All posts by Atanas Entchev

Maps and mappers of the 2016 calendar: Andrew Zolnai

In our series “Maps and mappers of the 2016 calendar” we will present throughout 2016 the mapmakers who submitted their creations for inclusion in the 2016 GeoHipster calendar.


Andrew Zolnai

Q: Tell us about yourself.

A: I’m a geologist who turned to computer mapping 30 years ago and GIS 20 yrs ago – high school Latin helped me transition to coding just short of programming – and I now started my third business and assisted two others. I’m taking a ‘business process first’ approach, using mind mapping as a ‘talking point’ to help firms help themselves, which will determine workflows in resources planning that may invoke web maps. My Volunteered Geographic Information also helps individuals and academics put themselves on the map.

Q: Tell us the story behind your map (what inspired you to make it, what did you learn while making it, or any other aspects of the map or its creation you would like people to know).

A: Ken Field’s hexagon maps featured on the BBC during UK elections this spring inspired me to do the same in the US Gulf of Mexico: 50K oil wells taxed, so binning the data points allowed to show progressively more detail at large scales as you zoom in. It clearly shows for example the march of wells further offshore with time, in a way that speaks to stakeholders and public as well as engineers and mappers.

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

A: Esri ArcGIS for Desktop Standard and Model Builder, scripts adapted from Esri’s Ken Field for US Gulf of Mexico wells, posted on ArcGIS Online.

'Hexagon binning, US Gulf of Mexico oilwells' by Andrew Zolnai
‘Hexagon binning, US Gulf of Mexico oilwells’ by Andrew Zolnai

Maps and mappers of the 2016 calendar: Terence Stigers

In our series “Maps and mappers of the 2016 calendar” we will present throughout 2016 the mapmakers who submitted their creations for inclusion in the 2016 GeoHipster calendar.


Terence Stigers

Q: Tell us about yourself.

A: I never formally studied GIS so I’m tempted to say I ‘fell into’ it, but that would imply there was something accidental about the process. I am a historian and archaeologist, and whilst studying these disciplines I heard about this new-fangled thing called GIS that ostensibly used computers to model and study spatial relationships. Immediately recognizing how useful such a thing could be for archaeology, I happily invaded the geosciences department of the university I was attending. At the time the only remotely related offering they had was a class titled ‘Computer Mapping’. I enrolled and ended up walking away with a copy of MapInfo 5.0 (still got it, too). Having exhausted the university’s offerings, I did some digging and learned that Esri (at the time, at least) offered substantial discounts to enrolled students. A series of phone calls and emails later had secured me a shiny new copy of ArcView 3.2a for a tenth of the retail price. I spent the summer teaching myself how to use it, and the rest is GIS (with a little bit of history and archaeology thrown in for good measure). So I didn’t actually fall into GIS but rather actively and doggedly hunted it down. But GIS isn’t my job. I do it for fun.

Q: Tell us the story behind your map (what inspired you to make it, what did you learn while making it, or any other aspects of the map or its creation you would like people to know).

A: I made this map to explore some techniques I intend to employ for an upcoming project. My friend Drew asked me to produce some maps for a new book he’s writing, so I decided to get a jump on things. It’s an academic book (but not a textbook), so I’ll be dealing with substantial size constraints and will be limited to greyscale. So the trick is figuring out how to convey enough information with the least amount of clutter. Whenever possible I try to produce maps devoid of legends. I feel every entry on a legend represents a failure on the part of the cartographer. An ideal map should need only a scalebar, a north arrow and maybe some labels. I try my best to attain this ideal. I usually turn to old maps for inspiration for these endeavors, and on this map you can see the results in the larger rivers and bodies of water. I also used Tanaka-style illuminated contours for this map, a technique I have long been fond of but only recently became able to leverage (I first encountered the idea of Tanaka contours using GIS software in an ArcUser magazine about a decade ago. It was a spirited effort, but was more a terraced DEM than anything else). It is a very effective tool for conveying a lot of elevation information at a glance. And doing so without a color ramp or the clutter of hillshading.

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

A: The only tool I needed for this map was QGIS (2.8.1, I think). The hydro symbology I achieved through the simple expedient of a series of semi-transparent layered negative buffers with varying dash arrays for outline symbology. I did the illuminated contours using a technique developed by Anita Graser (QGIS superstar extraordinaire) that she obligingly outlined in a post on her blog ( I had to tweak it just a little bit (mentioned in the comments, if you’re interested). All the data used came from MassGIS, OpenStreetMap, and myself. The town depicted is Greenfield, Massachusetts, and is the town in which I reside. Over the course of some years I have amassed, manipulated, and refined a sizeable amount of data pertaining to this town. Because of this, I have an intimate knowledge of these datasets, so they are my go-to datasets whenever I experiment with cartographic techniques (unless I need something they can’t provide. A volcano, for instance).

'Greenfield, Massachusetts' by Terence Stigers
‘Greenfield, Massachusetts’ by Terence Stigers

Link to full-size map

Maps and mappers of the 2016 calendar: Nathan Saylor

In our series “Maps and mappers of the 2016 calendar” we will present throughout 2016 the mapmakers who submitted their creations for inclusion in the 2016 GeoHipster calendar.


Nathan Saylor

Q: Tell us about yourself.

A: I’m the GIS coordinator for Hardin County, Ohio, where I do a variety of map projects to support and promote various county entities. I really enjoy my position there as I’m a one-person shop and there is ample opportunity to learn and experiment with my craft.

I am also the owner of Saylor Mapping. This was started to answer the many requests coming to the county GIS for cemetery mapping services that the county felt was beyond its reasonable scope to handle. Saylor Mapping is also breaking into municipal utilities as well.

I am also very involved with #GISTribe, which has a scheduled meet every Wednesday at 3pm ET on Twitter (though we’re active all the time), as well as the archive and blog.

Personally, my wife Marti and I have been married for nearly 18 years and have six clever kids.

Q: Tell us the story behind your map (what inspired you to make it, what did you learn while making it, or any other aspects of the map or its creation you would like people to know).

A: The deadline for the Ohio GIS Conference map competition was looming, so being in Buckeye country, I pondered what the map might look like if Michigan wasn’t there. I had never really thought about it, but looking at it, I considered what the impact of its sudden absence might be and within about 30 minutes came up with some economic reasons why this might be proposed by the fictitious Ohio Consortium for Greater Lakes.

Of course this is born out of the well-known rivalry between Ohio State and Michigan, and this was totally a play at the judges. While I had a lot of humored responses and requests for copies (download available here), sadly Ohio missed the opportunity to formally recognize the genius in their midst (I say with tongue firmly in cheek).

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

A: The data was from Natural Earth, and I used ArcGIS Desktop. If you fancy yourself a fontophile and an anglophile, you’ll have noticed the font used for the lakes is Blackadder which was named for a British comedy alluding to the jest in which this map was made.

Go Bucks!

'Great Lake Expansion Proposal' by Nathan Saylor
‘Great Lake Expansion Proposal’ by Nathan Saylor

Maps and mappers of the 2016 calendar: Kenneth Field

In our series “Maps and mappers of the 2016 calendar” we will present throughout 2016 the mapmakers who submitted their creations for inclusion in the 2016 GeoHipster calendar.


Kenneth Field

Q: Tell us about yourself.

A: I tend to call myself a professional cartonerd having never had a job with the word ‘cartographer’ in it. I have a Bachelors in cartography and PhD in GIS and spent 20 years in academia the UK. I was Course Director for GIS programmes at Kingston University in London and did all the usual academic stuff of research, teaching, supervising students, publishing etc. I’ve been privileged to have won a few awards for my maps, writings about maps and interior design (kitchen tiles!). I recently ended a 9-year stint as Editor of The Cartographic Journal and I’m currently Chair of the ICA Map Design Commission. I also co-founded The Journal of Maps, and am on the advisory board for the International Journal of Cartography.

I got totally frustrated by the admin-heavy bureaucratic nonsense of University life and moved to the dArc Side in 2011 to work with Esri to support high quality cartography and help develop the next generation of tools to support more intuitive, better map-making. That involved moving from the UK to California which is a switch I can heartily recommend. I’ve been called a ‘cartographer in residence’ though that implies some sort of temporary job which I hope isn’t the case. It’s a terrific place to work and I have so much freedom to experiment and push the boundaries of what’s possible in cartography.

I’m an advocate for high quality cartography and deliver keynotes, workshops, training and research support internationally and on the conference circuit. I blog about the good, the bad and the ugly under various guises (, and, tweet far too much (@kennethfield) and sometimes I make maps ( I’m currently writing a book on cartography with Damien Saunder which we hope will be out by the end of the year– the more I publicize that, the more I am committed to getting it finished! More than anything I’m passionate about encouraging and helping others make better maps through identifying and sharing best practices (and explaining cartofails).

I can also be found on a snowboard, in a pair of hiking boots, behind a drum kit, or supporting my once great football team Nottingham Forest.

Q: Tell us the story behind your map (what inspired you to make it, what did you learn while making it, or any other aspects of the map or its creation you would like people to know).

A: I tend to make thematic maps. I’ve always been skeptical about 3D thematic cartography and often struggle to find a compelling reason to switch from a planimetric map. The key, for me, is to use that third z dimension for something really useful and not just for the sake of making a glitzy map. As technology has improved to overcome many of the failings of static 3D cartography (fixed point of view, occlusions, labelling, etc.) I figured it was time to experiment. The 2015 General Election in the United Kingdom gave me the excuse I needed. It’s an online map, called Political Causeway, which you can view here (use Firefox or Chrome).

The map shows the results of the UK election in 3D on an interactive virtual globe and positions it as a new development of the tradition of using cartograms to represent election results.
The map shows the results of the UK election in 3D on an interactive virtual globe and positions it as a new development of the tradition of using cartograms to represent election results.

The challenge of trying to display results for 650 irregularly shaped and sized constituencies in the UK has spawned many different outcomes. Maps that show geographical constituency boundaries face the challenge of trying to accommodate distortions arising from the simultaneous display of visually incomparable areas. People are disproportionately distributed across space, and while constituencies attempt to iron this out for voting it creates a cartographic problem. After Danny Dorling’s innovative work on the development of cartograms for elections, we’re seeing increased use, particularly of hexagons, for political cartography. Of course, using hexagons as a data-binning technique can be traced back to the mid-1800s, but they are the very essence of carto-hipsterism. Equal-area and tessellated hexagons provide a good visual structure that also allows a reasonable amount of adjacency topology to be incorporated. They are abstract but ultimately a good visual way to display election results.

And why 3D? Partly the technical challenge, but also the structure of the voting meant I could use separate layers on the map to encode different aspects of the vote — with winners sitting on top and other political parties being represented in a second-place layer, third-place layer and so on.

For the 2015 UK election, virtually every media organisation used some sort of hexagonal cartogram (I wrote a blog on it here). As a fan of cartograms I also wanted to use hexagons, but I also wanted a challenge: to develop a three-dimensional hexagonal cartogram on a spherical virtual globe… and make it make sense. The map was inspired by a picture of David Cameron visiting the Giant’s Causeway in Northern Ireland taken in 2013. Hexagonal mapping and political photo-opportunities collided and my map idea was born. The map went on to win the Google Award for UK election mapping at the 2015 British Cartographic Society Annual Symposium.

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

A: The map was designed and produced as part of my work at Esri. I always attempt to challenge conventional thinking while building maps that are heavily informed by cartographic concept and theory. Sometimes this requires us to think outside the box, break rules, and bring new ideas to the table. It’s an exciting area to be involved with — marrying creativity with new technology to create innovative and interesting cartographic products.

In two-dimensional space the creation of equal area tessellated hexagons is relatively simple. Creating hexagons that curve across a surface is more complicated due to the geometry involved. The initial challenge was to build a set of hexagonal regions that partition the Earth’s surface. This was achieved computationally by creating an icosahedral discrete global grid. A number of grids of different resolutions were built and used in different ways in the final map. I used Kevin Sahr’s excellent DGGRID program to generate the grids — the key being that to wrap a hexagonal mesh around the globe the overall mesh has to include occasional pentagons else the tessellation wouldn’t work. Think of a football (a.k.a. soccer ball).

Once general grids had been developed, they were further processed to build a grid of 650 tessellating hexagons covering the UK. The Election results were manually collated during the live television coverage and entered into a spreadsheet, then processed into formats to support the creation of different layers in the final map. ArcGIS Pro was used to build a layer of three-dimensional extruded hexagonal polygons for each of four layers representing the winners, runners-up, third place, and also-rans (others). I’m calling them hexstones. Each hexstone in each layer was extruded proportionally to the candidate’s number of votes giving a causeway-like 3D surface and volumetric blocks. The base heights for each layer were modified so each layer sits relative to the layer beneath to build up the final three-dimensional political causeway. The model ultimately looks like a way of viewing the stratification of the election results a little like we might cut away layers of geological structure to see beneath. I liked the way this supports the causeway metaphor beyond simply the hexagonal shapes.

One of the limitations of any three-dimensional map of prisms (of whatever shape) is the inability to look ‘inside’. This is overcome through interactivity in the final map, but I also created a capstone for each constituency that shows the share of vote for the same four layers of results but in a single layer. This provides a way of seeing the political pattern of voting across all candidates across the top of the hexstones. It also allows the map to be viewed from above and reveal more than just the winners. At least — that’s the idea.

A range of supporting datasets (a custom 2D base map of hexagonal patterns, 3D leader lines, 3D labels, a 3D legend and pop-ups) were produced to support the final map, so it becomes something to explore rather than just look at and expect everything to magically happen for you. Interaction in a 3D environment is absolutely critical.

The map was published from ArcGIS Pro to Portal for ArcGIS into a 3D Web Scene which takes advantage of the 3D capabilities of WebGL browsers. The map must therefore be viewed in either Google Chrome or Firefox. The published web scene layers were configured to build the final map. The icosahedral global grid data was used to create a custom hexagonal basemap of different resolutions to create an abstract world map. Using a standard map of real global geography would not have suited the abstract 3D cartogram. A little transparency allows an imagery layer to bleed through, giving just a hint of a real world. The UK is outlined in hexagons of the same grid used for the 3D symbols. This illustrates the bloated England 3D cartogram compared to the fewer constituencies in Scotland and Northern Ireland. It provides an explicit comparison of the size and shape of the cartogram compared to the hexagonal representation of the real geography of the UK.

The 3D hexstone and capstone layers can be turned on and off in the legend. This supports the viewing of not only the winners, but the landscape of the runners-up, third place and the also rans. Party colours across the map give a recognisable link to the political affiliations. The undulating nature of the hexstones shows total voter turnout across the map… a small but subtle illustration of where the electorate were motivated to vote to a greater or lesser extent.

A layer of labels can be added to the map. These are scale-dependent so as you zoom in, pan and rotate the globe they update to give a reasonable amount of labelling in the immediate view atop the causeway. Simply adding all labels at once would swamp the map. More are revealed as you zoom in, and vertical leader lines anchor the labels to each constituency hexstone/capstone, and pop-ups can be revealed by clicking the label. This gives detailed results for each constituency, and reveals the full statistical makeup of the results.

A legend is viewable, again built from 3D hexstones that shows the party affiliated colours (to aid map interpretation), this time proportionally scaled in height by the total number of constituencies each party gained. Legend labels can be queried to get further details of the map and the overall results.

The map is fully interactive so you can zoom, pan and rotate. This gives the map user an ability to zoom across the landscape and position the view camera to any desired location and angle. This partly overcomes the limitation of a static 3D map that some features are inevitably occluded and foreshortened. Some pre-fixed positions are available to provide quick navigation. Of course, foreshortening does occur because it’s draped across a virtual globe with a curved surface. I’d usually use an isometric projection, but given each hexstone is broadly the same height (scaled by voter turnout) the need to visually assess the height of a hexstone and compare to another isn’t a crucial cognitive task. In addition, because the UK is relatively small, the curvature of Earth has a minimal impact.

This map exhibits some degree of technical and conceptual innovation. It has certainly pushed our ability to develop 3D products that support ease of use, clarity and interpretation, and it pushes election mapping and the use of hexagonal cartograms as a way of representing and reporting results. It was an hex-periment certainly, and I’m calling it helecxagon mapping.

'Political Causeway' by Kenneth Field
‘Political Causeway’ by Kenneth Field

Maps and mappers of the 2016 calendar: Jacqueline Kovarik

In our series “Maps and mappers of the 2016 calendar” we will present throughout 2016 the mapmakers who submitted their creations for inclusion in the 2016 GeoHipster calendar.


Jacqueline Kovarik

Q: Tell us about yourself.

A: I currently work as a GIS Developer at the Minnesota Department of Natural Resources (DNR), creating interactive web maps and data collection apps that assist with natural resource management. My BA in Environmental Studies and MS in Geographic Information Science are put to good use every day in a job that I truly enjoy.

Q: Tell us the story behind your map (what inspired you to make it, what did you learn while making it, or any other aspects of the map or its creation you would like people to know).

A: This past year I had the opportunity to work with several amazing bee experts at the DNR, looking for an efficient way to collect data on native bees in Minnesota. There has been a shocking decline in bee population across the country, which prompted the DNR to research native bees and their habitat. After creating a data collection app for our bee researchers, we spent a day testing it in the field where I was amazed to learn there are over 400 native bee species in our state. Many of these species gather pollen from plants in only one plant family (known as “specialist” bees), but there has been little research completed on their habitat characteristics or range.

Through this data collection application development process I was inspired to investigate a few of Minnesota’s specialist bees, and wanted to create a map that would draw attention to the diversity of bees in our state while bringing awareness to bee population decline. I also wanted to highlight the need for increased data and analysis, which is an integral component of bee population preservation.

Over the past few years I’ve created a handful of watercolor maps based on personal areas of curiosity, including illegal animal trade, UFO sightings, modern day pirate attacks, etc. I have a passion for painting as well as map making, so it was only natural to combine my two interests. It’s been a great way to maintain my cartographic skills which I find little time for now as a developer.

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

A: Data collected from the mobile app I created was compiled along with plant specimen data from the Minnesota DNR and specialist bee location data from the University of Minnesota’s Bee Lab. After mining and cleaning the datasets, I brought them into ArcGIS to identify areas of range overlap between 8 specialist bees and their 6 native host plants, and then used a hexagon tessellation tool to create generalized overlap zones. A plotted map of the state was transferred to watercolor paper using a graphite transfer method, then hand-painted with watercolors. Bee and plant species were hand-painted at an enlarged scale to show the unique differences in appearance.

'Planting for Pollinators' by Jacqueline Kovarik
‘Planting for Pollinators’ by Jacqueline Kovarik

Maps and mappers of the 2016 calendar: Kate Staley

In our series “Maps and mappers of the 2016 calendar” we will present throughout 2016 the mapmakers who submitted their creations for inclusion in the 2016 GeoHipster calendar.


Kate Staley

Q: Tell us about yourself.

A: My name is Kate Staley and I am a GIS Manager for the State of Utah School and Institutional Trust Lands Administration (SITLA). I graduated from the University of Utah in 2006 with a BS in Geography and a certificate in GIS. After graduating I started working with SITLA as an intern and recently became GIS manager this year.

Q: Tell us the story behind your map (what inspired you to make it, what did you learn while making it, or any other aspects of the map or its creation you would like people to know).

A: SITLA currently manages approximately 4.5 million acres of land for the benefit of the public school children. At the time of Utah statehood, congress awarded Utah with sections 2, 16, 32 & 36 to help generate money to place in a fund for the public school children and other beneficiaries. Money is generated through leasing, sales, development and exchanges of land parcels.

I thought it would be interesting to create a map showing the percent change in the total amount of annual School Trust Land distribution by school districts between the 2003-2016 school years. I wanted to see which school districts saw the greatest change in the amount of funds they received from SITLA.

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

A: At first this map was going to be a simple choropleth map to show the variations between school districts. But after doing some research I discovered a tool created by Jacob Wasilkowski/Esri St. Louis & Jie Cheng/UMASS Medical School – Copyright(c) 2014 Jacob Wasilkowski and Jie Cheng (inspired by Stewart, James and Kennelly, Patrick J “Illuminated Choropleth Maps”). This tool is known as the choropleth hillshade tool ( It enables maps to have 3 dimensions and makes your map look pretty cool. The tool is very simple to use and is available on github.

'The State of Utah Trust Lands Administration School Fund Distribution' by Kate Staley
‘The State of Utah Trust Lands Administration School Fund Distribution’ by Kate Staley

Maps and mappers of the 2016 calendar: Chandler Sterling

In our series “Maps and mappers of the 2016 calendar” we will present throughout 2016 the mapmakers who submitted their creations for inclusion in the 2016 GeoHipster calendar.


Chandler Sterling

Q: Tell us about yourself.

A: I work as a GIS Analyst for the City of Pasadena in Southern California. I really enjoy my role at the city as I get to work with each of the city’s departments which allows me to be involved in a myriad of projects and exposes me to many aspects of local government. I have a bachelor’s degree in Geography and Political Science from the University of Wisconsin.

I also serve as Treasurer on the board of Guerrilla Cartography ( which works to produce crowd-sourced thematic atlases. Twice a month I help run Los Angeles’s Maptime chapter, and have developed it into a local resource for both individuals and organizations throughout Los Angeles County.

I play guitar and piano in a band called Little Bones ( We released our first three-song EP in January and will have more music out this year, so follow us on social media if you like what you hear.

Q: Tell us the story behind your map (what inspired you to make it, what did you learn while making it, or any other aspects of the map or its creation you would like people to know).

A: The map I submitted is a joke. It’s a static map in two ways — the area of earth’s continents are filled in with a static texture, and it is static in the sense that it is not interactive. I thought this brand of irony would be fitting for a geohipster calendar.

The idea came to me as I was exploring a recent update to Mapbox Studio back in 2015. I noticed other maps created in MS with interesting textures and used this idea to learn how to use textures in the application.

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

A: The process was pretty simple: I used Mapbox Studio and OSM linework for the continents (to be honest I can’t remember if it was OSM or Natural Earth) and then searched for a high-resolution image of static. The challenge was finding an image that repeated nicely and did not pixelate too much. The result was a pretty basic map, and since geohipsters are certainly not basic, it makes sense that it was not included in the final cut of the calendar.

'Static Map' by Chandler Sterling
‘Static Map’ by Chandler Sterling

John Reiser: “The best work often occurs once you move outside of your comfort zone”

John Reiser
John Reiser
John Reiser is a Business Intelligence Analyst at Rowan University. He previously worked in state government and in a private planning firm. John is active in several professional organizations and also serves as a consultant on GIS, cartography, and data analysis projects. John lives in New Jersey.

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

A: I am a business intelligence analyst at Rowan University. I work primarily with University Advancement, dealing with fundraising recordkeeping and prospect research. We use technology to better connect with and support our alumni, as well as help find individuals who have both the capacity and the inclination to give philanthropically to Rowan. I also consult and work on projects in my spare time.

Q: You hold a graduate degree in urban planning. What attracted you to GIS?

A: The first time I can recall really getting excited about GIS was during my undergraduate program in Geography. The program at the time focused on raster-based analysis and did very little with vector data. This was 2004 and there was no easy access to large datasets like county-wide parcels. Thankfully, I was able to get copies of Burlington and Gloucester Counties’ parcel data, driving to their respective offices and picking up CDs, merging the data together and then using it to project ridership potential for a planned light rail in Gloucester County, comparing it to the recently-opened RiverLine in Burlington County. I continued research into access to transportation while pursuing my masters at Rutgers. Even though I initially wanted to pursue physical and transportation planning, I would get involved with projects that required GIS, and continued to build my knowledge on the software and myriad types of data available.

Q: Do you miss planning? How much of what you learned in planning school do you apply in the job you hold today?

A: I do miss working as a planner and I miss working with GIS on a regular basis, but I make up for it by working on side projects. My current project is NJ Parcels, an easy-to-use statewide listing of property assessment and sales information for New Jersey. I get to wear many hats as I work on the site, from system administrator, database administrator, software developer, UI/UX designer, and project manager. So far, I feel like I am successful in juggling the different roles and responsibilities to keep the site running smoothly. Over 2015, NJ Parcels served up 9.7 million pageviews to approximately 3 million users. I also develop and manage Florida Parcels, which is an attempt to do the same for the Sunshine State.

I do want to use the data I’ve collected to build the site for planning projects in New Jersey. I have assisted NJ Future to overcome difficulties matching the spatial data to the assessment records, namely where there are multiple lots but only one assessment record that contains the additional lots in a free-form text field. I am currently working on a project looking at distributed ownership in New Jersey — people who purchase property a distance from their listed owner address. This can help understand a variety of planning issues, from absentee landlords, transitional neighborhoods, market speculation, and the effects of out-of-state investment in places like the Jersey Shore. I am planning on releasing my findings in the spring of this year.

Two things I learned from planning school still weigh heavily in my mind: the need to build consensus, and having patience. Projects, both software development and large redevelopments plans, benefit greatly from consensus-building efforts. That extra work at the beginning trying to get buy-in from stakeholders and from the community might be seen as side friction, but it ultimately makes the project go smoothly. Patience is also critical. It takes patience to build a plan and see it through fruition. Not everything can get solved in a single meeting or a code sprint, and that’s okay.

Q: You have experienced GIS in state government, in academia, and in private consulting. Which environment is the most interesting? The most challenging?

A: State government can be frustrating because of the nature of the business. Interesting projects can spring up and die just as quickly as the whims of the politicians in charge change. I was told on occasion to simply stop working on a project because it was no longer supported by the Governor’s Office. Private consulting can be incredibly rewarding, but it has its own difficulties. The profit-driven nature of the private world shapes the outcome and the timeframe. Sometimes you just need to produce, even if it’s not the product you originally wanted to produce.

Academia allows for greater flexibility in exploring a project. Some truly amazing work has originated within academia. And if you’re fortunate to work with students, you’ll be constantly amazed what bright, passionate young minds can produce. However, the nature of the academic world can also be far more difficult to navigate than government or the private sector. Colleagues that block or stifle your work can do so simply because they can. Performance metrics are often ignored, and I have been amazed at the amount of “thinking with the gut” that is performed in higher ed. Unlike government, you’re not keeping your fingers crossed that the next election things will be better, instead you are stuck playing actuary and guessing if it is worth waiting around for retirements to occur. Academia can be an amazing place to work and be a contributor to some awesome projects, but it can also be immensely frustrating as Sayre’s law will demonstrate itself time and time again if you do not have the right people involved.

Q: You are equally well versed in Esri technology and in open source geospatial technology. Is mixing and matching geotools a necessity, a challenge, or a luxury?

A: To me, finding the right tool for the job is both a challenge and a necessity. I’ve seen fanatics on both sides — commercial and free software — produce projects that don’t meet their full potential because they’ve married themselves to a single software platform. Taking a step back and evaluating the options is important. Just because something happens to be your current favorite doesn’t necessarily make it the best choice for the task at hand. The best work often occurs once you move outside of your comfort zone.

Q: What are you working on now, and what technologies do you use?

A: At work I write SQL for Oracle on a daily basis and I use PostgreSQL for my side projects. It is amazing where the differences and similarities lie in the two DBMSs. I’m grateful that the one I find myself less frustrated with happens to be the free one.

I primarily use Python as my programming language of choice, but I have been looking into using Node.JS again after about two years of not using it to build an API to NJ Parcels. I also need to brush up on R and use that in my projects more often. I also use Tableau both at work and in my other projects. It’s a great tool for quick visualizations of complex data.

Q: Bike, beard, beer — you are in firm control of the ultimate hipster triad. Do people call you a hipster, and how do you feel about it if (when?) they do?

A: I don’t get called hipster often; I don’t think I dress well enough. I think I tend to come across more as a lumberjack with a desk job.

Q: On closing, any words of wisdom for the GeoHipster crowd?

A: When I was teaching GIS in higher ed, I stressed the importance of projects and building a portfolio. Recent grads looking for work often have little to show to potential employers, so having some tangibles that demonstrate your capabilities is crucially important. I would always encourage them to work on projects that aligned with their personal passions. It’s much easier to convince yourself to dedicate the extra time if it’s something you enjoy or strikes your interest. It’s also much easier to stick with the project after you’ve gotten the job. I’ve started countless projects over my 15 years in the workforce and most were abandoned or anything but successful, but I’ve learned a lot from each project. Take that experience and funnel it into your next project. I never would have thought that I’d be developing web sites around assessment data back when I was initially struggling with getting and using the same data a decade earlier. I don’t know what I’ll be doing ten years from now, but I know there will be a wide variety of options ahead of me because I continued to learn, adapt, and put my mix of talents to use. I’m likely preaching to the choir, but I feel it needs to be said: keep working towards the next big thing.

Maps and mappers of the 2016 calendar: Mario Nowak

In our series “Maps and mappers of the 2016 calendar” we will present throughout 2016 the mapmakers who submitted their creations for inclusion in the 2016 GeoHipster calendar.


Mario Nowak

Q: Tell us about yourself.

A: I studied geography at the University of Zurich, Switzerland, and did a Master in Geographic Information Science. I also studied land-use planning at ETH Zurich. Now I’m working for sotomo, a company based in Zurich specializing in political surveys, data journalism, and data visualization.

Q: Tell us the story behind your map (what inspired you to make it, what did you learn while making it, or any other aspects of the map or its creation you would like people to know).

A: The map shows the rental prices for a flat in every municipality in Switzerland. We did this map on assignment for the Swiss newspaper Tages-Anzeiger. They used it for an article on rental prices in Switzerland.

It is the remake of a similar map my boss made in the nineties, but with newer data. In fact, this map is an animated map (see here): The temporal dimension is perceptible in the GIF version. The map also hints at the fact that Switzerland is a country of mountains, but in this map, the highest peaks are where the prices are the highest.

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

A: The data comes from Wüest & Partner. It has a price value for every municipality (around 2,500[CHF]) for every year from 2000 to 2015. I only needed to extract the centroid of each municipality from a shapefile (done in QGIS) and match it to the data.

The map was then completely done in R. Two packages were particularly important: automap with its autokrige function, and the package plot3d (and the PDF file 50 ways to draw a volcano).

I did a lot of kriging interpolations to get a smooth surface. I also did linear interpolations between every time-step to make the growing of the mountains smooth. Otherwise, the GIF would have consisted of only 15 images. Finally, I produced high resolution raster image files and stitched them together using a tool called GIF animator.

Of course, there was a lot of trial and error involved in making this map, but now I am quite pleased with the result. It was, by the way, also nominated for the German reporter prize (however, it did not win 😉 ).

'Monthly rental prices for 4-room flats in Switzerland' by Mario Nowak
‘Monthly rental prices for 4-room flats in Switzerland’ by Mario Nowak

Machiko Yasuda: “You’d be surprised how much spatial thinking is involved in something as basic as selling and shipping things”

Machiko Yasuda
Machiko Yasuda
Machiko Yasuda ( is a journalist-turned-web developer, who especially likes writing Ruby.

She loves to teach and organize. She has taught bike safety, web development at General Assembly and coached at Rails Girls. She helps organize a pair programming meetup and Maptime LA. Outside of work, she likes rock climbing and is currently obsessed with learning about alignment and Nutritious Movement.

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

A: I currently work in Los Angeles at the Reformation, an eco-friendly women’s fashion company. Reformation makes “clothes that don’t kill the environment”, and I make apps that help the in-house team and factory design, manufacture, and ship clothes around the world.

Q: How did you get attracted to mapping?

A: When I was little, I onced asked my parents for an e-mail address and my own domain for my birthday. I always wanted to “work for a big website” but didn’t know how. I chose colleges by comparing how professional their daily newspapers looked, and immediately joined the Daily Bruin at UCLA to work on their site. We mapped local crime data from the police logs, but that was about it.

I always wanted to get more into web mapping, but without a geography degree or an ArcGIS license I felt like I had no options. In 2010 though, at my first full-time job out of college at a daily local paper, I learned about Google Fusion Tables and that really changed my life. I found myself mapping census data with Google Fusion Tables, even converting latitude and longitude in degrees, minutes and seconds from the National Park Service into decimals in Excel — because I didn’t know any other way. That’s how I got into mapping and code.

I couldn’t answer this question without a shout out to all those early tutorials and open-source tools I first used: Google Fusion Tables tutorials from John Keefe at WNYC:,  SHPEscape for converting data formats:  and for colors.

Q: You are one of the co-organizers of MaptimeLA. Tell us how and why that happened, and what keeps you going back.

A:  After I got my first apprenticeship at a software start-up, I heard about the original Maptime in the Bay Area. I had met many developers through the local tech meetups, but not many interested in GIS and maps. I wondered, out loud, on Twitter, whether LA could start a Maptime. A few months later, Alan from MaptimeHQ contacted me with others who were also interested. Voila! That’s how MaptimeLA started.

MaptimeLA grew out of a handful of local map enthusiasts from all sorts of industries — architecture, software, transportation, environment, consulting, local government, social justice, to name a few — and we all have a love, a rather nerdy sort of love, for Los Angeles.

Los Angeles is a vast, often confusing, sometimes intimidating, mysterious place. Mapping and meeting people from other corners of LA are two ways to explore this city, and that’s what I think brings people back to Maptime here.

You can see through the maps we make at MaptimeLA, whether it’s maps of historic restaurants or food banks, that everyone’s trying to visualize their appreciation for LA and share it with others.

Mapillary's Johan explains the workings behind the app to MaptimeLA at Opodz
Mapillary’s Johan explains the workings behind the app to MaptimeLA at Opodz

Q: You are representative of a new generation of software engineers for whom GIS / spatial / mapping is just one of many tools in their arsenal. Will a GIS / mapping skillset be to the office worker of the future what typing is to the office worker of today? Or is it already?

A: I work in e-commerce and tech, and you’d be surprised how much “spatial thinking” is involved in something as basic as selling and shipping things. Whether it’s querying addresses and calculating distances, visually displaying geographic information, or estimating employees’ commute times, offices have a lot of “spatial needs”, as Ken Jennings calls it in his must-read book on different kinds of mapping nerds, “Maphead”.

In Ellen Ullman’s 1997 book, “Closer to the Machine”, she talks about how graphical user interfaces of the Internet and in particular, spreadsheet software, embolden users by being able to bring shape to data. ( ( The 2000s equivalent, I believe, are open source mapping tools.

Q: Along the same lines, you are representative of a new generation of software engineers who “do GIS” outside of the Esri ecosystem. What do you think about open source? Is open source the future of computing?

A: I wouldn’t have been able to learn GIS without open source software and tutorials — starting with Google Fusion Tables, QGIS, GDAL, ogr2ogr, Leaflet, Mapbox, and more. I already see a lot of friends in small non-profits using free tiers of Google Maps and Google Fusion Tables to create maps for their own without much coding necessary. The abilities to gather data, map boundaries, layer data and publish it are the new spreadsheets.

The more we can build mapping tools like OpenStreetMaps to involve as many new people as possible, the better for everyone.

I remember when I first moved to a new neighborhood two years ago, I noticed that on Apple Maps, my neighborhood was spelled incorrectly. “Del Rey” was spelled “Del Ray” everywhere. “Del Ray Blvd.”, “Marina Del Ray Elementary,” and “Del Ray” as the neighborhood. At the time, I did not know anything about OpenStreetMap, but was still able to somehow easily log in and request a spelling change. And now it’s fixed:

Everyone these days knows about Wikipedia, but not very many of even the computer-heads know about or use OpenStreetMap. I hope Maptime can change this.

Q: In his infamous rant about cloud computing, Oracle’s Larry Ellison says: “The computer industry is the only industry that’s more fashion-driven than women’s fashion.” Do you agree? Why / why not?

A: Agreed. In the computer industry there’s an even higher level of pretentiousness that comes with all the hardware and software choices you have to make: Mac vs. Windows, vim vs. something else, mechanical keyboards vs. everything else, and in GIS, Esri vs. everything else. I’ve found that at Maptime especially, that attitude drives people away and we try not to do that by making sure our tutorials and workshops cover as many operating systems and libraries.

Q: What is the normcore of GIS?

A: I don’t know how to answer this! Maybe Google Maps? It’s so ubiquitous, at least for us in developed areas. It’s plain, it’s unpretentious, it’s basic.

Q: As befitting to a geohipster, you cycle. Tell us why you do it.

A: Unlike most Angelenos, I didn’t get a car and a driver license at 16. I didn’t drive for all of college at UCLA and used a bike instead. As an especially unathletic, non-active, map-obsessed and tree-hugging child, biking was perfect for me. I got a scholarship to become a bike-safety instructor — where I got interested in hands-on teaching as a form of advocacy.

Q: On closing, any final thoughts for the GeoHipster crowd?

A: Cheers to another year of much mapping!