Maps and Mappers of the 2017 GeoHipster Calendar – Johann Dugge and Juernjakob Dugge

Johann Dugge and Juernjakob Dugge – May

Johann Dugge and Juernjakob Dugge

Tell us about yourself.

Johann: I model packing processes of consumer products like laundry detergent to optimise the package design and manufacturing lines at Procter & Gamble in their Brussels office. 

Juernjakob: I work on software for optimising water and wastewater treatment processes. So our day jobs have only little to do with mapping. However, we’ve been exposed to cartography and particularly terrain models from a young age: Our father is a geomatics engineer, and our parents have been collecting raised relief maps for as long as we can remember.

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).

Juernjakob: I was following Daniel Huffman’s tutorial on generating shaded reliefs using 3D rendering software, and slightly adapted the approach by first converting the DEMs to triangulated irregular networks before rendering them. The faceted appearance reminded me of the low-poly papercraft models that have been in vogue for a while, and I thought it might be fun to build a terrain model out of paper.

Johann: In June 2015 as we were cycling over the hills of Belgium we discussed what the qualities of such a model would have to be to be considered “optimal”. When we returned home to Brussels and Stuttgart we both started to adapt existing triangulation algorithms for this specific problem. In the end I came up with a solution that strikes a good balance between terrain fidelity and having a small number of triangles, avoiding difficult-to-assemble thin and tiny triangles as much as possible. My background in numerical optimisation certainly came in handy for this.

We presented the first results at the ICA Mountain Cartography Workshop in April 2016 and received a lot of very encouraging feedback. Since then we have been working on new models – the Matterhorn is already available through our site Also keep an eye out for Mount Fuji which will be released shortly!

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

We developed the triangulation algorithm in MATLAB. The elevation data comes from the USGS National Elevation Dataset, the orthophoto from the US National Agriculture Imagery Program. The quality of publicly available data in the United States is amazing, the rest of the world still has a lot of catching up to do in this regard.

Blender is used to add the stiffening structure to the 3D model. Pepakura is an unfolding software for paper model layouts and the final touches are done in Inkscape.

Maps and Mappers of the 2017 GeoHipster Calendar – Michele Tobias

Michele Tobias, PhD – January

GIS Data Curator – Data Management Program – UC Davis Library

Tell us about yourself.

In January I started my current job as the GIS Data Curator for the UC Davis Library where I work on data projects related to the library’s areas of particular interest and help patrons with questions related to data acquisition, creation, documentation, preservation, and sharing. I have a PhD in geography, and I am especially interested in the biogeography of coastal plants. When I’m not working on map-related things, I’m either dancing or crafting.

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).

OK, but it’s kind of a long story… I’ll try to keep it short. It started a few years back when I saw an episode of Huell Howser, a show produced by the Los Angeles PBS station, KCET. In this episode, Huell interviewed people involved in growing the seeds that went to the Moon on the Apollo 14 mission and visited several of the resulting “Moon Trees” growing in the state. Curious about where the rest of the trees are, I looked for more information online and found some lists and a few basic maps. Fast forward to the 2016 call for FOSS4G North America presentations… I submitted a talk on cartography with Inkscape. I needed an interesting dataset to work with in my examples, and remembered the Moon Trees. Tree locations are easy to understand for a broad audience, and the story is interesting. Plus, my talk was on May 4th… so something with space needed to happen. Sometimes it seems that everything just sort of falls into place. It just happened that the keynote speaker for the conference that year was Tamar Cohen from the NASA Ames Research Center. And as I was making the map for my presentation, my aunt told me that my grandfather was on the crew that tracked the Apollo 14 mission and retrieved it when it came back to Earth. He would have gotten a kick out of the map for sure.

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

One of the goals I had for this map was that I use only open source software to make it. I found a Google Map of Moon Tree locations made by a person affiliated with NASA, and asked her via Twitter for permission to use her data. I cleaned up the KML attributes in LibreOffice.  I had hoped to get tree icons from Phylopic, a site for silhouettes of life forms, but they didn’t have the species that I needed so I made my own and contributed them back to the project. The basic layout and data display was done in QGIS, but I made the icons and did all of the big cartography in Inkscape.

This map was perfect for demonstrating some of the things you can do in Inkscape that isn’t possible in QGIS (or any GIS for that matter). The map has 3 data frames. In QGIS, you can’t have a different projection for each of them right now, so I had to export the frames separately and reassemble them in Inkscape. Also, the moon image fill on the polygons was achieved through a clipping process in Inkscape. The tree icons and numbers needed a lot of moving by hand to separate them enough to distinguish. The coasts of the US have a lot of trees and when I started, they were all lumped together. Some of the trees have a very subtle glow behind them to help them stand out from the background. In a GIS, it’s just not that easy to make a subtle halo.

The whole process of creating the map is documented in my 2016 FOSS4G North America talk that’s on their YouTube channel. The pitch video for the talk composed of screen captures of the map as it came together is on my channel.

Maps and Mappers of the 2017 GeoHipster Calendar – Alison DeGraff Ollivierre

Alison DeGraff Ollivierre – September

Tell us about yourself.

I’m a cartographer who works full time at National Geographic Maps, part-time doing freelance cartography/GIS work as Tombolo Maps & Design, and part-time for the NGO BirdsCaribbean. I’m from Vermont, have been living in the Eastern Caribbean on and off for the past six years, and currently live in Colorado. I love making maps and living abroad, and my primary topic of research for the past seven years has been participatory mapping, with a focus on its use in Caribbean small island developing states, particularly in relation to climate change, for the past six years.

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).

When I was going through a stint of less cartographically-exciting freelance work last year, I started doing a map-a-day (inspired by Stephen Smith’s tile-a-day project) where I made quick, fun, daily snapshot maps that explored less commonly used fonts, colors, and projections with whatever exciting data I could get my hands on. I found NOAA’s climatic data center to be a jackpot for interesting data, and decided to map hurricane tracks across the Atlantic. Since I grew up in Vermont, I had not experienced hurricanes before moving to the Eastern Caribbean. The first big storm that passed through after I moved to St. Vincent and the Grenadines in 2011 was Hurricane Irene, which passed north of our island (just dumping a bit more rain than usual) and then proceeded to swing all the way up the coast to pummel Vermont. Nothing like a little geographic irony to inspire a map!

Tell us about the tools, data, etc., you used to make the map.
This map was made with NOAA’s national weather data and Esri country boundaries in ArcGIS and Adobe Illustrator. I started by converting the KMLs into shapefiles and selecting out the years that corresponded for both the Atlantic and Pacific hurricane seasons (there was twice as much data for the Atlantic hurricane seasons), leaving me with the 1930s-1980s. I then completed the cartographic design work in AI, including the graphic effects on the continents and oceans, and the visualization of the hurricane tracks.