Harel Dan is a GIS and Remote Sensing analyst based in Israel, and the GIS Coordinator at HaMaarag - Israel's National Nature Assessment Program. Twitter / Website
Q: You’re the GIS Coordinator at HaMaarag, Israel’s National Nature Assessment Program. What is HaMaarag, and how does GIS factor into the program?
A: HaMaarag is a consortium of organizations that manage open landscapes, that was set up to provide evidence-based knowledge to managers and decision makers. We run several long-term projects that take place all over the country, in varying biomes and their ecotones, from evergreen Sclerophyllous woodlands to hyper-arid shrubs, monitoring several classes like Mammals, Birds, Reptiles, as well as vegetation. As such, the entire process of planning out, sampling and analysing the data is dependent on locations. Be it precise measurement of monitoring plot corner pegs with GPS, or creating spatially-balanced sampling methods. My job also entails collecting and processing spatial data from other organizations, with their peculiarities and errors.
Q: You do a mix of technical work, coordination with other agencies, and field work. That sounds like an interesting mix – could you describe a typical day in the life?
A: 6:00 AM, Phone rings, ornithologist on the line, asks me to explain to him how to load the background layer to the Fulcrum monitoring app. 8:30 AM, Log on computer, answer email from chief scientist of the nature and parks authority. 10:00 AM, Run the script that scrapes data from that website. 11:45 AM, Finish that map and send it to graphic design. 13:37 PM, Coffee. 14:03 PM, Back in office after wandering around the labs in the Steinhardt Museum of Natural History, where our offices are. 15:00 PM, Finish a call with the Open Landscapes head at ministry of environmental protection. 16:00 PM, Send drone orthos segmentation results to the botanist for assessment. 17:30 PM, Put kids to sleep. 19:00 PM, Goof around on whatever personal project distracts me these days.
Q: Based on your Twitter account and website, it seems you also take on a good amount of personal projects. What do you look for in a personal project? Any favorites you’d be willing to share?
A: My personal projects are a mix of disciplines and topics that on the one hand interest me, and on the other can be used as an excuse or reason to delve into something new; a concept, a programming language, a tool, etc. Furthermore, as a Geographer, I think I can bridge the gap between the analytical aspect and the human story it tells. For instance, over the summer I’ve made and published a constantly-updated map of fire damage in the south. I saw that there was a lack of connection between news reports and the scale of the damage that was creating misconceptions and lack of understanding. So telling this story was a chance to try out new internet tools to help streamline the work and be easy to read and comprehend for the general public.
Q: What inspired you to publish your analysis of SAR data to identify military radars? Were you nervous at all about the sensitivity of the subject matter?
A: I was intrigued by a peculiar image artifact when I was trying to incorporate Sentinel-1 data in my landcover classification mapping, which happened to appear mostly over broad-leaves and coniferous forests. After tweaking a Google Earth Engine script I’ve noticed that these artifacts converged over a single constant source, so I’ve figured out what these were. After a year or so of hesitance, asking around what should be the preferred action, and actually getting in touch with the Army, I had a job interview for a company that does SAR analysis, so I knew this would be a perfect time to publish the story. So with a tongue-in-cheek image alluding to some issues publicising the location of the radars in my country (It was a PNG image I made in MS Paint that read [REDACTED], you won’t believe how many people over-analysed this), I posted my findings on social media.
I got the job btw, but declined to take it as the conditions weren’t manageable from my perspective.
Q: You’ve successfully had your work featured in multiple publications. What advice do you have for other geohipsters out there looking to get more exposure?
A: Hustle. Made something interesting? Think you’re onto something? Post it on social media. If your career is not dependent on the number of publications in peer-reviewed journals, there’s no reason not to share your work and ideas with the geo community, no matter how half-baked they are.
Q: What do you do in your spare time? Any hobbies?
A: I have a garden with some fruit trees that I tend to when it’s not too hot, but other than that, I’m wholly immersed in being a full time parent to two small kids. Whatever spare time I have, it’s used to wind down and relax with techie reading material, or go on twitter and see what others are up to and engage in the war on Shapefile and banter on that other GIS software.
Q: Are you a geohipster? Why or why not?
A: I tick about a dozen or so results in the GeoHipster poll tally, so I guess I’m on the geohipster spectrum, even though I never got into the laptop stickers and pin badges fad. Besides, the backside of my laptop screen has velcro strips which I use to firmly attach dongles, chargers and an external drive full of hoarded geodata to reduce desktop clutter, this way I have room to place old printed atlases, a working sextante, PostGIS cheatsheet… OY MY GOD I’ve just realised I’m a geohipster.
Q: Any final words of wisdom for our global readership?
A: Don’t use Twitter’s Bing-based translation tool, it’s horrendous.
Ari Gesher, Matt Gordon and Julia Chmyz work at Kairos Aerospace, a Bay-Area-based company specializing in aerospace solutions for environmental surveying and digital mapping. Ari, Matt and Julia were interviewed in person during the 2018 Mapbox Locate Conference in San Francisco.
Describe Kairos Aerospace.
Ari: Kairos applies the notions of faster, cheaper, iterative cycles of technology to Aerospace. Specifically, with the mission of building sensors to spot very large leaks of Methane.
Julia: A less high-level description of Kairos — Kairos deploys aerial sensors, spectrometers, optical cameras, and thermal cameras to conduct large-scale surveys of assets from oil and gas companies, to survey those assets to discover things about them.
Matt: Kairos is a bunch of physicists and engineers who care about health and safety and climate change. We fly sensors and sell data about environmental pollutants (specifically methane) to oil and gas producers.
What led you each to Kairos?
Ari: I ended up at Kairos because the two original founders, Steve Deiker and Brian Jones, both worked at Lockheed for a long time, and they decided to start their own company. Steve’s wife worked with me at Palantir, and they knew that everything they were going to do was going to require a lot of heavy data processing, and that was not an area of expertise for them. They approached me for advice around what it would take to build a team with that kind of ability. That was late 2014. I was instantly interested, it sounded really, really cool… But, for reasons of childbirth, I was not about to switch jobs; I ended up being the original angel investor. Two years later I came on board as the director of software engineering.
Julia: Brian’s wife worked with the woman who was married to my grandfather. And so, my grandfather was actually another one of those original investors — This was 2015 — and he was saying to me, “Julia, there’s this great new company.” And I’m like, “Okay, Grandpa… I’m sure. That’s cool.”
Grandpa says, “They’re so great! They’re so great! You gotta send ‘em your resumé.” I was in school at the time (I’m a year out of college now), and I said, “Okay, fine grandpa, I’ll send ‘em my resumé.”
I hadn’t really looked into it, I just didn’t really want to work at this company my grandpa thought was so cool. But I sent my resumé, and I was really clear about this, I was like, “My grandpa’s really excited about this, but I’m not sure it’s such a good fit.” — expecting to give them an easy way out.
And instead, they wrote back and said, “We’re really interested! Your resumé looks great, we’d really love to have you on board.” So I came in and talked, and actually got to see for myself. And I was like, this looks really great. So I was an intern in the summer of 2016, when we were a third of size we are now. And then I came back full-time a year ago.
Matt: There’s a lot of funny history between Ari and I, which I won’t go into. I had just done my postdoc at Stanford in physics, and Ari recruited me to go work at Palantir. Then, about six years later, I quit and I was bumming around a bit, and making fire art.
Matt: Making fire art… yeah… and I thought I would go get a real job. Ari, at that point, was an angel investor, and he tried to recruit me into his current job.
Ari: That’s right, I tried to hire Matt for my current job.
Matt: And I turned him down to go start my own company, to develop online treatment for substance use disorders. Which, let’s say, the world was not ready for… [Polite chuckles] Mark my words: you’re going to see it.
And then about a year after doing that, Ari saw I was on the job market again, and asked me to come work at Kairos, on a team of four people – two full-times, an intern, and a couple of physicists who commited code to our code base (for better or for worse).
How many people are there now?
So it’s grown quite a bit?
Matt: Yeah. It’s moving.
Ari: Yeah there was sort of two different phases. The first two years, Brian and Steve quit their jobs and were literally in their garage in Los Altos, developing the hardware that is the heart of the methane sensor (which is the imaging spectrometer). And there’s pictures; like, one of them’s across the street, positioning a methane cell in the light path of a heliostat, the other one’s at the laptop with the original Mark-1 Spectrometer, making sure it worked.
Do they still have that?
Ari: They do — it sits on a shelf, and looks like a broken projector or something. [chuckles] So, the first two years was just validating that the hardware would work, and at the end of that, they had the design for what is today our production spectrometer, and the first production-designed unit (although we’re probably going to throw that one out pretty soon.)
The next two years have been developing both the operational side (How do we hook this thing up to a computer, and fly it, and collect data?), and also the software pipelines that sit behind it (How do we take that data off the instrument once it’s done? How do we upload it to the cloud, and develop the algorithms, from scratch, that turn that spectrographic data into the plume images that we have?).
Walk me through the process of: going out and sensing the area, to: you have a final product; and what that final product looks like.
Ari: The way that this works is that we’re given an area, a spot on the ground — the job we’re working on now is about 1,300 square miles?
Matt: We’re given a shapefile.
Ari: Right, we’re given a shapefile, and if we’re lucky, we’re also given a list of assets (another shapefile that tells us where all their wells and storage tanks and things are, so we can identify things once we find a plume over them). We then draw up flight plans to go fly over that area… like, if you look at it, you see the plane going back and forth like a lawn mower. And then, that data goes through the processing pipeline.
Example of a flight path
What comes out the other end are a stack of rasters that show us various measures of what the spectrometer has picked up. At a very rough level, what we’re actually sensing is a methane anomaly. Methane is everywhere in the atmosphere at some level; so it’s not “Is there methane here or is there no methane?”, but “Is there elevated methane?”
We use the large survey area, or chunks of it, to develop what we think the background levels of methane are in that area of the atmosphere. And then, we look for places in the data where there are elevated levels, and use that to interpolate a plume shape.
Example of a plume
One of the things we like to do at GeoHipster is geek out about the tools that people use; tell me about your day-to-day.
Ari: We’re mostly a Python shop. Very large amounts of effort dedicated to making GDAL install and compile correctly.
Matt: I do a lot of the GIS stuff at Kairos. There’s all the code for taking remote sensing data and GPS, and figuring out where that was placed on the ground. Then, taking all of that and creating GeoTIFFs out of that, with all the different metrics that we’re interested in.
Ari: And that’s all custom software, we don’t even use GDAL very much. We use GDAL to open the dataset that we write, but how we figure out what goes into each pixel is all ours.
Matt: Yeah, the ground placement of remote-sensed data is an art form… it’s interesting how much we’ve built from scratch. I think people with a lot of background in this probably know a lot of tricks and tools (and I’ve heard tell that there’s a book, but I’ve been unable to find it).
In terms of GIS nerdery: we used to do a lot of ad-hoc analysis in QGIS, and as we were increasing the number of reports we wanted to produce for customers, we wrote a QGIS plugin. It’s custom, and it’s not published anywhere because it’s specific to our workflow and our data, and it gives people summary information.
Anyone who has used QGIS will know that it’s like, incredibly powerful and can be incredibly frustrating. And if anyone from QGIS is reading this, I want them to know that I really appreciate the tool. We love it, and we would use something else if we thought it was better, and we don’t. There’s nothing else better.
Julia, you work on the tools that pilots use when they’re out collecting data. Can you tell us a bit about those?
Julia: There’s the feed that the flight operator sees in the plane, and the spectrometer frames that are being taken. There’s also all the IMU data that’s used for path stuff and all the later calculations… and this is our flight monitoring Mapbox Leaflet. The back end is built in Python, and the front end is in React.
Matt: Ari’s contribution was the X-Wing fighter.
Julia: The point of this is to make everything work as smoothly as possible — so the flight operators don’t have to spend their time staring at multiple log files, which is what they were doing before this.
Matt: So imagine a terminal, and just watching lines of term logs scroll past… in an airplane. In a very small plane.
Ari: Well, now that they use this, they say that they get kind of bored on the plane, because it gives them everything they need. In fact, we built this this tool not just to spit the information to the operator, but it also ingests all the raw data coming off the instrument; and we have a bunch of agents that watch that data for different conditions, and control the instruments.
It’s called R2CH4 as an homage to R2D2, who’s an astromech repair droid — and its primary job is not to save the universe, its primary job is just to make the X-Wing go.
I wouldn’t have caught that reference.
Well, CH4 is Methane sooooo… [makes the “ba-dum-tssssss” joke sound]
What do you do when you’re not at work – any hobbies? Matt, I heard about yours a little already: I know you’re a fire artist and you hang-glide?
Matt: I don’t hang-glide anymore, but yeah, I build weird Burner kinetic fire art. I’m making a fire Skee-Ball machine right now, where the balls are on fire. You get to wear big, fireproof kevlar gloves. I was going to bring it to Precompression, which is the pre-Burning Man party they do in SF, but the SF fire department nixed it.
Ari: I dabble in home automation. That’s kind of my tinkering hobby currently. I mean, I’ve had really good hobbies, but now my hobbies are basically my two children. But, you know… I used to be a DJ for a little while. I swear I used to have better hobbies — but I’ve really just been well-employed for like twelve years.
Julia: I spend most of my free time either outside, like hiking, or reading — real books with paper.
Ari: I thought that was illegal now?
Julia: It is here.
Just one last question for you.
Ari: 4-3-2-6! I’m glad you asked — it’s my favorite coordinate system.
Matt: 3-8-5-7 is way better, man.
Are you a geohipster? Why or why not?
Ari: Oh, absolutely. It’s interesting that all of us came to Kairos, not completely illiterate in the ways of GIS, but certainly not as well-steeped. And I was actually thinking about this on the way home: we have non-GIS operational data about what we do, but the core of what we do — everything is geo data. Like, there’s no non-geo data. And, what we’re trying to build is: taking a novel stream of data about the earth, and then running it through very, very modern software pipelines, to automate its processing, it’s production, all of that, in a way that requires understanding the bleeding edge of technology and blending that with GIS. And that’s what we spend all day doing.
Matt: I am geohipster because I make artisanal Geo data. And I’m opinionated about it. And I’m obnoxious. So, here a thing that I do, which is super geohipster: We produce a lot of stuff internally at the company, in WGS84 — which is not a projected coordinate system. It’s a geo-coordinate system — and I constantly complain about this. That we are producing GeoTIFFs in 4326, but we should be producing them in a projected coordinate system.
Julia: …And I want to tell you, we were doing all this way before it was cool.
Ari: One last thing — we use US-West 2 as our AWS data center, because it’s carbon-neutral (they run entirely on hydropower), so it fits in well with our overall mission.
The State Plane Coordinate System is comprised of 120+ geographic zones across the US. The system, developed in the 1930s by the U.S. Coast and Geodetic Survey, is a commonly used mapping standard for government agencies and those who work with them.
There’s a website that I’ve had bookmarked for as long as I can remember. It’s simply a list of State Plane zones and the US counties that fall within each. At the top of the page are state links that redirect further down on the site, but I rarely use those. I usually just cmd+f and search for the county I’m looking for. Even if I know the zone already, the site gives me a sense of security when I’m making a map that uses the US-based coordinate system – like the feeling one gets when going back to double check that the stove is off and the door is locked.
There are most certainly other ways to look up State Plane zones, but this one, hosted on a stranger’s personal website, is the one I like best. Maybe it’s the simplicity of the site, its Web 1.0 design, the fact that the person who made it picked tan for the background color. Maybe it’s the nostalgia of going back to something I’ve used time and time again, and always has what I want – like a well-loved t-shirt.
A while back, I went to the State Plane site only to find the site could no longer be reached. Russell Edward Taylor, III, experienced something similar, but instead of chalking it up as a mystery like I did, got in touch with the owner, Rick King, and asked about hosting the site on his own domain. Lucky for those of us who’ve relied on it as a useful reference, it continues to live on on Russell’s personal website. Russell also did some investigating and found nearly 400 links to the State Plane site from across the geospatial community, from universities to professionals to students. Inspired by his initiative, I decided to reach out to Russell, who put me in touch with Rick, to learn about the site’s story.
Q: Rick, thank you for creating the State Plane site. Could you tell us a bit about yourself, and why you created the site?
A: I am currently retired having worked in GIS and Land Surveying since the 1980s. I was a Professional Land Surveyor licensed in Utah with most of my “experience” being while working in Indianapolis, Indiana, and ending after a 4-year stint working as a GIS Analyst in Los Alamos, New Mexico, documenting some hazardous waste remediation on a material disposal area that was used at the time of the Manhattan Project. I also helped with the development of an Acequia GIS for the Taos Soil and Water Conservation District in Taos, New Mexico.
My initial work in GIS was to allocate mapping resources to provide the base layers for large regional geographic information systems being developed primarily by the various utility companies. In the pre-internet days this work was accomplished by telephone inquiry starting at a state geological office or somewhere to see if there was any existing mapping available. GIS has evolved since then, but, just wanted to throw that in to let people know that GIS was existing before the world wide web.
I created the site as a reference for myself to help me at work. In the course of my work I received hundreds of datasets most all of which came without metadata and without any identification of the coordinate system on which they were based. The website I created in basic HTML would give me starting points to make the coordinate system identification. At the time of its creation, there really wasn’t anything else online to fulfill the need. I wanted to reference both the NAD 27 and NAD 83 systems, and found those references listed in the state statutes when I could find them online. The UTM references and the MS Excel spreadsheet were added later.
The state plane coordinate system page was part of a multi-part GIS reference page titled “GIS Landbase Information and Data Links”, which provided weblinks to the same.
The awful tan color of the background was carefully chosen for providing less eye-strain.
I hosted the site for many years as my contribution to the internet.
Q: Russell found almost 400 links to the State Plane page on other websites. Did you realize the site was being used by so many others in the geospatial community?
A: I did. It was Comcast’s decision to withdraw hosting personal web pages which is why it went down.
Q: When did you create the site? Looking at it now, is there anything you would change?
A: I created the site in 1999, and most of its creation is covered in the metadata I created for the page. Actually, I was one of the first people to quit using the page, so changes would have to be made by someone else.
Q: What was your reaction when Russell reached out about hosting the site. Were you surprised at all?
A: I was hoping that someone would step up and host the page as there were some educational institutions using it as a reference. A big thanks to Russell for stepping forward.
Q: Now being retired from a long career in land surveying, what do you do with your spare time? Do you have any hobbies?
A: I spend a good deal of time day trading on the stock markets. The goal is to grow my retirement funds specifically so that I can afford to build a new house. Yep, that’s the goal!
Q: A geohipster is someone who works anywhere along the broad spectrum of geospatial data and applications. Usually they’re described as being on the outskirts of mainstream GIS, thinking outside of the box, and doing something interesting with maps. Would you call yourself a geohipster? Why or why not.
A: No, I just never got involved with the analytics of GIS to get that excited about it. But…
Q: Rick, thank you for your contributions to the geospatial community, and for helping bring well-documented GIS resources online throughout your career. Any words of wisdom you’d like to leave with our global readership?
A: The world has become so dynamic. Everything is changing. People and politics, the environment, business and trade, and world economies. GIS is the only science that is capable of accumulating all the data, visualizing the data, comprehending the data, and finally using the data to forecast future models that will benefit us all. Population management, food management, resource management will be extremely vital in the near future. There will be plenty of opportunities to resolve what most of us believe are foreseeable problems, especially having clean water and adequate food for everyone.
Russell Edward Taylor, III
Q: From your resume, I see that you’re a Senior GeoSpatial Analyst at CoreLogic. Could you tell us a bit about what you do there?
A: I’m part of a group that works on a suite of data products used by clients for location intelligence. It’s based on a standardized, nationwide parcel dataset derived from point and polygon data acquired in every data format, attribute layout, and projection under the sun. Taken together, our little team likely has more experience than anyone with the quirks of the many different ways parcel mapping is done. I’m on the more technical end these days, maintaining internal tools in Python, preparing custom data deliveries for clients, managing our metadata and documentation, plus a variety of internal process-improvement initiatives that have immersed me in the database world more than I ever imagined possible when I got into GIS in the late 90s.
Q: When did you realize the State Plane site was no longer live, and what inspired you to reach out to Rick?
A: It was in July 2015; a colleague brought it to my attention when they went looking for the state plane zone of a county they were working with. After I hurriedly cached a copy from the Internet Archive for use by my team and myself, it occured to me that there were probably others out there wrestling with similar data that would miss it too. I have a personal website, and since the State Plane site is just one simple page, I realized that it would be very easy for me to keep it available to the world. Over the years, I’ve benefited greatly from the community-mindedness of others, so it seemed like a good way to do my part.
Personally, I favor open software, data, and public licenses that make works more widely available for use, but I’m also aware that not everyone does. Rather than take the risk of running afoul of an unknown benefactor by re-hosting the site without permission, I decided to do it by the book. I thought it was especially important to do it that way for two reasons: first, it would be a full, verbatim copy, and not anything that might fall under fair use if I ever had to defend it; second, if I republished it without a notice at the original URL, those who had been using it might have a harder time finding their way to its new home. So, after gathering a bit of courage, I shot off a short message that happily found a friendly response.
Q: Have you received any notes from others who’ve found the state plane site on ret3.net?
A: I have, at a rate of a few each year. Most are simple thank yous from visitors glad to find it still alive somewhere. Most emails come from businesses domains, almost as many from .edu accounts. I’ve had a couple interesting ones that led to a little research about parts of the page I’d never used for myself, most memorably as to just what an ADSZONE is.
Q: Enlighten us?
A: Oddly, I received not one but two questions about this within a few months of each other in late 2016. As near as I can tell, ADSZONE stands for Automated Digitizing System Zone, named for the tool the Bureau of Land Management used to convert NAD 27 maps to NAD 83, along with other subsequent projects, and the regions used for that project. Now knowing more about Rick’s experience, the inclusion of this bit of information makes more sense! If you’re curious (or very, very bored, although there is some fine early 90s clipart to be seen therein) the manual is online here: https://archive.org/details/automateddigitiz00unit. I don’t believe this numbering system is used very widely anymore, although in the surveying business (the field of both of my interlocutors on this topic), encountering disused references is pretty common.
Q: When you’re not being a geospatial analyst, what do you like to do in your spare time? From your website I glean that beyond maps, you also like comics and bikes.
A: I got my start reading comics with my dad’s Silver Age DC collection, but fell out with constant reboots of the modern era, so these days I’m far more likely to pick up self-contained stories, or at least serials that aren’t under pressure to run forever. Of course, I’ve always had a weakness for maps in comics: the World of Kamandi, Krypton, Marvel’s New York City, Prison Island and other small-town memoir settings, even the dotted-line paths in Family Circus.
I’ve been a daily bike commuter for 8 years (and 110 pounds), following a 25-year hiatus from pedaling. I ride a modest 5 miles round trip on my commuter bike, plus weekend trailriding on my mountain bike and recently longer road bike events. Interestingly, all my bikes are folding models. Although it’s not closely related to my professional niche in geography, planning, land use, and transit issues have always fascinated me, more so since bike infrastructure became a rather personal concern!
I also enjoy Austin’s energetic music and craft brewing scenes, with friends in the former (go see Danger*Cakes, Bird Casino, and Oh Antonio & His Imaginary Friends!) and my neighborhood being taken over by the latter, which happens to combine well with cycling.
Q: Are you a geohipster? Why or why not?
A: That’s hard to say; most of my work is not what would come to mind for that label — it’s pretty traditional and desktop-oriented, working with shapefiles in proprietary software, focused on fundamentals of data integrity for the end user. GeoNormcore, perhaps. The GeoJSON, FOSS4G, webmapped world is something I encounter mostly at conferences and in occasional at-home dabblings. That said, I am planning a Dymaxion tattoo, so perhaps I have a bit of geohipster in me after all.
Q: Any final words of wisdom you’d like to leave with us?
A: Although I always have to remind myself of it when the opportunity arises, folks are far more willing to help and collaborate than you’d think. Muster your gumption, screw up your courage, steel your nerves and ask nicely. I know it works on me.
Tim Wallace is a Graphics Editor and geographer for The New York Times, where he makes visual stories with information gathered from from land, sky and space. He has a Ph.D. in Geography from the University of Wisconsin-Madison.
Q: How did you get into mapping?
A: I’ve always been into maps and geography. I grew up outside of Boston in a family that took one kind of vacation—road trips to go camping. We drove everywhere we could in the Northeast: Vermont, New Hampshire and Maine, of course, but also New Brunswick, Nova Scotia and even Newfoundland (my favorite). For me, as an elementary school kid and middle schooler, it was pretty spectacular seeing all those beautiful landscapes in person, as well as discovering how they all were connected thanks to the maps we collected along the way.
While my first job (at the age of 8) was in journalism (I was a paperboy for the Boston Globe, of course!), the realization that I could have a career in journalism came much later, after a few years as an aspiring maritime archaeologist. I’d gotten both my undergraduate and masters degrees in archaeology, but after realizing the thrill of diving on a wreck was an opportunity I’d only experience rarely, I found myself drawn to the kinds of storytelling and visual explanation that are crucial to the preservation of cultural heritage. I was already doing a lot of cartography as an archaeologist, but without a great deal of formal training, I felt like I was winging it more than I wanted to be. So I decided to go for a PhD in geography.
Q: The title of your thesis is “Cartographic Journalism: Situating Modern News Mapping in a History of Map-User Interaction”. It was published in 2016, but you’ve been at the New York Times since 2012… so you completed a PhD while working at the NYT? That sounds impossible – how did you manage to pull it off?
A: Oh, boy. Short answer: writing retreats and sticking to a strict schedule. Long answer: It wasn’t easy, and I didn’t do it alone. Once I’d started at The Times, many people asked me why I would bother finishing. And as time passed, doubt crept in that I was even capable of it. In fact, I don’t think I would have finished if I hadn’t had the support of my wife, Kelly, and family, who understood on a deeply personal level what finishing might mean to me. I don’t talk about it much (because really there’s no point), but I struggled with dyslexia and short term memory issues as a kid—so much that one teacher told my folks that I would never be able to go to college. So, if I’m being honest, a good percentage of my drive to finish was thanks to family support—and also the desire to stick it to those long-since-gone teachers and prove to myself that I’m every bit as capable as the next geographic nerdlinger. Take that, Mrs. Baldwin! Hahaaa!
Q: You started off as an intern for the New York Times, but now you work as a graphics editor. What’s that like? Can you walk us through a typical day?
A: One of the greatest things about my job is that when I wake up in the morning, I often have no clue what I’ll be working on that day. Breaking news, fresh assignments or successful pitches often turn any expectations of how a day (or even a week) might go, upside down. Having said that, there are a handful of things that I often do (even if I don’t know when I’ll be doing them). I make maps, solo or along with a handful of other geographers in the department, and those same geographers and I assist other colleagues with mapmaking. I work with satellite imagery quite a lot, and increasingly, various types of drone imagery. Sometimes that drone imagery comes from flights that I or my colleagues have piloted. Occasionally I find myself working alone, but our department, and the newsroom as a whole, is extremely collaborative. So it’s pretty rare that the work I do isn’t done in support of a team effort.
Q: You work with a wide range of data types, from satellite imagery to spatially referenced data, and not so spatially referenced data. Can you tell us about the tools that you use?
A: Our department has a handful of internally-built tools (some of which have been opened to the public, like ai2html!), but everyone works with their own little hodgepodge of tools that suit their pace and type of work. For short deadlines (sometimes only minutes), we keep it simple (often only using illustrator and/or photoshop); for enterprise stuff we often have time to get a little experimental and try new tools and techniques. Geospatial tools I use include GDAL (my bash profile is a mess with functions for common tasks, like cleaning up gross shapefiles or pansharpening Landsat imagery), Mapshaper (made by my colleague, Matthew Bloch!), Arc/Q GIS (am I allowed to list them interchangeably like that?), GeographicImager, MAPublisher—but I’ll dabble in ENVI or Pix4D if I have time! Because of our often-frantic work pace, our spatial database management is borderline atrocious though. So, please don’t ask me about that. 🙁
Q: How often do you get to experiment, try out a new tool or a different approach to a problem?
A: Every story is at least little different from any other, so some level of experimentation is a part of the job. Dedicated whacky experimentation time usually only happens when we know a story is coming that we want to cover very differently. But I work with a group of creative people who are always pushing to do better work with new and surprising techniques, so some days feel almost like I’m in a little R&D graphics lab.
A: The Tubbs fire was unique for several reasons, but chief among them was the unusual rate at which it moved down a hill and into a populated area. We felt pretty strongly that this needed to be explained visually to give our readers the best sense of what happened. Projects like this are big team efforts. Derek Watkins was reporting from California for the first part of the production of the graphic. Others of us back in New York were helping delineate the fire’s perimeter using the latest data from the state, images from the European Space Agency, Landsat and DigitalGlobe. We were also using the DigitalGlobe imagery to determine which buildings were destroyed. If we weren’t sure about a building and Derek had access, he would go take a look and we would update our map with what he found. The locations of deaths were mapped with old-fashioned reporting. The timeline was put together using VIIRS, MODIS and GOES-16 data and we tried our best not to imply any more precision than we had. You may notice the lines aren’t sharp, for example. Their gradient is meant to visually display the fuzziness of the precision of our timeline based on our amalgam of sources.
Q: Is it normal for news publications to employ top notch geographers, or is that something unique to the New York Times?
A: What it means to be a Geographer in a newsroom and what we do has changed over time, but we’ve always been around. Maps have appeared in newsprint for centuries and many reporters do geography all the time! The type of work we’re doing now though feels special, like we’ve hit an inflection point where institutions are leaning on Geographers not just for maps or square mile calculations, but also for their perspective on news events as they happen across cultures and landscapes.
Q: Many people I’ve talked to who make maps professionally often make maps in their spare time for fun. Do you have any fun mapping projects in the works?
A: I’ve made a habit of puttingmyself to sleep at night with satellite imagery instead of a long read. I sometimes tinker with ideas too, but I’ve found that it’s pretty important to step back a little from my work during certain hours so that I don’t burn out!
Q: You also run a website called Bostonography with Andy Woodruff. For those who might not know, what is Bostonography? How did it come about?
A: Andy approached me about it at NACIS in St. Petersburg in 2010. He’d just moved to Boston and I’d just left. So, with his fresh eyes and my perspective as a recent Bostonian, it made good sense to team up. And it has been a lot of fun pretending to be the modern day Kevin Lynches of Boston. I just wish we had more time for it!
Side note: Amy’s favorite on the site is Whoops: Dunkin’s are Closer, which is a correction of an earlier Bostonography map showing distances to the nearest Dunkin’ Donuts across Boston. The farthest place in Boston from a Dunkin’ Donuts appears to be a cemetery, which you point out is ironic, because there’s another great Bostography map showing distance to cemeteries.
Q: What do you do for fun? Any hobbies? Your website has a lovely photo of your writing coach, who looks like a lot of fun…
A: I really don’t think I could enjoy spending time with Kelly, my son and my dog, Lucy, any more than I do. We cherish the weekends when we can stretch out our walks in the park, build worlds out of train tracks, hit up the zoo or go for a swim. I love taking photos and experimenting with photographytoo. I bake and cook a lot. Oh, and I might make a map here or there for fun (like this housewarming gift for my parents).
Q: Are you a geohipster? Why or why not?
A: Why, sure! I’m a geographer living in Brooklyn, I make my own pickles and babka, and I collect old maps. I should at least be geohipster-adjacent with these qualifications, right?
Q: Any words of wisdom you’d like to leave with the geohipster community?
A: Be friendly, share your knowledge and try to get the whole picture before you criticize. We all work differently and have a lot to learn from one another.
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.
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.
Stephen Mather has been working in GIS, planning, and related fields since 1998, working for the last 7 years as the GIS Manager for Cleveland Metroparks. He has been interested in the application of computer vision to geospatial analyses since 2004, and has recently initiated the OpenDroneMap project — a project to bring together and extend a suite of open source computer vision software for use with UAS (drone) and street level images. He is also coauthor of the PostGIS Cookbook.
Q: How have you been enjoying the conference so far?
A: It’s been consistently good! There were sometimes two or three sessions that I wanted to be in at a time, so I had to figure out if I could clone myself.
Q: Clone yourself?
A: Yeah, well it would make it so much easier (well, probably the easier thing is to watch the video afterwards).
Q: Let me know if you figure out the cloning thing.
A: Oh, I’ll share it. It’ll be on Github.
Q: Awesome. Have you been to this conference before?
A: I went to variants on FOSS4G in DC, Denver, Portland, and Seoul.
Q: Wow, what was Seoul like?
A: That was FOSS4G Korea. It was awesome. The hospitality was amazing, the conference was really interesting. It’s a beautiful city, and it was lots of fun.
Q: Do you speak Korean?
A: Not adequately, no. (*laughs*). Not at all.
Q: You presented at this year’s conference. How did it go?
A: It was really fun. It was similar to a presentation I gave at North Carolina GIS a couple of weeks ago. The slides were already there, but it never ends up being the same presentation. OpenDroneMap is what I presented on, which started off as a GeoHipster joke at first, but then started to become a thing! People are excited about it, and are trying it out with their drones.
Amy and Steve at FOSS4GNA 2015
Q: Who started the joke?
A: Well, there was the GeoHipster artisanal vertices, and at the time I was thinking about computer vision and drones and where all that’s going, and the absence of an open source project that addresses that. When I made my prediction about 2014, I said it would be all about the artisanal pixel. We’d go from these global satellite images to these handcrafted satellite images effectively. Then I starting thinking, actually, that’s not a bad idea. The best way to predict the future is to stake a claim in it and make it happen.
Q: I definitely want to pick your brain about that later on in the interview. But before we get there, I wanted to ask you how you got started in the geospatial world.
A: I came from the biology side of things. As an undergrad I actually took a lot of music classes, and a lot of biology classes. At the time, a lot of biologists weren’t really thinking spatially. Everything was about static statistics, which assumes some normality that doesn’t really exist. There were people starting to pull on that thread, but it was the minority. My interest in GIS and the geospatial was applying it to understanding biology and ecology better, and then I never really got out of that rabbit hole.
Q: But you haven’t really left music either. You make custom guitars.
A: Very, very slowly. I’ve been making them for 12 or 13 years. I’m on guitar #2.
Q: That’s a really cool hobby.
A: It’s one of those things that seems like it should be harder than it really is. A lot of people think, “Oh, I couldn’t do that”, but actually it’s not that hard of a hobby, and for a woodworking hobby, it doesn’t require many tools. If you want to become a furniture maker, you need to invest a lot in tools just to start. The total cost for guitar-making is much smaller with a minimum viable set of tools, which is kind of cool. In that way, it’s kind of like open source. The barrier to entry for open source is just a laptop, which you may already have.
Q: Totally. Let’s go back to drones for a minute. For those who might not be familiar with it, what is OpenDroneMap?
A: OpenDroneMap is an open source project for taking unreferenced images and turning them into geographic data. Maybe you have a balloon, kite, or drone, and you’ve taken some overlapping photos of an area, and you want to turn that into an orthophoto as a TIFF or PNG or a point cloud. It’s basically an extension of the photogrammetric techniques. Back in the day, you’d fly with a nice camera that was well parameterized so that you could correct for all of the optical distortion. You’d have a plane that was flying a known route with inertial navigation and GPS to help you know exactly where the plane is at any given point in time, and then you construct three-dimensional data from that, with contours and orthophotos. If you extend that concept, and instead of having two overlaps with lots of knowledge about your position, you have three overlaps, then you can write an equation that back-calculates where all of your camera positions are. In the process of doing that, you generate a point cloud of all of the features that match, which is something that you can derive other products from. You could create a mesh from that point cloud, then paint those photos back onto the mesh. Now you’ve got the geospatial information you need, and it can be turned into an orthophoto. When I first proposed the project, I thought, well we could license something like this, or we could start an open source project. I had a hunch there was enough existing computer vision code out there to get it 50, 60, or even 70% of the way there, just with the existing code. Fortunately my hunch was right. This leverages years of computer vision stuff done by people all over the world.
Q: It sounds like it was worthwhile to see what other people were doing, and build off of it.
A: Yeah, the stuff that people had been doing was absolutely brilliant, and allowed me to move whole hog and jump into the parts I was interested in.
Q: When I was in college I took some courses in remote sensing and did work with Synthetic Aperture Radar. I’m a little familiar with working with imagery. I’m guessing that working with imagery from drones is pretty different from working with aerial and satellite imagery. What are some of the differences you noticed in working with drone imagery versus something from an airplane or satellite?
A: A plane or a satellite gives you a nice synoptic view. There’s a usefulness, not in the specificity, but in the synopsis. If you think of the world as you view it from the ground, you can observe and make sense of the world; it’s what we’re most familiar with. There’s a wide gap between what’s happening in the plane or the satellite and the first-person view. Drones, balloons and kites fill that gap. Drones fill it particularly well because they can fill large areas. That’s what brought me into working with them altogether.
Q: Speaking of working, you work for the government. Could you tell us more about that?
A: I work for Cleveland Metroparks. We manage about 23,000 acres, which includes forests, wetlands, open areas for people to picnic, a zoo, lakefront parks, and really a whole range of interesting cultural and natural resources. We provide access for passive uses such as picnicking and hiking, and active uses such as events that draw people into those spaces. It’s a really cool park system with a lot of energy and a great history, as well as an amazing staff and a good vision for where we are now and where we’re going.
Q: How long have you worked there?
A: Seven years.
Q: I did some LinkedIn stalking, and I saw that you are a manager there. I’m sure that GIS manager can mean lots of different things depending on whether you’re with the government, a private company, or what industry you’re in. What are the things you think are common descriptors of GIS managers?
A: I’m relatively hands on. I’ll hack a code, I’ll work on data when I get the opportunity, but I also make sure to give a lot of freedom to the people that work with me, because they’re brilliant, and I don’t have to worry much.
Q: You sound like a great manager!
A: I’ve got great employees! There’s coordination and advocating for resources, ensuring that my employees have what they need. There’s also the aspect of ensuring that folks within the organization, as well as outside of the organization, understand what we do, so that they can value and take advantage of it. In addition to giving the degrees of freedom that people need in order to grow, we make sure they have educational opportunities and that they have challenges. There’s a lot of autonomy, which again links back to the open source community, where there’s a lot of autonomy.
Q: You’ve written a book on PostGIS. Can you tell us about the book and how it came about?
A: A couple years ago a publishing company discovered my blog and asked if I’d write an outline on PostGIS. I wrote them the outline, and they said “This is great, when can you start?” And I said, “I can’t, my daughter’s due in a few months, and there’s no way I can write a book.” They said, “Well, you could get a co-author”, and I said, “I can’t even write half a book!” Their response was “Well, you could do 60/40!”, and I said “Alright, but you’ve got to find the co-author”. They found Paolo Corti, who’s an excellent writer and knows his PostGIS stuff, and also knows the middleware level of that, and how to get it out to the web. That adds a nice element. Paolo and I started on that and we realized between the two of us, we weren’t going to get it all done. We found Bborie at the Boston code sprint, and Tom works with me and wrote a chapter. [Interviewer note: Bborie, Tom, and Paolo co-authored the book with Stephen.]
Q: Thanks so much! It’s been a lot of fun talking with you. I have one last question for you. Do you consider yourself a geohipster?
A: I’m a geohipster, absolutely! I’m the guy who predicted artisanal pixels. I don’t ride a fixie, but I do ride an e-bike. When I’m in sound health, I bicycle from 2-3 days a week, so I think I qualify.
Q: I think so, too.
Postscript: Steve gave me a signed copy of his book!
Post Postscript: Steve and I geeked out for a while about Synthetic Aperture Radar. We’ll spare you the nitty gritty details, but tweet at us if you ever want to talk SAR. We’ll talk your ear off. :)