Maps and mappers of the 2020 calendar: Daniel Fourquet, July

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Q: Tell us about yourself

A: For most of my life I have been fascinated with maps, both studying them and making them myself. As a child I would fill folders with detailed maps of an imaginary country and would spend too many hours playing games like SimCity and Civilization on the computer (ok, I do that as an adult sometimes too!). These interests would eventually lead me to studying geography at Old Dominion University in Norfolk, VA and begin a career doing GIS work. Recently I’ve become interested in programming and am now enrolled in the University of Wisconsin-Madison’s online GIS and web map programming masters program. I’m currently a GIS Analyst at the Virginia Department of Transportation in Richmond.

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 became interested in using 3D rendering software in cartography when I stumbled on some of the beautiful maps created by Owen Powell (@owenjpowell) last Spring. While doing research to learn how to make 3D maps of my own, I discovered the work of Daniel Huffman (@pinakographos) and Scott Reinhard (@scottreinhard), both of which were also influential. I experimented with terrain maps for a couple months before deciding to try creating an urban map using lidar data. I chose the US Capitol because it’s such a well known landmark.

My decision to design this map in black and white was inspired by Daniel Huffman’s NACIS talk (https://www.youtube.com/watch?v=ptKDS1Z8Oro) about the challenges and advantages of mapping in monochrome. I initially planned on designing the map in color, but then I realized that removing color created a more formal tone that is fitting for a map of the buildings where such important decisions are made.

 

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

A: Data Used:

– The Lidar data was downloaded from the USGS National Map.

– I used land cover data from the Chesapeake Conservancy.

Tools Used:

– WhiteboxTools (https://jblindsay.github.io/ghrg/WhiteboxTools/index.html) is a collection of GIS tools that allowed me to process the lidar data via Python to prepare it for rendering in Blender.

– ArcMap was used to organize and prepare the data.

– Blender was the 3D software used to render the Lidar data.

– GIMP was used to add the land cover data. I also manually brushed in the trees, which was time-consuming, but resulted in a much better map than relying on the trees from the land cover data.

– Illustrator was used for labelling and finishing the map.