Eric Fischer: “There may yet be an objective measure of the goodness of places, but I haven’t found it yet“

Eric Fischer
Eric Fischer
Eric Fischer works on data visualization and analysis tools at Mapbox. He was previously an artist in residence at the Exploratorium and before that was on the Android team at Google. He is best known for "big data" projects using geotagged photos and tweets, but has also spent a lot of time in libraries over the years searching through old plans and reports trying to understand how the world got to be the way it is.

Q: You’re coming up on four years at Mapbox, is that right? What do you do there?

A: I still feel like I must be pretty new there, but it actually has been a long time, and the company has grown tremendously since I started. My most important work at Mapbox has been Tippecanoe, an open-source tool whose goal is to be able to ingest just about any kind of geographic data, from continents to parcels to individual GPS readings, numbering into the hundreds of millions of features, and to create appropriate vector tiles from them for visualization and analysis at any scale. (The name is a joke on “Tippecanoe and Tyler Too,” the 1840 US Presidential campaign song, because it makes tiles, so it’s a Tyler.)

Q: I read that you’re working on improving the accuracy of the OpenStreetMap base map. Can you describe that process? I’m guessing one would need to figure out how accurate it is in the first place?

A: I should probably update my bio, because that was originally a reference to a project from long ago: to figure out whether it would be possible to automatically apply all the changes that the US Census had made to their TIGER/Line base map of the United States since it was imported into OpenStreetMap in 2006, without overriding or creating conflicts with any of the millions of edits that had already been made directly to OpenStreetMap. Automated updates proved to be too ambitious, and the project was scaled back to identifying areas where TIGER and OpenStreetMap differed substantially so they could be reconciled manually.

But the work continues. These days, TIGER is valuable to OpenStreetMap mostly as a source of street names and political boundaries, while missing and misaligned streets are now identified mostly through anonymized GPS data. Tile-count is an open source tool that I wrote a few months ago for accumulating, normalizing, and visualizing the density of these GPS tracks so they can be used to find streets and trails that are missing from OpenStreetMap.

Q: In the professional mapping world, I’ve noticed there’s a nervousness around datasets that aren’t time-tested, clearly documented, and from an authoritative source such as the US Census. These official datasets are great resources of course, but there’s a growing amount of data at our fingertips that’s not always so clean or complete. You’ve been successful at getting others to see that there’s a lot to learn about cities and people with dynamic (and sometimes messy) data that comes from many different sources. Do you have any advice on warming people up to thinking creatively and constructively with unconventional datasets?

A: I think the key thing to be aware of is that all data has errors, just varying in type and degree. I don’t think you can spend very much time working with Census data from before 2010 without discovering that a lot of features on the TIGER base map were missing or don’t really exist or are tagged with the wrong name or mapped at the wrong location. TIGER is much better now, but a lot of cases still stand out where Census counts are assigned to the wrong block, either by mistake or for privacy reasons. The big difference isn’t that the Census is necessarily correct, but that it tries to be comprehensive and systematic. With other data sets whose compilers don’t or can’t make that effort, the accuracy might be better or it might be worse, but you have to figure out for yourself where the gaps and biases are and how much noise there is mixed in with the signal. If you learn something interesting from it, it’s worth putting in that extra effort.

Q: Speaking of unconventional data: you maintain a GitHub repository with traffic count data scraped from old planning documents. For those who may not be familiar, traffic counts are usually collected for specific studies or benchmarks, put into a model or summarized in a report… and then rarely revisited. But you’ve brought them back from the grave for many cities and put them in handy easy-to-use-and-access formats, such as these ones from San Francisco. Are you using them for a particular project? How do you anticipate/hope that others will use them?

A: The traffic count repository began as a way of working through my own anxieties about what unconventional datasets really represent. I could refer to clusters of geotagged photos as “interesting” and clusters of geotagged tweets as “popular” without being challenged, but the lack of rigor made it hard to draw any solid conclusions about these places.

And I wanted solid conclusions because I wasn’t making these maps in a vacuum for their own sake. I wanted to know what places were interesting and popular so that I could ask the follow-up questions: What do these places have in common? What are the necessary and sufficient characteristics of their surroundings? What existing regulations prevent, and what different regulations would encourage, making more places like them? What else would be sacrificed if we made these changes? Or is the concentration of all sparks of life into a handful of neighborhoods in a handful of metro areas the inevitable consequence of a 150-year-long cycle of adoption of transportation technology?

So it was a relief to discover Toronto’s traffic count data and that the tweet counts near intersections correlated reasonably well with the pedestrian counts. Instead of handwaving about “popularity” I could relate the tweet counts to a directly observable phenomenon.

And in fact the pedestrian counts seemed to be closer than tweet counts to what I was really looking for in the first place: an indicator of where people prefer to spend time and where they prefer to avoid. Tweets are reflective of this, but also capture lots of places where people are enduring long waits (airport terminals being the most blatant case) rather than choosing to be present. Not every pedestrian street crossing is by choice either, but even when people don’t control the origin and destination of their trips, they do generally have flexibility to choose the most pleasant route in between.

That was enough to get me fixated on the idea that high pedestrian volume was the key to everything and that I should find as many public sources of pedestrian counts as possible so I could understand what the numbers look like and where they come from. Ironically, a lot of these reports that I downloaded were collecting pedestrian counts so they could calculate Pedestrian Level of Service, which assumes that high crossing volumes are bad, because if volumes are very high, people are crowded. But the numbers are still valid even if the conclusions being drawn from them are the opposite.

What I got out of it was, first of all, basic numeracy about the typical magnitudes of pedestrian volumes in different contexts and over the course of each day. Second, I was able to make a model to predict pedestrian volumes from surrounding residential and employment density, convincing myself that proximity to retail and restaurants is almost solely responsible for the number, and that streetscape design and traffic engineering are secondary concerns. Third, I disproved my original premise, because the data showed me that there are places with very similar pedestrian volumes that I feel very differently about.

If “revealed preference” measured by people crossing the street doesn’t actually reveal my own preferences, what does? The ratio of pedestrians to vehicles is still a kind of revealed preference, of mode choice, but the best fit between that and my “stated preference” opinions, while better than pedestrian volume alone, requires an exponent of 1.5 on the vehicle count, which puts it back into the realm of modeling, not measuring. There may yet be an objective measure of the goodness of places, but I haven’t found it yet.

Why did I put the data on GitHub? Because of a general hope that if data is useful to me, it might also be useful to someone else. The National Bicycle and Pedestrian Documentation Project is supposedly collecting this same sort of data for general benefit, but as far as I can tell has not made any of it available. Portland State University has another pedestrian data collection project with no public data. Someday someone may come up with the perfect data portal and maybe even release some data into it, but in the meantime, pushing out CSVs gets the data that actually exists but has previously been scattered across hundreds of unrelated reports into a form that is accessible and usable.

Q: What tools do you use the most these days to work with spatial data (including any tools you’ve created — by the way, thanks for sharing your geotools on Github)?

A: My current processes are usually very Mapbox-centric: Turf.js or ad hoc scripts for data analysis, Tippecanoe for simplification and tiling, MBView for previewing, and Mapbox Studio for styling. Sometimes I still generate PostScript files instead of web maps. The tool from outside the Mapbox world that I use most frequently is ogr2ogr for reprojection and file format conversion. It is still a constant struggle to try to make myself use GeoJSON for everything instead of inventing new file formats all the time, and to use Node and standard packages instead of writing one-of-a-kind tools in Perl or C++.

Q: You’re prolific on Twitter. What do you like about it, and what do you wish was better?

A: I was an early enough adopter of Twitter to get a three-letter username, but it wasn’t until the start of 2011 that I started really using it. Now it is my main source of news and conversation about maps, data, housing policy, transportation planning, history, and the latest catastrophes of national politics, and a place to share discoveries and things to read. I’ve also used long reply-to-myself Twitter threads as a way of taking notes in public as I’ve read through the scientific literature on colorblindness and then a century of San Francisco Chronicle articles revealing the shifting power structures of city planning.

That said, the Twitter timeline interface has become increasingly unusable as they have pulled tweets out of sequence into “in case you missed it” sections and polluted the remainder of the feed with a barrage of tweets that other people marked as favorites. I recently gave up entirely on the timeline and started reading Twitter only through a list, the interface for which still keeps the old promise that it will show you exactly what you subscribed to, in order.

Q: If you could go back in time, what data would you collect, from when, and where?

A: I would love to have pedestrian (and animal) intersection crossing volume data from the days before cars took over. Was the median pedestrian trip length substantially longer then, or can the changes in pedestrian volumes since motorization all be attributed to changes in population and employment density?

Speaking of which, I wish comprehensive block-level or even tract-level population and employment data went back more than a few decades, and had been collected more frequently. So much of the story of 20th century suburbanization, urban and small-town decline, and reconsolidation can only be told through infrequent, coarse snapshots.

And I wish I had been carrying a GPS receiver around with me (or that it had even been possible to do so) for longer, so that I could understand my own historic travel patterns better. I faintly remember walking to school as a kid and wondering, if I don’t remember this walk, did it really happen? Now my perspective is, if there is no GPS track, did it really happen?

Q: Are you a geohipster? Why or why not?

A: I think the most hipster thing I’ve got going on is a conviction that I’m going to find a hidden gem in a pile of forgotten old songs, except that I’m doing my searching in promo copies of 70-year-old sheet music instead of in the used record stores.

Maps and Mappers of the 2017 GeoHipster Calendar: Nathaniel Jeffrey

Nathaniel Jeffrey – August

Q: Tell us about yourself.

Before I fell into GIS, my studies in Environmental Science led me to a freshwater conservation project in Kenya, and down sewer pipes in my home city of Melbourne. Honestly, sewers are kind of fascinating if you have a background in biology.  You think tapeworms can only survive in a digestive tract?  Think again!

Professionally, for the last 10 years I’ve worked as a GIS analyst for Urbis, which is an international urban planning consultancy.  It’s an ever-changing, data-driven job, which makes it a fun geo playground.

Apart from that: I cook, I eat, I game, I poke Raspberry Pis while frowning, and I travel (mostly to Japan, it seems).

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).

I’ve lived in Melbourne for 25 years after coming over from the USA with my parents as a kid.  And as any Melburnian will tell you if you give them half a chance, it’s the World’s Most Liveable City.

So one of the big factors influencing “liveability” is the ability of a city’s infrastructure to adequately service its growing population. Melbourne has been growing at a rate over 2% per year for more than a decade, adding 80,000+ new people every year. Melbourne’s population has grown from just over 3 million in 1991 to 4.5 million today, and is projected to hit 6 million by 2031.  I can’t do much to solve the many political headaches that spring up due to such rapid growth, but I sure can make a map.

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

The population data I used is a mix of counts from past censuses (1991 to 2011), and future projections (2016 to 2036).  I would have loved to go further back in time, but the small-area population data isn’t easy to come by.

I converted the population counts for each year into a raster surface representing population density, and then smoothed the heck out each one.  This was a bit tricky, because I wanted to generalise the data enough to create an easily-readable map, but I didn’t want to misrepresent the truth in the underlying data.

Through trial and error, I then found a density value that more or less matched up with the edge of the suburban fringe for each year, based on aerial and planning maps. Applying that density cutoff to each year gave me the isopleths you can see on the map — lines of constant density.

Obviously this approach makes the assumption that the chosen density threshold has accurately represented to suburban boundary in the past, and will continue to do so in the future.  This might not be the case, with a shift towards higher density developments at the urban fringe.  But I think the approach is fine for a map that’s just trying to give a high-level view of the amoeba-like spread of Melbourne’s population.  I would hope that no one tries to make any policy decisions based on this map!

Cartographically I went with a dead simple basemap — just roads and locality names for context.  I made a deliberate effort to label locations where interesting things were happening in the data — lots of growth in a given year, for example.  The colour scheme I chose for the isopleths is…striking.  What can I say; it’s tricky to find ten colours that are distinct enough when placed next to one another, but still look reasonably harmonious as a whole.  I had a bit of fun with the look of the title and legend — I’m no graphic designer, but I like to dabble in design, and steal things that look cool.

Jim McAndrew: “There’s always going to be some next big thing, but the basics remain the same”

Jim McAndrew is a Geospatial Database Developer. Before adding ‘geospatial’ to his job title, he worked on large Oracle databases for pharmaceutical and manufacturing companies. For the last few years, he has been working with the US Geological Survey and the National Park Service to create tools that provide public access to government data.

He sometimes tweets @jimmyrocks.

Q: How did you get into GIS?

A: I have loved maps for as long as I can remember. I used to study the maps in the phonebook, and I knew where every local road went. In college, I decorated my apartment with maps I had purchased from the Department of Transportation.

After a few years working as a software developer in manufacturing, I saw something called a “Mapping Party” for this open source mapping project claiming to be a “Wikipedia of Maps”. I was in luck, they would be holding a party in New York City the next weekend. I bought a bus ticket to New York, paid the extra fee to bring my bike, and I was introduced to OpenStreetMap.

I was hooked, and I thought that maybe getting into mapping could actually be a viable career option. I started attending different conferences and meetups that sounded interesting, and tried to learn all I could about the industry. I started a graduate certificate program in GIS, and eventually got a GIS job.

Q: Where do you work and what do you do there?

A: I am a researcher at Colorado State University working for the National Park Service (NPS) as a Software Developer. I started working on a new system to collect data from all the NPS units using an OpenStreetMap-style approach. I work on tools that allow data from this, and other internal systems, to be displayed on web maps. Now I am the Lead Developer on some of the NPS tools, including the internal side of the NPS mobile app project.

Q: Tell us about a cool project you are working on

A: The NPS mobile application project is the coolest thing that I’m working on, because it’s easy for everyone to access and use. It also involves working with Park Rangers that are extremely knowledgeable about their parks and are excited about sharing that knowledge. The coolest part of it for me is the opportunity to visit the parks and to do a little bit of field work.

Q: What technology (GIS and otherwise) do you use?

A: I try to do all my work using vi and tmux within an Ubuntu Linux virtual machine. For GIS work, I prefer to do most of the processing in PostGIS with a lot of help from GDAL and OGR. I have been working on some fun projects with Python and GeoPandas recently. For work, I do most development in Node.js and browser-oriented JavaScript.

Q: Open source — Y/N? Why?

A: I prefer to use open source software whenever possible. The best part about open source software is that if you can’t figure something out from the documentation, you can always go look right at the source. If there is a bug in the source, you can find it yourself and suggest a patch. It is also easy to package software in a VM or a Docker image and share it with others as a working system without worrying about licensing.

Q: Is open source for everyone, or just for tinkerers?

A: Open source is for everyone! Open source tools tend to be a little less user-friendly and sometimes lacking in support. This has created a market for companies such as Red Hat and Boundless Spatial to provide support and integration for businesses. While the “Linux on the Desktop” dream may never really come true, the future will include more open source tools packaged in commercial software.

Q: Biking, hiking, any other hipster attributes?

A: I enjoy biking, hiking, and kayaking whenever I get the chance. I enjoy craft beer, I sometimes homebrew beer, and I enjoy working with yeast to make breads, pretzels, and pizzas. I was on a locally-roasted-coffee kick for a while (OQ Coffee in Highland Park is very good), but I have recently switched to drinking mostly tea and tisanes. I enjoy listening to a lot of obscure music. I also love emojis. 🎉

Q: Are you a geohipster? Why / why not?

A: No true hipster would self-identify as a hipster, at least according to the Wikipedia article on the subject. I do enjoy following the latest JavaScript and geospatial trends outside of the mainstream. Maybe not enough that I will go back and refactor code just to use the latest JavaScript functions, although I do really like await/async. I also enjoy hand-crafted maps that capture more than just raw data, but instead show how the cartographer views the world. I make sure to get a GeoHipster wall calendar every year.

Q: Words of wisdom for our global readership?

A: A few years ago I went skiing in Aspen, Colorado. If there’s still snow on the mountain, they open on Memorial Day, and charge a severely discounted price. I brought my skis that were a hand-me-down from the 1980s. People started commenting on how cool and “retro” my skis were. They were so out of date that they were cool again.

There’s always going to be some next big thing, but the basics remain the same. Don’t focus on doing what’s cool now, but instead focus on what you want to work on or learn, even if it’s something completely different than what you’re doing now; eventually, it’ll be cool again.

Amy Sorensen: “Keep pushing the arbitrary boundaries between geospatial and IT”

Grew up on a farm in Iowa. Started my GIS career as an intern for Emmet County, working on first iteration of E-911 for the sheriff's department. Moved to South Dakota from there and worked for the SDDOT for a while with the esteemed title of “Automated Mapping Specialist”. Really enjoyed the work but was looking for a faster pace and more of a challenge. Ended up taking a project-related position with a consulting firm working for DM&E railroad out of Sioux Falls. Had great fun learning all about rail, sidings and frogs. When that project ended, I decided to take a position with HDR and moved down to Omaha, Nebraska, where I am currently.



Q: How did you get into GIS?

A: I had been doing in-home child care, I have an Associates degree in Early Childhood Education. I was bored and broke and wondering what I should do. Driving down the road I heard a radio ad for the local community college that talked about computers and mapping. I thought… “I love maps!” and went and signed up for the program after that.

Q: You work for HDR, an engineering company. Tell us what you do there.

A: What I do day by day really varies based on the projects I’m on. The funnest part of my job is the variability of what I am involved with on a week by week basis and meeting new people and learning about what they do. I work on hydrology projects where we are looking at flood zones, levees, or stream flows for one project, and then I am managing the GIS database for a large transportation project and dealing with right of way, utilities, and shifting contracts. I also like to code, so I will put together web maps or write some scripts to automate work flows. It’s really fun to listen and evaluate what is currently being done and then to apply some type of technology to help streamline and document the work as well. Recently I’ve gotten involved with the sustainability group here at HDR, and now there is great potential to mix my love for GIS with my desire to make the world a better place.

Q: Do engineers “get” GIS?

A: Yes! I would say there are varying levels of “get” involved. I find that if you are on a project, and learn as much as you can about the overall big picture, then it is easy to plug GIS into it in ways that make sense and help meet those project goals. If someone isn’t getting the point of using GIS then it could be that you aren’t getting what the big picture is for them.

Q: What technology — GIS and other — do you use at work? What do you / don’t you like about it?

A: Of course the big technology provider I work with is Esri, I work with the full suite of Esri products. I really love working with Python and use Notepad++ for the majority of that type of work. It’s simple and straightforward. When I’m working with JavaScript I have been using Atom, which has been a good editor. I’ve gotten to use Jupyter Notebook on projects as well now, and really have found the power in being able to quickly write code, see the results, then tweak. Being able to revisit later and use the notebooks to document what has been done is priceless. I’m digging into some new (to me) JavaScript frameworks, and am really interested in playing with Ember. I’ve heard good things, and Esri uses it a lot and is starting to push out add-ons using it.

Q: You were a volunteer in a GISCorps project for North Korea. Tell us about the project, why you did it, and what you got out of it.

A: This project was for the World Food Program (WFP) and the information Management and Mining Action Program (iMMAP). We digitized features like roads, cities, rivers, and rail from historical maps. The idea was to create this data to support their humanitarian efforts. I got involved since I had been listed as a GISCorps member for some time and was waiting for a volunteer opportunity to come up that I could do at home. This project was great and I was able to put a couple hours in on a weekly basis. I am always trying to save the world and it really gives me a great sense of satisfaction to be able to do something with the skillset I have to help the world be a better place.

Q: You do lots of volunteer work, not just GIS. Tell us about your other volunteer activities.

A:  I do like to do volunteer work, it’s my desire to make a difference that drives it. Though I would say I’m not doing a ton right now, there are a few things I’m involved in. I do manage a website for a local grassroots organization. For the last couple years I’ve been able to create some mapping for a local group that puts together garden tours in Omaha and hosted for them as well. Over the years I’ve done things like volunteer for Boys and Girls Homes, and also was a baby rocker at a NICU for some time. I think volunteering really does add a lot to your life and gets you out in the community, which is fun.

Q: What is the tech scene like in Omaha?

A:  I think the tech scene is good. We have some good coding school options in Omaha, which have fast turnaround to get people into the workforce. There are coding groups that happen for kids and teens like Girls Who Code, and we have a really innovative tech library that offers classes and opportunities to work with and learn all kinds of software and cool things like 3D printers and maker events. There are also some good groups I’ve found through Meetup — Women In Technology of the Heartland is one, and it has great social events and is a good support group for those working their way up or into technology fields. There are other groups I’ve not joined yet based on Python and JavaScript that I plan on checking out soon as well.

Q: What is the hipster scene like in Omaha?

A:  Isn’t that the same as the tech scene? 😉 Ok, maybe not but there is some crossover. The hipster scene is good. There are some known areas in town where you will find great local music, food, and events. One of my favorite is the Benson First Friday Femme Fest — it’s an amazing opportunity to see all kinds of females taking the lead role and sharing their music, poetry, and art to the masses.

Q: Knitting and Dr. Who — is that hipster or what?

A: Probably. I still need to knit my Dr. Who scarf, I think once that is completed then I can really grab the hipster trophy. My list of nerd interests is strong and I think if I could pull together a group of geohipsters to crash the UC dressed in Dr. Who cosplay, then my life would be complete.

Q: Do you consider yourself a geohipster? Why / why not?

A: Sure. You know, unless in considering myself one I negate the title. 🙂 I think a geohipster is anyone who is constantly striving to do new and cool things with geospatial data. With that definition, I’m 100%.

Q: On closing, any parting words of wisdom for our global readership?

A: Keep pushing the arbitrary boundaries between geospatial and IT. Data is data and we all can and should be playing and working together. Also — volunteer for something. You do need to get away from the computer once in a while, and it will change your life to do so. And finally, if you love Dr. Who we should talk. 🙂

Nate Smith: “Visit a new place in the world; reach out to the OSM communities there”

Nate Smith is technical project manager for the Humanitarian OpenStreetMap Team. He leads out the OpenAerialMap project and dives into all things technical across HOT’s operations. Originally from Nebraska, he is now based in Lisbon, Portugal, slowly learning Portuguese and attempting to learn to surf. 

Q: We met at State of the Map Asia in Manila! What was it that brought you to the conference?

A: I came to State of the Map Asia through my role in two projects with the Humanitarian OpenStreetMap Team: OpenAerialMap and a new project called Healthsites. I had the chance to give short presentations about the projects, plus I wanted to connect with the OpenStreetMap community in Asia about the projects to get feedback and input on the direction of the projects.

Q: Tell us about the Humanitarian OpenStreetMap Team (HOT) and how you got involved.

A: I’ve been involved in HOT in one way or another since 2011. At the time I had just joined Development Seed in Washington DC. I began to get involved in any way I could with HOT, most of it started with trainings about Mapbox tools or collaborating on projects. Most of it initially revolved around helping identify data that could be helpful in an activation or joining in tracing. Over the years, I gradually got more involved in working groups which is the best place to get involved beyond contributing time to mapping. I’ve since joined HOT as a technical project manager to help build and manage projects around some of our core tools like OpenAerialMap or OSM Analytics.

Q: For those who may not be familiar with HOT, “activation” is kind of like bringing people together to participate in disaster mapping or a similarly geographically-focused humanitarian mapping effort, did I get that right?

A: Right, a HOT activation in the traditional sense is exactly that. It is an official declaration that the community is coming together to aggressively map an area for a disaster response. The Activation Working Group is one of several working groups where anyone can get involved, and they define the protocols, monitor situations, and are in contact with many OSM communities and humanitarian partners around the world.

Disaster mapping is a core part of the work HOT does. Not everything but still a big part. If you’re interested in helping think about activation protocols or want to help organize during an activation, come join and volunteer your time to support the work.

Q: What are some interesting projects you’re working on?

A: I’ve been actively working on two interesting projects: OpenAerialMap, and for lack of a better name at the moment, the Field Campaigner app. OpenAerialMap launched two years ago and we’ve been slowly rolling out new features and working with partners on integrating new data since. What’s interesting is the work we’re doing this summer — we’re rolling out user accounts, provider pages, and better data management tools. This is exciting as it lowers the barrier to start collecting imagery and contributing to the commons.

The second project is our new Field Campaigner app. It has a generic name at the moment but it’s part of a move for us to have better tools to manage data collection in the field. A majority of the work the global HOT community does is remote mapping. While this is super critical work and extremely helpful for people on the ground, there is a gap in how work is organized on the ground. This work looks to help improve the way data collection is organized and coordinated on the ground — we want to see field mapping in OpenStreetMap to be distributed and organized well. This work also crosses over some similar work that is happening across the board in this area — Mapbox is working on analyzing changesets for vandalism and a team from Development Seed and Digital Democracy through a World Bank project are working on an improved mobile OSM data collection app.

Q: How easy/hard is it to build these tools? Once they’re out in the world, what are some ways that people find and learn how to use them?

A: It’s not easy building tools to meet a lot of needs. A core thing for success many times is dogfooding your own work. We’re building tools that serve a wider audience but at the core we’re testing and helping spread the word about the tool because we use it.

But just because it’s not easy doesn’t mean people shouldn’t be trying. The more we experiment building tools to do better and faster mapping, whether it is remote or in the field, the more information we will have to improve and address the challenges many communities face.

Q: It looks like your job is fairly technical, but also involves outreach. Is there a particular aspect of your work that you enjoy the most?

A: I think the mix of technical and outreach is what I love most. Spending part of my day diving into some code while the other part talking or strategizing with organizations is what I’ve had the chance to do over the last six years through working with Development Seed and now HOT. I enjoy trying to be that translation person — connecting tools or ways of using data to solve real-world problems. I think one of the things I enjoy the most is the chance to help build products or use data with real world impact. Being able to support MSF staff responding to an Ebola outbreak at the same time working with world-class designers and developers is pretty great.

Q: Looking at your Twitter feed, you seem to travel a lot. What’s your favorite / least favorite thing about traveling? Favorite place you’ve been? Any pro travel tips?

A: I traveled a bit while living in DC but now that I’m living in Lisbon, Portugal I’ve had the chance to do some more personal travel throughout Europe which has been great. This past year I’ve had a chance to travel through Asia a bit more through HOT-related projects. My favorite part of traveling is the chance to meet people and experience new cultures or places. There are some incredible geo and OSM communities around the world and it’s been awesome to meet and work with many of them. Least favorite — awkwardly long layovers – you can’t get out.

I think my favorite spots have been Bangkok and Jakarta. I find that I enjoy big cities that have great food options. As for tips, I would say pack light and do laundry when you’re traveling, and always make time for good local food.

Q: Would you consider yourself a geohipster? If so, why, and if not, why not?

A: Heh, that is a great question. I think I’ve become less geohipster moving to Portugal. I drink light European beer, I don’t bike because there are too many hills, and drink too much Nespresso. Although I’m still a Mapbox-junky, work at a cowork in my neighborhood, and love open source, so maybe I still lean geohipster. 🙂

Q: On closing, any words of wisdom for our global readership?

A: Get out and visit a new place in the world if you can. And while you’re at it, reach out to the OSM communities there and meet them in person. You’ll meet some incredible and passionate people.

GeoHipster Mixtape Volume 2

GeoHipster Mixtape Volume 2

Last April we published the first GeoHipster Mixtape,  a look into the tunes we chill to, scream to, and grind to during the work day. This is Volume 2.

On most days we listen to the soundtrack of work:  phones, email notifications, office chatter, or the sound of the city. For some of us our daily soundtrack is a carefully curated playlist of our favorite tunes. Being in the latter group, music can provide the white noise needed to push through an hour of getting the labels “just right”, or the inspiration that sparks the fix for that problem with your code.

I was curious about what others are listening to during the day — what does a geohipster listen to?

As you might expect, asking anyone who likes music to pick a few songs can be a near-futile task. A desert island playlist would be drastically different from a top side one, track ones playlist. Making a mixtape is subtle art, there are many rules — like making a map. I recently talked to several of our interesting colleagues in geo to see what tunes get them through the day. I asked the impossible: pick  3 tracks they love to share for a mixtape.

For your listening and reading pleasure we have hand-crafted a carefully-curated playlist from the geohipsters below, complete with liner notes of the cool work they do while listening to the tracks they picked.

Ps. i couldn’t help but add a few selections of my own.
Sorry/Not Sorry

For your enjoyment, a YouTube playlist — the GeoHipster Mixtape Volume 2

 Brooke Harding @BrookEHarding  || GIS Specialist at USAID-Macfadden

Brooke is a Cartographer and Data Analyst specializing in Europe & Asia and government acronyms. Outside of the office she’s all about supporting her fellow #geopeeps through organizations like the NACIS (Check out their October 2017 conference in Montreal, eh?) and eating her way through #geobreakfastdc one waffle at a time.

  • Paul Simon feat. Chevy Chase – Call Me Al
  • T-Pain – NPR Tiny Desk Concert
  • Nahko and Medicine for the People – Black as Night

John Nelson  || Cartographer at Esri

John works in a small wooden shed in his back yard. He does everything from making points on a map glow like fireflies to hacking up cartographic techniques to use on your next map.


  • Seu Jorge – Changes (from The Life Aquatic with Steve Zissou)
  • Sigur Rós – Hoppípolla
  • Flatt & Scruggs – Doin’ My Time (from 16 Original Bluegrass Hits)

Cristen Jones // UI designer

Cristen’s an urban planner by training and used to be one of those civic hackers found at Boston-area hackathons and meetups. She’s worked with Code for Boston on and , but more recently    joined Maptime Boston as a co-organizer.

  • Childish Gambino – Break
  • Madeon – Pop culture
  • Daddy Yankee – Shaky Shaky

Dylan Moriarty // Illustrator & Cartographer

Dylan is bad at writing bios, but he has a swell website — believes in open source — loves hand-made maps & hand-drawn elements — helps run GeobreakfastDC & MaptimeDC () — works with the Humanitarian OpenStreetMap Team & designed Missing Maps — spends most waking hours listening to tunes

  • Buddy Rich – Norwegian Wood
  • tUnE-yArDs – My Country
  • Medeski, Martin & Wood – Let’s Go Everywhere

Amy Smith  @wolfmapper // Uber
Policy research, data science & mapping at Uber. Thinks a lot about cities, maps, and transportation. Sometimes writes about them too. Proud GeoHipster interviewer and board member.


  • Todd Rundgren – Hello Its Me
  • YMCK – Magical 8Bit Tour
  • Gillian Welch – Hard Times

Hannes  // HafenCity Universität Hamburg

Hannes breaks GDAL doing crazy things, procrastinates with Shapely doing silly things, and enjoys QGIS doing useful things.


  • L.S.G. Transmutation (reworked)
  • Bohren & Der Club of Gore – On Demon Wings
  • Wolfgang Hartmayer – Every Day

Juliet Eldred   // Student at the University of Chicago

Juliet is a Geography/Visual Arts double-major, which means she spends a lot of time making and looking at maps. When she’s not sleeping, biking, or yelling at QGIS, she runs the geospatial meme Facebook group “I feel personally attacked by this relatable map” and works as a DJ at WHPK, her school’s radio station.

  • Built to Spill – Car
  • Sleater-Kinney – Light Rail Coyote
  • Emperor X – Wasted on the Senate Floor

Maps and Mappers of the 2017 GeoHipster Calendar: Mark Brown

Mark Brown MSc – February

Tell us about yourself.

I am an ecologist and conservationist with strong technical skills in GIS & Remote Sensing. My interests lie in the application of geospatial technologies to help solve ecological and environmental problems. I love developing novel techniques in areas where these technologies might not have been previously used.

For the past several years I have been working on landscape scale habitat restoration schemes such as the Yorkshire Peat Partnership in the uplands of northern England. There is a very special type of habitat found here known as a blanket bog. Referred to as the ‘rainforests’ of the UK, they are home to many unique plants and animals. These areas of land are not covered by trees however, but a ‘blanket’ of peat material that has formed over thousands of years through the accumulation of dead plant material such as Sphagnum Mosses. Due to this they act as a massive carbon sink. They are also a very important source for much of our drinking water and help to regulate runoff and therefore flooding. They are also an important site for leisure and recreation.

Despite this, most of these habitats are in a heavily degraded state. Mismanagement of this land through burning and overgrazing, as well as natural causes such as wildfires, is causing much of it to erode away. Once peat is exposed to the elements, it rapidly wears away releasing carbon and entering waterways, where it turns the water a brown colour similar to English Breakfast tea. Peat that is dissolved in waterways is causing a problem for water companies, as they have to spend millions of pounds each year to remove the peat through chemical treatments.

The project I work on aims to reverse degradation of the blanket bog by providing the stable conditions necessary for its recovery

In order to do this we need to identify those areas currently undergoing or most at risk of erosion and this is where I come in.

As well as being qualified with an MSc in Geographical Information Systems, I am also a certified Unmanned Aerial Vehicle (UAV) pilot. I use a fixed-wing drone known as a senseFly eBee to capture aerial imagery and to generate digital surface models (DSMs) of the habitats that we work on. This data is of a very high resolution (up to 1.5cm!). This gives me the capability to examine and analyse the blanket bogs in an unprecedented level of detail.

I use this data within GIS and remote sensing software to carry out a whole range of analyses. This includes but is not limited to topographic modelling, hydrological analysis, feature extraction, Object-Based Image Analysis (OBIA) to detect different types of vegetation communities and exposed peat, 3D visualisation, and the creation of cross-sectional profiles to determine the dimensions of eroding gullies.

If you’re sat there reading this and wondering what on earth is a blanket bog?! I’d suggest having a look at the Yorkshire Peat Partnership Facebook page. There are lots of interesting photographs of the landscapes as well as our restoration works and imagery of the UAV in action. See link below:

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).

I’m sorry to admit it but blanket bogs just aren’t sexy! With no charismatic fauna, cold, wind and rain, to the untrained eye there’s not really much there. They are often seen as barren wastelands. However if you delve down among the undergrowth, there are many interesting species of lichens, mosses, and England’s only carnivorous plants!

This map was part of a series of images that I created in an effort to make blanket bogs more interesting to the public eye. It has been used in Yorkshire Peat Partnership reports as well as at international conferences.

I was interested in creating a series of photorealistic terrain models of blanket bogs. I visualised the terrain in open-source 3D modelling software with a light source over a white background. This creates the interesting shadow effect so the terrain looks like it is floating over a white surface.

This was a departure from my usual workflow as I normally work exclusively with GIS software such as QGIS. However I found that this was providing too many limitations for graphical visualisations and it was interesting to learn an entirely new piece of software from scratch.

Actually I was quite surprised to be selected for the calendar. I think if I was to enter the image again I would put more information on the image regarding what the image actually is and how it was generated. Hindsight however is a wonderful thing!

I was super pleased to be selected and hopefully this will introduce a very novel application of GIS and remote sensing to a wider audience!

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

The UAV I used to survey the site was a senseFly eBee. ( This is a small fixed-wing drone that is proving to be one of the most popular commercially-available drones for surveying and mapping purposes. The UAV is fully automated and flies along pre-defined transects,taking photographs along the way.

The imagery that was captured was then processed within photogrammetry software known as Pix4D Mapper ( This software is used to generate point clouds, digital surface and terrain models, orthomosaics, and textured models.

The resulting orthophotograph and digital surface model was then imported into Blender ( where the image was rendered. Blender is an open source 3D modelling software package. It is more commonly used for 3D art, animation, and the creation of computer games.

Maps and Mappers of the 2017 GeoHipster Calendar: Ralph Straumann

Ralph Straumann – June

Tell us about yourself.

I’m a consultant, data analyst, and researcher with EBP in Switzerland and the Oxford Internet Institute in the UK. My background is in geography, with a PhD in geoinformation science from the University of Zurich. Besides GIS I studied remote sensing, cartography, and political science. In my work for EBP I assist clients with data analysis tasks, do strategy and organizational consulting, and build tools, geodata infrastructures, and workflows. In my free time I occasionally blog about GIS, data, and visualization.

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 few years ago, Stephan Heuel and I developed a raster-based walking time analysis tool. This product has since matured into Walkalytics. Based on OpenStreetMap and/or cadastral surveying data, we can infer the time it takes somebody to walk to or from a place, construct pedestrian isochrones, and compute quality of service metrics, e.g. for public transit. We can carry out these types of analyses world-wide, at high resolution, very fast, and taking into account the topography. The map serves as an illustration of the capabilities and versatility of Walkalytics.

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

I used our Python Walkalytics client and a test subscription to the Walkalytics API to derive the data for the map. Besides, I used data from the (in my opinion, fantastic) Natural Earth. I then designed the map entirely in ArcMap. I tried to move away from the ArcGIS defaults. I’m simplifying, but I think a map tends to be good when you cannot tell straight-away which software has been used to make it. For the interested: Below you can see a GIF of some of the revisions of my map for the GeoHipster calendar:

Maps and Mappers of the 2017 GeoHipster Calendar: Jan-Willem van Aalst

J.W. van Aalst, Ph.D. – November

Tell us about yourself.

I’m a cartographic designer and data analyst. I live and work in The Netherlands. My background is in computer science; I did my Ph.D. on knowledge management at Delft University. These days I mostly advise the Dutch Emergency services on (geo) information management.

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).

The map is part of my Dutch OpenTopo series, which I designed to supply the Dutch emergency responders with the most up-to-date topographic maps possible. I’ve always experimented with combining the best ingredients of various map sources, including the geospatial base registries published by the Dutch government as Open data. The result is now available at

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

The map was made using QGIS. Some post-processing of the raster output of QGIS is done using GDAL. The map data is stored in a PostgreSQL/PostGIS database. The data itself is made “PostGIS-ready” using the Dutch NLExtract tools developed by some geo-wizards also associated to the Dutch branch of The map features data from several Dutch Base Registries (BRT, BAG, BGT, BRK) and also contains various elements extracted from OpenStreetMap.

Guido Stein: “Spatial is now a first-class citizen in most databases”

Guido Stein is a Geospatial Data Alchemist who has been working for Applied Geographics for the last 10 years. He is also the founder of AvidGeo, a Boston area meetup group that hosts events for the geospatially inclined, and he is the Co-Chair of FOSS4G Boston 2017. Having lived in Somerville, MA for over a decade, he has truly absorbed some hipster characteristics including growing a beard “ironically” and riding to work on a bike with his little dog Beau.

Q: You are the Conference Co-Chair for the 2017 FOSS4G conference in Boston. Isn’t that like a lot of work? Why do you do it?

A: It is a lot of work. I have been working and organizing community events in the Boston area for over a decade. I do this work because I want to attend these events and the only way these events happen is if someone is willing to do the work. I am not afraid to be that someone. I really enjoy being involved in community work. I like to learn about what cool things everyone else is up to. I also like sharing in the victories and commiserating around failures specific to our community. If these events didn’t exist, who would share a beer with me over the limitations of using shapefiles?

Q: Tell us about the conference. How did you get involved?

A: I think that it was my boss, Michael Terner, who first approached me about it. I have been a big fan of the Open Source Geospatial (OSGeo) community for a long time. Sadly, other than participating as a user, I did not have much interaction with the community. Michael had participated in a few FOSS4G conferences and was ready to get more involved. He approached me to put together a bid knowing that I would jump at the chance to build a stronger tie between OSGeo and Boston.

The reason I want to see FOSS4G in Boston is that I think that there are many groups locally that would benefit from exposure to the OSGeo community and from getting a chance to show off what they are up to. I have been trying to unite people in the Boston area around geospatial for over a decade, and there is such a great and exciting group here doing things in business, government, academia, as well as in the startup tech world.

Q: You and I first met in Boston in 2011 in the offices of Applied Geographics. You are still there, so you must like it. What do you do for AppGeo?

A: I recently celebrated my 10th anniversary at Applied Geographics. When I started I worked on parcel edits, parcel generation using scanned plans and COGO input, utility system development all working with many Esri tools. Since then, I have been really happy to explore many different tools from FME to QGIS to PostGIS for editing, collaborating on, and analyzing data.

My mantra these days is “Spatial, not special”. My work these days focuses on how to use spatial knowledge to solve data problems. I am very happy becoming a more powerful user of all the tools I use, but I feel super powerful when I figure out complex SQL queries to solve problems. I love working on the database solutions.

Q: How did you get into GIS? Why?

A: My father introduced me to GIS in high school. He was a city planner (since retired), and knew that I would really enjoy this use of technology. I have always liked playing and working with computers.

I attended Clark University. Initially I was interested in the psychology department, but found coursework in geography to be very fulfilling and soon started to work with the Clark Labs. I was very fortunate to work closely with the staff and Ron Eastman. They were very supportive of my thirst for knowledge.

Q: Tell us about some of the cool tech you use these days. Describe a cool project that you currently work on.

A: Giggles…

Cool tech, well… the thing I think is coolest right now is my $10 Raspberry Pi Zero W. It is so exciting to have such a cheap computer with Wi-Fi and Bluetooth built in. It is a powerful tool for building IoT projects and also gives me a chance to improve my Linux chops. I really want to buy a bunch of these and create some simple navigation tools around them.

The last year has had me working on projects using Python, FME, PostGIS, CARTO, SQL Server, Oracle, and many other tools. My co-worker Calvin Metcalf has been trying to get me to switch from Python to Node. I really like the work CARTO has done to make mapping and PostGIS available online, it’s really quite powerful.

Q: Do you like open source for pragmatic or ideological reasons? Explain.

A: Both. I like tools that work and I want tools that I can contribute to. I think libre software is the ideal, but I think there is a lot of useful and good grey area in the open source community that is far superior to proprietary solutions.

Q: You knit, which is amazing. I did try it, but didn’t have the patience. Tell us how you got into knitting, and whether you see parallels between knitting and coding.

A: I started knitting when my wife took it up many years ago now. I really love making something with my hands and I also enjoy spending time with people in knitting circles; it’s like the ticket to enter a reality TV show of some very interesting and creative folks. I highly recommend it to everyone.

There is a wonderful tie between raster-based geospatial and knitting; they are both based on basic data principles. Both have rows and columns. Someday I really want to knit some NIR imagery into a hat.

Q: You ride a bike, which — along with knitting and the beard — puts you in the running for the perfect hipster. Is there a hipster attribute that you wish you had but lack?

A: Wait, there are so many more hipster attributes:

  • I live in a hipster community
  • I prefer artisanal chocolate and farm-to-table dining
  • I run my own hipster website

The only hipster attribute I wish I had that I lack is the hipster gene that makes them all slender and buff. I am now getting ready for a 9K in July and this non-skinny-jean-wearing butt is just not as easy to move around as I would like it to be.

Q: Are you a geohipster? Why / why not?

A: I am a poser. I am a pretender. I am an imposter.

I am not good at defining myself as any particular thing. I love to learn and I love to listen. This makes me less a specific type of person as much as it makes me a person who enjoys being in the presence of others who are specific about who they are.

I have been running a hipster web site for years trying to figure out what being a hipster means and as far as I can tell, no one really knows. Hipster is used as both a positive and negative, so I don’t know if I am or am not.

But let’s do the checklist once more:

  • Lives in hipster community, check
  • Rides his bike to work, check
  • Has a beard, check
  • Goes to farmers markets, check
  • Can tell you about local beer, chocolate, and cheese makers, check
  • Has skinny jeans, nope
  • Can describe a bespoke projection, nope

Q: On closing, any parting words of wisdom for our global readership?

A: Get out of your silo. Spatial, not special.

Spatial is now a first-class citizen in most databases, so we should use databases and other data tools and not be totally reliant on vendor to solve our spatial needs.

Also, check out my friend’s local chocolate CSA ( it is the most amazing chocolate made by the most wonderful guy around.