Tag Archives: 2019 geohipster calendar

Maps and Mappers of the 2019 GeoHipster calendar — Gretchen Peterson, May

Peterson is a geo expert working in the realm of GIS analysis and cartography. Peterson is the author of several cartography how-to books and the co-author of the recently-published QGIS Map Design, 2nd Edition along with Anita Graser of the Austrian Institute of Technology. Peterson’s consulting work has included the creation of numerous map styles for world-wide OpenStreetMap and Natural Earth based vector tiles using Mapbox GL JS including nautical, topographic, humanitarian, and specialty styles for clients such as Digital Globe and Microsoft. Peterson’s work also includes all manner of GIS data management, analyses, cartography, and tools for salmon and shellfish management in the Pacific Northwest.

The Lewis and Clark Expedition map was created for potential inclusion in a future book, which Peterson would like to produce but has not found the time to create as of yet.

The expedition route line was obtained from the Esri Schools and Libraries Program. Basemap data is from Natural Earth. US Historic Territories and States is from the Newberry Library and processed for the date of the expedition (yes, the current states of Maine and Massachusetts both fell under the name “Massachusetts” in 1804) with different colors for states, territories, and unorganized territory. The Missouri river was offset from the route line even though they physically overlap on much of the route. This was done for visualization purposes. A texture was obtained for the background. The Gabriola font is employed throughout. The elevation graph, which shows the extreme elevation changes encountered by the expedition group, was computed with the QGIS profile tool plugin and then exported and re-styled. QGIS and Inkscape were used to further process and finish the map.

Maps and Mappers of the 2019 GeoHipster calendar — Team Bright Rain, April

Q: Tell us about yourself.

A: I was surprised that we were the only collaboration to submit an entry, we are a team of two strong here at Team Bright Rain:

David Puckett

Bright Rain Solutions’ owner, operator, geospatial developer, data wrangler and self professed Grand Poobah. I’ve been part of the Geo Community for over twenty years and still get fantastically excited about all things geo. I’ve been known to run a workshop or two and have taught a class on web mapping. I consider myself a ‘bridger’ between the proprietary and open source worlds. And some of my best friends are “proprietarians”.

Andrew Lindley

Bright Rain’s Dynamic Technologist with an earnest mission to change the way you put boots and hats on maps. Drew has been with Bright Rain for two years and earned a degree in Geography from the University of British Columbia. He was also the star student in my GIS programming class, from which I promptly drafted him.

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: When it hit me, I literally jumped out of my chair and hollered, “Hexes in Texas!,” with a rousing “Yes! Divorce Rates in Texas!” and All My Hexes Live in Texas was born. It could have been the boots… I happened to be wearing cowboy boots that day… It could have been the H3 hexagon project we had going. But it was definitely cosmic inspiration.

The map is honest to goodness tongue-in-cheek grit but it also brought several interests together for us and that’s why we were excited (and committed enough) to create and submit it. It’s funny yet not so silly that we couldn’t actually wrangle some real data and present it in, dare I say, a (geo)hip way. We love the slight clash between the slick, modern feel of the web map and the old timey western feel of the title text, hat and boot.

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

A: We are web (map) developers so our toolset in making this map definitely embodies that. The map was created as a web map and later exported and enhanced in Adobe Illustrator to create the final image output. Mapbox GL was used to display and extrude counties as hexagons based on the divorce rate within the county. The hexagons themselves were generated using Uber Engineering’s H3 Hexagonal Hierarchical Spatial Index (Javascript) library (at scale level 5).

DATA

Data was gathered from the state of Texas (population per county and divorces per county) and the US Census Bureau (us states: Tennessee).

Texas 2012 Population Estimates by County

https://www.dshs.texas.gov/chs/popdat/ST2012e.shtm

Texas 2012 Marriage and Divorce by County

http://www.dshs.state.tx.us/chs/vstat/vs12/t39.shtm

Texas County Boundaries (shapefile, SHAPEFILE!)

http://gis-txdot.opendata.arcgis.com/datasets/9b2eb7d232584572ad53bad41c76b04d_0

ANALYSIS

Analysis was conducted in QGIS where the divorce rate per thousand was calculated and the hexagons were assigned a value for extrusion (based on divorce rate calculation). The resulting hexagons with divorce rates assigned were exported as geojson for direct use in the web application.

AND

An interactive, web map version is here:

http://dev.brightrain.com/hexes-in-texas/

Maps and Mappers of the 2019 calendar: Chris Van Pollard

Q: Tell us about yourself.

A: What’s up! I’m Chris, and I’ve been making maps and tinkering with GIS for over 19 years in the GIS Department at a Regional Planning Commission in the City of Brotherly Love (Philly, Philly!). I spend most of my days focusing on all aspects of geospatial technology, cartography, spatial thinking, and hacking away at web maps. I’m a huge ice hockey and coffee enthusiast, which helps fuel that passion to learn and improve my cartography and web mapping skills. Since 2012, I’ve been an adjunct professor at Rowan University, in Southern New Jersey, teaching young minds about GIS, the mystifying transformations of map projections, and cartographic design.

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 allowed me to combine my passion and love for ice hockey with that of cartography. I was inspired by the amazing work, map design, and GIS tools that carto-wizards John Nelson, Ken Fields, and Johan Adkins have been sharing with us lately. John’s series on Air Mile Index  gave me the initial idea that I wanted to map how far each NHL team travels throughout the season. I wanted to determine if there was a correlation between performance (wins) and how much travel affects the players throughout the season. I was able to find the 2017-2018 NHL Travel Super Schedule in a user-friendly spreadsheet listing all the games for the season. Next, I added the Latitudes and Longitudes for all of the “Home” game teams, and included a sequence/order so that I could generate an Origin/Destination pairing between games. Once I had the data prepared, I utilized ArcMap’s XY-to-Line Tool to generate the paths. I wanted to learn more about the layout tools and capabilities in ArcGIS Pro, so I decided that I would make this map within that platform. Before diving into this project, my ArcGIS Pro skills were limited, but through this process I was able to learn, fail, try again, and have fun while doing it.

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

A: Shapefiles, Shapefiles, and more Shapefiles. This map was made using ArcGIS Pro with a little data creation assistance from ArcMap. The symbology and transparency tools in ArcGIS Pro are incredibly exciting to work with, making map creation fun. I used Adobe Illustrator to create the Old School hockey mask to add that extra flair. Initially I needed to create a point shapefile, then I used the hockey mask as a marker symbol layer in Pro to allow me to adjust its transparency so that it faded into the basemap.

 

Maps and mappers of the 2019 calendar: Tom Chadwin

Q: Tell us about yourself

A: I live in deepest rural Northumberland, close to the England-Scotland border. I studied Middle Irish at university (coincidentally becoming friends there with Richard Fairhurst of OpenStreetMap fame), and then started work as a printer (not a successful one). I worked as a web designer in the days of version 3 of both Internet Explorer and Netscape Navigator, and then a web developer in the days of classic ASP, before .NET was invented. I’ve been in the public sector for over fifteen years now, most of them at Northumberland National Park, working on networking and open-source telephony, among many other things. We made the switch from MapInfo to QGIS many years ago now, and have never looked back.

I got involved with QGIS when I started to help out with the plugin qgis2leaf by Riccardo Klinger. Since then, I created qgis2web, which I still develop and maintain. I try to help out with QGIS and OSGeo events in the UK, and co-chaired FOSS4GUK 2018 with James Milner. Please come along to FOSS4GUK 2019 in Edinburgh this autumn!


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: In 2018, our local council proposed the closure of our local first school. Our daughter was in her last year at this amazing place, so we resisted. I thought that some striking maps might help our case, so I made one map of the proposed increase in journey-to-school time (below), and a second map of the signatories to the petition to save the school. The signatories map is the February 2019 GeoHipster map:

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

A: The map was built almost entirely in QGIS. I used GIMP to add the tilt-shift blur, and because of this blur, I had to use GIMP for the text as well. The data was scant to the point of naivety, being simply the postcodes of around 400 petition signatories.

The idea behind the map was to try to use this scant data in an emotive way, in what was an emotive argument. Visual appeal was of greater importance than spatial analysis, which is just as well, since I’m no spatial analyst. The scant data and the intent to grab attention led to my using the height of the styled points to denote not number of signatories, but proximity to the school. My hope was that this visualized how highly localized the support for the school was, a fact not immediately apparent from the raw data.

Technically, the overriding technique and principle behind the map is the separation of data from style. No processing at all was done on the data, which was a necessity because I was designing the map while the petition was still gathering signatures, so the data was changing all the time. All the heavy lifting is done by QGIS geometry generators, creating squares around the points, rotating and skewing them into faux perspective, and then extruding them into 2.5D symbols.

I had a huge amount of help from the Twitter carto community, without which I simply could not have built the map. I wrote about both maps in much greater detail on my website: tom.chadw.in/wrote/MappingEmotion.

The school was saved from closure, but further unwanted changes to our rural schools are ongoing, and the fight continues. Who knows whether this map had any effect on the Council, but it did result in a very old friend describing it as the “worst game of Risk ever”.