself.

A: I always thought I was going to be a scientist and had a brief stint as researcher and field biologist. Then I decided I liked communicating science to the public more, and worked as an interpretive park ranger and zoo education specialist. And then I discovered GIS and the rest was history. With GIS, I found a tool that combined my technical side with my eye for design and an opportunity to communicate complex subjects in new and innovative ways.

A recent master’s graduate from the University of Michigan, I now work as a GIS consultant for an environmental consulting firm in Michigan and I couldn’t be happier. Say hi to @pokateo_ on Twitter (that’s po-kate-o like potato. Get it? I like potatoes)! Or mosey over to my website at https://kateberg.github.io/ to learn more about my journey.

Q: Tell us the story behind your map (what inspired you to make it, what did you learn while making it, or any other aspects of the map or its creation you would like people to know).

A: I stumbled across the Gallup-Sharecare Well-Being reports and immediately thought of making a map using a scale of happy to sad faces (sort of inspired by recently reading John Nelson’s suggestion in his latest ArcGIS blog post to use Chernoff faces for symbology). A quick Google search of PNG faces led me immediately to a bunch of cutouts of celebrity faces and I knew that’s what I wanted to use. I found faces with a variety of different emotions, from smiling to meh to frowning to crying and played around with a scale that made sense to me.

Q: Tell us about the tools, data, etc., you used to make the map.

A: I worked in ArcGIS Pro. I used my cubic tessellations I created for another project (also inspired by John Nelson. This time his Electo-Cubo-Grams) as the base (that was a whole other challenge; trying to fit all the states into a general US shape was quite difficult). With my base layers from that project, each state had its own point. Then, I uploaded the face PNGs as the point symbology for each state and went from there.

I was really excited by how it was shaping up, but I shared it with a couple of friends and they weren’t too keen on it. They said it [was] actually quite frightening:

(https://kateberg.github.io/img/Wellbeing/wellbeing1.png)

They said I should stop what I was doing and burn it with fire.

I was undeterred. Perhaps I was blind or a bit abstracted, but I still thought what I was doing was pretty cool.

I played with different ways to make the heads less creepy:

https://kateberg.github.io/img/Wellbeing/wellbeing2.png

https://kateberg.github.io/img/Wellbeing/wellbeing3.png

https://kateberg.github.io/img/Wellbeing/wellbeing4.png

https://kateberg.github.io/img/Wellbeing/wellbeing5.png

I noticed that the overall pattern of states’ well-being changed depending on the component (e.g. purpose, social, financial), so I wanted to find a way to include those patterns, without making the map look extra complicated (or creepy as it were). I found using the colored circles on the right to be a great way to provide a quick glance of the interesting patterns! Overall, I think the final result came out pretty neat and I’m very proud of it being selected for the GeoHipster Calendar!  You can read more at: https://kateberg.github.io/portfolio/wellbeing.html

 

Maps and mappers of the 2018 GeoHipster calendar — Atanas Entchev, October

Q: Tell us about yourself.

A: I am an architect and urban planner by training, and GISer by circumstance since 1991. I founded ENTCHEV GIS in 2005 and GeoHipster in 2013. Currently (since 2015) I am the GIS specialist for Franklin Township, NJ. Read more about me in my GeoHipster interview.

Q: Tell us the story behind your map (what inspired you to make it, what did you learn while making it, or any other aspects of the map or its creation you would like people to know).

A: This map is one in a series offering visual representation of all reported animal-vehicle crashes in Franklin Township over the course of several years. The map series informs environmental policy decisions in the town, particularly with regard to hunting regulations. I felt that discrete representation of point events was not communicating well the story behind the data, being that many animal crashes locations were concentrated in tight clusters — hence my choice of heat mapping for the series. I learned that deer population moves over time, which is probably obvious, but I never thought about it before.

Q: Tell us about the tools, data, etc., you used to make the map.

A: The map uses data from police reports. The project started in a MapInfo derivative, moved to QGIS, then ArcMap, then Paint.net. Data was originally created in MapInfo TAB, moved to SHP (hi, @shapefile! 🙂 ), then to GeoTIFF, to PNG, to PDN, to PNG, ultimately to PDF (of course!).

 

Maps and mappers of the 2018 GeoHipster calendar: Nathaniel Jeffrey, September

Q: Tell us about yourself.

I’ve been making maps professionally for over 10 years now.  But when I’m not doing that, I could be cooking, messing around in VR (how exactly do you ingest geojson into Unity, anyway?), or running about as fast as the world’s fastest 90 year old.  Seriously, I looked it up; his name is Frederico Fischer. My sprinting pace is terrible, but it keeps my legs thicc at least.

Q: Tell us the story behind your map (what inspired you to make it, what did you learn while making it, or any other aspects of the map or its creation you would like people to know).

Oh hey, speaking of running – my boss had the idea for this map while he was training for his first marathon.  He came into work on Monday and explained how cool it would be if we could produce a map that showed the bounding boxes of every map our business had ever made.  I agreed that it would indeed be cool. Then I promptly forgot about it.

Working on something completely unrelated a couple of months later, which required me to programmatically extract the coordinates at the corners of some map documents, I was reminded of his idea.  A bit of Python frankenscripting later – with StackExchange acting as Igor – and I was able to unleash this on our entire corporate directory of map files. Turns out, in ten years of using our current GIS, we’ve collectively authored over eighty thousand maps.

Zooming in to Melbourne (which accounted for 30,000+ maps on its own), I started to play around with layered transparencies to visualise the data.  This eventually evolved into a nice glowy blue colour scheme, which reminded me of deep space images of clusters of stars and galaxies, connected by glowing filaments.

This map has no practical use.  I’m fine with that. There’s still something really satisfying about it, how it just hints at the tens of thousands of hours of work that went in to making all of those maps, which are reduced down to their most basic representation.  It looks nice too (I think). If you got a GeoHipster calendar, I hope you think so too, because you’re stuck with it for this month.

Q: Tell us about the tools, data, etc., you used to make the map.

To scrape the data: A simple, custom Python script, run over a big and messy nested directory structure, full of .mxd files.  It extracted the x/y min/max coordinates of every map document, and reconstituted them into a shapefile full of rectangles.

To visualise the data: A mixture of ArcGIS Pro (I love the feature-level transparency), InkScape, and Paint.net.  

 

Maps and mappers of the 2018 GeoHipster calendar: Topi Tjukanov, August

Q: Tell us about yourself.

A: I’m a geospatial geek from Finland. I do this kind of visualization for fun and as a freelancing work. You can read more about me from this GeoHipster interview: http://geohipster.com/2018/04/16/topi-tjukanov-in-finnish-basemaps-forest-is-white/

Q: Tell us the story behind your map (what inspired you to make it, what did you learn while making it, or any other aspects of the map or its creation you would like people to know).

A: I originally saw the Roads to Rome project from moovel Lab and was really inspired by that. I wanted to recreate that with my own tools. I had already done a few similar maps before this, but this one was custom made for the GeoHipster calendar submissions! While making the map I learned a lot more about Python. Basically before venturing into this, my Python skills were almost non-existent, but this was a great way to learn as I had a clear goal in mind. Writing the simple script for the API calls was a small step for mankind, but a big step for me. I wanted to keep the style really simple and clean so I didn’t want to add anything else than the routes and graticules on the final map.

Q: Tell us about the tools, data, etc., you used to make the map.

A: The data is from OpenStreetMap. Routing is done with the great GraphHopper open source routing engine. GPX routes were then stored into a single PostGIS table and visualized with QGIS. Graticules are from Natural Earth.

You can find a bit more info, links, and an animated version here: https://tjukanov.org/roadsofamerica/