A. My name is Emmanuel Duchene. I work as a teacher in Sweden. Originally from France, I have for a long time felt a strong attraction for Sweden. I moved here in 2011. I am married and have two children, one of which did this map collab with me. I have always liked maps and geography but have no GIS background whatsoever. It all started when I stumbled upon a 3D rendered map of California by Scott Reinhard on Pinterest. It was quite fascinating to me how he managed to make a vintage map look like 3D. I had never seen that before. Not on that level at least (we’ve all seen 3D plastic maps with relief in school, for sure). I am very stubborn and set on a quest to make these myself. Many hours passed, many Youtube videos were watched and many blogs read. The thing is, there was nowhere to be found any material covering the whole process. So, I had to learn everything, from importing a georeferenced map into ArcGIS Pro to adding ambient occlusion in Blender, not forgetting how to use feature classes to crop rasters, etc. I have to say that John Nelson’s ArcGIS Pro content on different media were a big help. I think it turned out quite okay. Really, I mainly make these for fun and to entertain my map nerdiness.
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. The story behind this map is a bit different. I did not really come up with the idea myself. I told my daughter that you guys were looking for entries for the calendar. I asked her if she wanted to make a map together and send it to you. She said yes and we agreed that we needed to do something a bit different and original. We both love space stuff and planets. I knew from before that elevation data was available for Mars and suggested that to her. She came up with the idea of mapping the rovers’ landing sites. And off we went! The most challenging part was finding the right projection and layout so that all rovers would fit. Mostly, it was trial by error.
Q: Tell us about the tools, data, etc., you used to make the map:
A. The map is made using ArcGIS Pro for layout, geodata, elevation and design. The 3D is rendered in Blender. Some Photoshop is also used to prepare the DEM for blender and make final adjustments in contrast to the final image. The elevation data is from the Mars Orbiter Laser Altimeter (MOLA) DEM at a resolution of 200m.
A. Hi, I’m Connor Houston (www.reachabove.ca) and am a geographer and a geospatial professional. I work for the Province, putting Ontario (CANADA) on the map by using a variety of GIS technologies, introducing Ontario to potential investors and constantly striving towards faster, better, cheaper geospatial systems of insights, engagement and record. My journey into the mapping stack began 20 years ago and have been fortunate to work and volunteer with a variety of organizations domestically and internationally over the years.
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. Launched in the summer of 2022, Trail Hub is a community HUB for mountain bikers, hikers, nature lovers, snowshoers & cross country skiers to access over 240km of local trails. I was introduced to the founders of Trail Hub through our mutual involvement in Active Transportation Committees in our Region, just as Trail Hub was looking at ways to showcase the trail system to their visitors. Serendipitously we connected just as they were undertaking the project and just as I was wrapping up a very awesome personal Heat Map for a friend, who had the amazing idea to create a poster of his riding accomplishments over the pandemic to hang in his office for motivation.
The calendar map is a smaller version of the original 40” x 60” map which is mounted in the Trail Hub main hallway as visitors enter the facility. The primary function of the map was not for navigation, wayfinding or quick reference. This map was designed to engage the reader in a way that draws them into the local environment. Their first impression is hopefully “that’s a big beautiful environment”. Second “whoa.…there’s a lot of trails”. Third, “lets go explore!” And fourth, if they are returning visitors, “where’s that trail? – over there, see that’s the hill we climbed”. Engaging the reader trying to draw them in, the labels were left at a minimal size, so that at a glance you can’t tell what the trail name is. It’s only when you take a step closer and see the details of the imagery, elevation and then the trail names become apparent.
Q. Tell us about the tools, data, etc., you used to make the map.
A. The data for the map came from three sources, all processed in QGIS and exported to GIMP to create the final layout. The main aerial photo was styled in Mapbox Studio using their Maxar imagery. This was connected in QGIS as a web service. The elevation rasters are a combination of a 0.50cm DSM and a 5m DEM from the Province of Ontario GeoHub. The hillshade, slope and aspect derivatives were created in QGIS using Grass. The trail lines are from OSM with updates from myself and community members ensuring they are located and named correctly. Using GIMP, the Trail Hub branding was incorporated including the font, colours and graphic elements. The trail labels and POIs were all manually placed using GIMP as well.
The map has been a great success at Trail Hub. Additional derivatives have been created for social media as well as postcards for distribution at events.
Well, you can count on this as much as you can count on your favorite open source database: it’s that time of year when we release our map calendar on PostGIS Day! What does this calendar do?
Accurately tells the Day, Month, and Year
Features 14 Amazing Maps, including the above cover from our art director Jonah Adkins
Provides you an easy gift for friends, family, and co-workers
Joel Salazar brings us the highway running through the Andes Mountains
How do you get it? Well, this stunning printed product can be yours for just $15.99 (US)! Head on over to Lulu.com to get yours – and some for your pals, too! (Or you can just tell them to head to tinyurl.com/geohipster2023.)
A: Hi, I’m Tom Armitage (@MapNav_Tom on Twitter) and I have been working in GIS for 20 Years. I’m MapTiler‘s Technical Writer and I also do some GIS training and teaching at the University of Edinburgh where I am an honorary fellow. I’m an Open Source Advocate, and have spent a lot of my career teaching GIS skills in QGIS.
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 originally started as my entry for “Red” in Topi Tjukanov’s #30DayMapChallenge. I was using some quirky layers of data with minimal base mapping to give different perspectives of Edinburgh. The map is therefore part of a series with water represented on the Blue map, trees on the Green map and parking restrictions on the Yellow map. This was all made possible by having great Open Data resources from Ordnance Survey, British Geological Survey and the City of Edinburgh Council. The red map was always my favourite of the series so I made some improvements and submitted it. The Listed buildings data lends itself to the firefly cartography I used, there are different levels of protection which can be used to vary the size of the points and there are low and high density areas across the city. The resulting map shows areas with high concentrations with increasingly bright intensity. All of the maps in the series were recognisable as Edinburgh, certainly to a local anyway. However, the red map highlighted areas with the oldest buildings and so it was possible to see where the city had grown and taken over what would have been individual villages in the surrounding countryside. Coupled with Edinburgh’s sometimes bloody history (look up Burke and Hare), it’s why I liked this one the best.
Q: Tell us about the tools, data, etc., you used to make the map:
A: To create this Map, I only needed QGIS, but I made extensive use of the Blend modes and Draw effects. Those of you that follow me on Twitter will know I’m a big fan of these! First I varied the point size based on the level of protection a building had, largest points for the most highly protected. I then applied an Outer Glow to the points and made this red like the points themselves. I used the Screen blend mode on the points with the map layer and also with each other. This meant that the points would brighten the backdrop and the effect would be amplified the more the points overlapped. At this point in the process I needed to decide what scale the final map was going to be, and set the DPI in the print layout. These both affect how much overlap there is between the points so it is important to fix them first before deciding on the final point size. Varying any of these values will affect how intense the brightness gets in the final map. There was a fair amount of trial and error before I got it right! Also, to make sure that this effect works, it is important that the red used wasn’t at full saturation. I used one that was a bit darker, so that there was more room for it to become intense. One final trick I used was to put in a layer of building polygons in dark grey, over the black backdrop. This is a point dataset, but it is about the buildings, so the lighter polygons and screen blend mode helped highlight these more as areas, rather than just the points. At this scale though, the points were a better call to use than creating a polygon layer… though you may notice a couple of lonely looking dots in the Firth of Forth representing the Bridges!
Producing the map was a lot of fun, but I also learned a lot about defining a proper process and procedure to follow. This has helped a lot when creating more firefly maps!
Could your map be featured in the 2023 GeoHipster Calendar?
Fall weather (in the northern hemisphere). Back to school. Pumpkin spice lattes. Spooky movies and Halloween candy. What other traditions can you count on happening each September?
You guessed it! We’re pleased to announce that there will be a 2023 GeoHipster Calendar, and we’re opening up the call for maps today. Mike and Randy will be tag-teaming the administration duties this year, our pal Bill Dollins will once again serve as chief judge, and we have frequent contributor Natasha Pirani serving as a guest judge.
We want to continue our tradition of revealing the calendar by PostGIS Day in November, so get your maps in soon (the deadline is October 21). All the details are available on the 2023 calendar page. Happy Mapping!
A: I’ve loved maps for my entire life and have been drawing and making maps since my childhood. Currently I live in Richmond, VA. I work for the Office of Intermodal Planning and Investment where I do my best to make a positive contribution to Virginia’s transportation plan (VTrans) using my background in GIS and data management.
Q: Tell us the story behind your map
A: In 1864, as the American Civil War was entering its final months and the Union army was closing in on Petersburg and Richmond, the US Coast Survey Office produced a map of Richmond, Virginia, presumably commissioned in support of the Union Army’s ongoing siege, showing the streets and major landmarks of the city. One hundred fifty years later in 2014, the US Geological Survey mapped the same area using lidar to evaluate the damage from Hurricane Sandy. My map combines these two datasets allowing you to see how the city has physically evolved over the past century and a half.
You can easily see how much has remained the same over the years in the basic layout of the streets. The fact that the 19th century map is able to be georeferenced so accurately to the lidar data is a testament to the skill of the surveyors who created the original map. Mayo’s Bridge, the oldest in the city, is clearly visible in both datasets even though it’s been rebuilt a couple times in the interim. Some of the buildings that survived the war are visible in the lidar dataset (in fact I used the Capitol building and the Masonic Hall as control points while georeferencing the 19th century map). The ruins of the Petersburg railrod bridge are clearly visible as periodic squares in the lidar data next to the line in the 19th century map. The most notable change is the removal of the canal system and the additional bridges that were built in the 20th century, as well as the Interstates and the Downtown Expressway that carve their way through the city.
Not as easily seen in the map is the cultural change the city has seen over the course of a century and a half. Before the Civil War, Richmond had the second largest slave market in North America. The St Charles Hotel in the eastern side of the map was known for hosting auctions in the basement. By 2014 there was a growing movement to recognize the city’s dark past, often hidden from the history books, and to remove the massive “lost cause” monuments scattered throughout the city that glorified the Confederacy.
Q: Tell us about the tools, data, etc you used to make the map
A: The 19th century basemap was acquired from the Library of Congress’ map collection. Taking a look at that map by itself is interesting (you can view it at the Library of Congress website), but I decided to try georeferencing it in order to compare it to modern GIS data. I relied on buildings and intersections that have survived since the mid-1800s as control points. I was amazed by how well the map matched up to modern imagery.
The 21st century lidar data was from the USGS National Map. I used WhiteBox Tool’s Python interface to visualize the data using the Time In Sunlight tool. Finally, I combined the two datasets in GIMP image editing software.
A: Originally from New England in the U.S., I’m a second year student in the International Master of Science in Cartography degree program, which takes place in Europe at the Technical University of Munich, the Technical University of Vienna, the Technical University of Dresden, and the University of Twente. Probably like most people reading this article, I’ve been interested in cartography for a long period of my life. Since elementary school, some of my favorite things to do have included perusing the content of globes, atlases, and maps and making maps (or at least attempting to) of real and imaginary places. For my undergraduate education, I completed a B.A. in geography partly because I like maps, but perhaps more than anything because I like a lot of things and geography seemed like a sufficiently broad and synergistic discipline to allow me to pursue a lot of interests. Following graduation, I completed two cartography and geospatial analysis internships and then spent about ten years working in a few jobs that often had little to do with geography – a fact which might be considered hipsterishly ironic because I spent the majority of that time working for National Geographic. I also occasionally did work with maps in volunteer and recreational contexts.
At some point a few years ago, I decided I wanted to pursue more formal education in cartography and geoinformatics and spend some time living in Europe (my Europhilia is nearly as strong as my cartophilia), so I enrolled in my current program. In addition to maps, I really like reading, traveling, attempting to learn new languages, playing the bassoon, and trying unusual foods. I’m honored by my map’s selection for inclusion in this wonderful calendar alongside the amazing work of other cartographers. Its selection helps me confirm for myself that I’ve likely taken a step in a good direction by studying cartography at the master’s degree level.
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 made this map last spring for a class called Project Map Creation, which is a degree requirement for my current study program. It is taught by professional cartographer Manuela Schmidt, to whom I’d like to express strong gratitude for the help she gave me while I worked on the map at the Technical University of Vienna. Students enrolled in the class are required to spend a semester creating an analog thematic map about a topic of their choice. In past years when this course was offered, many students made maps showing cultural features of the places they’re from. I decided I wanted to do the same thing. The thought struck me that Maine’s lighthouses might be an interesting focus for my map: They are culturally iconic of the place where I’m from and have a large number of spatial attributes suitable for visualization on a map and ancillary infographics.
I often kayak along the ocean coastline of Maine’s Midcoast region in the early evenings when lighthouses first begin to flash their lights. I’m curious to learn the geographic locations of the lighthouses associated with the lights I see, as well as general information about the lighthouses’ histories and how they can be used for navigation. I thought other kayakers and casual boaters might be similarly curious, so I created the map with these people in mind as target users. The map shows the geographic locations of Midcoast Maine’s lighthouses, the colors and flash patterns of the lights’ primary lights, and the oceanic spaces where each light is generally visible for an observer two feet above sea level (such as a kayaker) during a night with good weather conditions (meteorological visibility of ten nautical miles).
As is the case with all maps, this one excludes information about the geography it depicts, including some I’ve come to think is important. In addition to the primary lighthouse lights the map provides information about, small sector lights, whose colors, flash patterns, and visible ranges differ from those of the primary lights, shine from some of Midcoast Maine’s lighthouses. When making my map, I decided not to include information about these sector lights, since I couldn’t quickly figure out how to do so in a legible and aesthetically pleasing way. I considered their exclusion an appropriate generalization for the map’s scale. However, in retrospect I’ve questioned this decision because lighthouse sector lights help mariners avoid dangers to navigation. My exclusion of this information likely means that while the map is appropriate for use as an art object published in a calendar, it should not – despite its title and original intended use case – actually be used for navigation.
Q: Tell us about the tools, data, etc., you used to make the map.
Could your map be the cover of the 2022 GeoHipster Calendar?
Is it true that 2021 was almost as unpredictable as 2020? We don’t know the answer to that, but we do feel like our 2021 calendar was our best yet. We also know some of you are back in the office and need wall candy…and those of you who are still working from home love to mix up your backgrounds! So why stop now? That’s right, we’re pleased to announce that there will be a 2022 GeoHipster Calendar, and we’re opining up the call for maps today.
We want to continue our tradition of revealing the calendar by PostGIS Day in November, so get your maps in soon. All the details are available on the 2022 calendar page. Happy Mapping!
A: I am a GIS lead at the State of Michigan’s Department of Environment, Great Lakes, and Energy (EGLE), where I wear many hats including web GIS administrator, open maps and data wrangler, geospatial educator, and project consultant. When I’m not wearing those hats, you can find me in the water scuba diving a local Michigan shipwreck (I wonder where the idea for this month’s map came from!) or at the desk dabbling with my latest carto- creations. I am known on Twitter by my alias @pokateo_ because my idea of a perfect day is being surrounded by yummy spud dishes. Another hobby I enjoy is making and sharing geography/geospatial memes under the tag #mappymeme on Twitter.
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: As an avid scuba diver, I’d been playing with various Great Lakes shipwreck spatial layers and knew I wanted to do something fun with them but didn’t know what. It wasn’t until I came across this article and saw a painfully sad Google Maps + Microsoft Paint map for the “Bermuda Triangle of the Great Lakes” that I had a lightbulb moment. I played with two versions of this map: a messy conspiracy theory board (akin to this Always Sunny meme) and an antique pirates map you see on this month’s calendar page. There are various Easter eggs on the map including a faded list of all the ships that have gone missing in the triangle over the years, a reference to a Stonehenge-like structure recently found under Lake Michigan as a possible correlation of the disappearances, a remnant of old maps where cartographers would put the phrase “Here be dragons” in unknown areas with potential danger, and a simple map monster that’s apparently factually inaccurate (should have checked out Michele’s Lake Monsters of the world :p).
Q: Tell us about the tools, data, etc., you used to make the map.
A: I used ArcGIS Pro to complete this map. The majority of the artistic flair credit should probably go to John Nelson (as per the uzh), as I adapted some of the styles, textures, and bathy he’s shared on his national treasure of a blog. The triangle’s location is from the previously mentioned article, and the shipwrecks were a combination of datasets from NOAA and this most excellent story map by the Michigan Department of Natural Resources. This map was originally made portrait with north straight at the top, but to submit to the calendar I adjusted it to make it landscape and I am pretty happy with the funky tilt of the map. I am humbled to be in the 2021 calendar. Thank you for all GeoHipster does for our special spatial community!
A: I am a GIS Consultant working for Arup in the UK, with a specialism in data engineering and 3D visualisation. I think I have an unusual background for someone in GIS, having studied Fine Art, and later 3D Modelling & Animation. I have a passion for art and design, and studied painting, photography, and architecture which I still love.
I got into GIS by accident but found it fascinating, especially being able to join data together with spatial relationships. I learned Maya & Blender (thanks to Nick George if you’re out there!) before ever knowing GIS was a thing.
I am one of the people responsible for the popularity of Blender in cartography in recent years, having developed and shared new workflows and techniques.
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 am slightly obsessed with Japan, and Japanese culture – it is so unique. I made this map of Hachijō-jima Island for no real reason other than to create something new and different, plus I love making maps of islands. In my work I try to do something different each time, and consider it a failure if I just repeat a style I’ve done before, or in the style of someone else.
Q: Tell us about the tools, data, etc., you used to make the map.
The basis of the map was made with FME, in creating a surface as well as textures such as the coastal vignette. I love that FME gives you complete control and works with practically any format of data. FME is vital in my work, effectively extending the possibilities in Blender beyond the standard VFX and games industry data formats.
The map is an orthographic render of a 3D model, made from triangulating contours and extruding 2d features (GML > FBX using FME). This is something I find myself doing more and more, because the resolution of elevation data rarely fits well with the available topographic data. If you create your own DEM raster or surface then there are opportunities to fill voids or smooth areas to match your intended map scale.
With this map I used Blender’s node-based shader editor where you can mix map layers as textures to affect the way it reacts to light, for example with the roads, water, and the coastal vignette.