3D Printed Geographies – Techniques and Examples

April 25th, 2016

As a follow-up to my post on “Geospatial Data Preparation for 3D Printed Geographies” (19 Sept 2015), I am providing an update on the different approaches that I have explored with my colleague Dr. Claire Oswald for our one-year RECODE grant entitled “A 3D elevation model of Toronto watersheds to promote citizen science in urban hydrology and water resources”. The tools that we have used to turn geospatial data into 3D prints include the program heightmap2stl; direct loading of a grey scale image into the Cura 3D modeling software; the QGIS plugin DEMto3D; the script shp2stl.js; and a workflow using Esri’s ArcScene for 3D extraction, saving in VRML format, and translating this file into STL format using the MeshLab software.

The starting point: GIS and heightmap2stl

Being a GIS specialist with limited knowledge of 3D graphics or computer-aided design, all of the techniques used to make geospatial data printable rely heavily on the work of others, and my understanding of the final steps of data conversion and 3D print preparation is somewhat limited. With this in mind, the first approach to convert geospatial data, specifically a digital elevation model, used Markus Fussenegger’s Java program heightmap2stl, which can be downloaded from http://www.thingiverse.com/thing:15276/#files and used according to detailed instructions on “Converting DEMs to STL files for 3D printing” by James Dittrich of the University of Oregon. The process from QGIS or ArcGIS project to greyscale map image to printable STL file was outlined in my previous post at http://gis.blog.ryerson.ca/2015/09/19/geospatial-data-preparation-for-3d-printed-geographies/.

Quicker and not dirtier: direct import into Cura

The use of the heightmap2stl program in a Windows environment requires a somewhat cumbersome process using the Windows command line and the resulting STL files seemed exceedingly large, although I did not systematically investigate this issue. I was therefore very pleased to discover accidentally that the Cura software, which I am using with my Lulzbot Taz 5 printer, is able to load greyscale images directly.

The following screenshot shows the available parameters after clicking “Load Model” and selecting an image file (e.g. PNG format, not an STL file). The parameters include the height of the model, height of a base to be created, model width and depth within the available printer hardware limits, the direction of interpreting greyscale values as height (lighter/darker is higher), and whether to smoothen the model surface.


The most ‘popular’ model created using this workflow is our regional watershed puzzle. The puzzle consists of a baseplate with a few small watersheds that drain directly into Lake Ontario along with a set of ten separately printed watersheds, which cover the jurisdiction of the Toronto and Region Conservation Authority (TRCA).

Controlling geographic scale: QGIS plugin DEMto3D

Both of the first two approaches have a significant limitation for 3D printing of geography in that they do not support controlling geographic scale. To keep track of scale and vertical exaggeration, one has to calculate these values on the basis of geographic extent, elevation differential, and model/printer parameters. This is where the neat QGIS plugin DEMto3D comes into play.

As can be seen in the following screenshot, DEMto3D allows us to determine a print extent from the current QGIS project or layer extents; set geographic scale in conjunction with the dimension of the 3D print; specify vertical exaggeration; and set the height at the base of the model to a geographic elevation. For example, the current setting of 0m would print elevations above sea level while a setting of 73m would print elevations of the Toronto region in relation to the surface level of Lake Ontario. One shortcoming of DEMto3D is that vertical exaggeration oddly is limited to a factor of 10, which we found not always sufficient to visualize regional topography.


Using DEMto3D, we recently printed our first multi-part geography, a two-piece model of the Oak Ridges Moraine that stretches over 200km in east-west direction to the north of the City of Toronto and contains the headwaters of streams running south towards Lake Ontario and north towards Lake Simcoe and the Georgian Bay. To increase the vertical exaggeration for this print from 10x to 25x, we simply rescaled the z dimension in the Cura 3D printing software after loading the STL file.

Another Shapefile converter: shp2stl

The DEMto3D plugin strictly requires true DEM data (as far as I have found so far), thus it would not convert a Shapefile with building heights for the Ryerson University campus and surrounding City of Toronto neighbourhoods, which I wanted to print. Additionally, the approach using a greyscale image of campus building heights and one of the first two approaches above also did not work, as the 3D buildings represented in the resulting STL files had triangulated walls.

In looking for a direct converter from Shapefile geometries to STL, I found Doug McCune’s shp2stl script at https://github.com/dougmccune/shp2stl and his extensive examples and explanations in a blog post on “Using shp2stl to Convert Maps to 3D Models“. This script runs within the NodeJS platform, which needs to be installed and understood – the workflow turned out to be a tad too complicated for a time-strapped Windows user. Although I managed to convert the Ryerson campus using shp2stl, I never  printed the resulting model due to another, unrelated challenge of being unable to add a base plate to the model (for my buildings to stand on!).

Getting those walls straight: ArcScene, VMRL, and Meshlab

Another surprise find, made just a few days ago, enabled the printing of my first city model from the City of Toronto’s 3D massing (building height) dataset. This approach uses a combination of Esri’s ArcScene and the MeshLab software. Within ArcScene, I could load the 3D massing Shapefile (after clipping/editing it down to an area around campus using QGIS), define vertical extrusion on the basis of the building heights (EleZ variable), and save the 3D scene in the VRML format as a *.wrl (“world”) file. Using MeshLab, the VRML file could then be imported and immediately exported in STL format for printing.

While this is the only approach included in this post that uses a commercial tool, ArcScene, it is likely that the reader can find alternative workflow based on free/open-source software to extrude Shapefile polygons and turn them into STL, whether or not this requires the intermediate step through the VRML format.

In Search of the Mother of GIS?

April 6th, 2016

My thoughts on Panel Session: 1475 Gender & GIScience, at AAG 2016.

Guest post by Dr. Victoria Fast (@vvfast)

Roger Tomlinson has passed, and Mike Goodchild is in (a very active) retirement. So, this panel made me consider: are we searching for a new father of GIS? In fact, do we need a father of GIS? Would a mother of GIS balance the gender scales? It seems all disciplines need leaders, and the powerful panellists in this session—populated with many of my mentors and leaders in the field, including Renee Sieber, Nadine Schuurman, Sarah Elwood, Agnieszka Leszczynski, Britta Ricker, and Matthew Wilson—demonstrates that we indeed have strong leadership in GIScience. This mostly female panel is a reminder that, in fact, there are many influential female scholars. But do we hear these influences? Do we hear them equally? Have we heard them in the past? Based on the discussion in this session, the answer in overwhelmingly ‘no’.

The discussion in this session revolved around the ways in which our science has been heavily masculinized, epitomized by the commonly accepted ‘Father of GIS’ notion. The discipline has been dominated by all-male panels, focused on programming and physical science, subdued critical or theoretical work, and “straight up misogyny in GIScience” (Renee Sieber’s words). Female scholars are less frequently cited, underrepresented as researchers in the field, and almost absent in the representation of the history of the discipline.

This made me think of deep-rooted masculinization I have faced in my GIS journey, as a student and now as an educator. Issues related to working in the ‘old boys club’ aside, masculinization was especially predominant when I taught a second year Cartography course. The textbook “Thematic Cartography and Geovisualization” contains a chapter of the History of Cartography. Without sounding ‘…ist’ myself, the chapter largely recognized the contribution of older, white males. I didn’t feel comfortable teaching my students that narrow history of Cartography, so instead went looking for my own resources to populate a ‘History of Cartography’ lecture.

I was delightfully surprised that there are so many resources available that show multi-faceted sides of cartography (and GISci more broadly). These perspectives and resources are often shared via disparate sources in journal articles, blogs, and discussion forums. For example, Monica Stephens has a great publication on Gender and the Geoweb in Geojournal [2013, 78(6)]. City Labs also has a great series on the Hidden Histories of Maps Made by Women (thanks for sharing Alan McConchie): http://www.citylab.com/design/2016/03/women-in-cartography-early-north-america/471609/. Unfortunately, they refer to it as the “little seen contributions to cartography”, but panels like this help address that while they’re little seen, they are highly impactful contributions. Over time, these blog posts, journal articles, and conference panels will (hopefully) amass and make their way to more formalized forms of textbook knowledge. (There was a great deal of interest by those attending this session in a published version of these compiled resources. Given the overwhelming response, I’m considering compiling a manuscript… stay tuned.)

I recognize that it is impossible to undo the deep-rooted masculinization that has persisted in GIScience. However, we can change how we address it moving forward. Let’s recognize that we don’t need a father (or mother) of GIS; we need leaders, visionaries, and mentors of all shapes, sizes, colours, backgrounds, and genders. I challenge all those who are GI Professionals in training to look for the untold story, the hidden history of GIS, and the little-seen influences on the discipline. I challenge those who teach GIS to go beyond the ‘truth’ presented in the textbooks. And lastly, I want to conclude by saying thank you to the powerful female mentors on this panels and ones not represented here; mentors who transcend the need for a ‘Mother of GIS’.

Ryerson Geographers at AAG 2016

March 28th, 2016

Another year has passed, and another annual meeting of the Association of American Geographers (AAG) is about to start in San Francisco this week. The Department of Geography and Environmental Studies at Ryerson is sending its usual strong complement to AAG 2016, although the writer of these lines is sadly staying behind in a cold and rainy Toronto.

Contributions from @RyersonGeo have a traditional focus in Business Geography, with additional abstracts in the areas of urban forest, population health, migration & settlement, local food, renewable energy, and sustainability science. In approximate chronological order of presentation:

In addition to these contributions, Dr. Hernandez also serves as chair, introducer, organizer, and/or panelist of sessions on

  • BGSG Career Achievement Award: A Conversation with Ken Smith
  • Connecting Practitioners and Students – Advice on Career Development in the Field of Location Intelligence
  • Location Intelligence Trends in the Contemporary Omni-channel Retail Marketplace
  • Retail and Business Geography I & II

Dr. Millward also serves as chair of the session on “Arboriculture and Urban Forestry” and Dr. Steenberg is a panelist in the session entitled “Disrupt Geo 1: new ideas from the front lines of maps, mobile, and big data”.

We wish our colleagues and all participants a productive and enjoyable AAG 2016!

Victoria Fast and Daniel Liadsky receive Ryerson’s top award

November 11th, 2015

Blog post co-authored by Victoria Fast, Daniel Liadsky, and Claus Rinner

Ryerson’’s Department of Geography and Environmental Studies is celebrating two gold medal recipients this fall. The Ryerson Gold Medals are the University’s highest honours, presented annually to one graduate of each Faculty. Victoria Fast (PhD in Environmental Applied Science and Management, supervised by Dr. Claus Rinner) received the Gold Medal for the interdisciplinary programs housed at the Yeates School of Graduate Studies, while Daniel Liadsky (MSA in Spatial Analysis, supervised by Dr. Brian Ceh) received the Gold Medal for the Faculty of Arts.

Victoria’’s PhD research investigated the potential of novel geographic information techniques to reshape the interaction of government with community organizations and citizens through crowdsourcing and collaborative mapping. The study applied a VGI systems approach (Fast & Rinner 2014) to actively engage with urban food stakeholders, including regional and municipal government, NGOs, community groups, and individual citizens to reveal and map uniquely local and community-driven food system assets in Durham Region. The Durham Food Policy Council and Climate Change Adaptation Task Force are currently using the results to support informed food policy and program development. Victoria’s research contributes to geothink.ca, a SSHRC Partnership Grant on the impact of the participatory Geoweb on government-citizen interactions.

Daniel’’s research in the Master of Spatial Analysis (MSA) examined how dietary intake is mediated by individual, social, and environmental factors. The Toronto-based study was stratified by gender and utilized self-reported data from the Canadian Community Health Survey as well as measures of the food environment derived from commercial retail databases. The results uncovered some of the complex interactions between the food environment, gender, ethnocultural background, and socioeconomic restrictions such as low income and limited mobility. In addition and as part of an unrelated investigation, Daniel undertook a feasibility study into a mapping and data analytics service for the non-profit sector.



Congratulations 2015 MSA Graduates!

November 9th, 2015

Another year has passed and another ‘generation’ of professional Geographers has completed our Master of Spatial Analysis (MSA) degree. Congratulations to the 17 graduates of the Fall 2015 class!

All 17 MSA graduates after Fall 2015 Convocation (photo credit: Vadim Sabetski)

All 17 MSA graduates after Fall 2015 Convocation (photo credit: Vadim Sabetski)

MSA students are required to conduct an independent research project that is documented in a major research paper. This MRP is formally defended and subsequently revised prior to degree completion. This year’s MRPs span the range of applications from sustainable development, Toronto’s SmartTrack transit plan, food retail and foodscapes, health-care service locations, bank branch networks, crime patterns, urban heat islands, and housing. Methods chosen by the students include visual data exploration, multiple regression, multi-criteria decision analysis, risk terrain modeling, self-organizing maps, and many more.

The abstracts for the following 17 major research papers are available from the MSA program homepage at http://www.ryerson.ca/graduate/programs/spatial/abstracts/index.html. Supervisors are listed in parentheses.

  • Kaylin Chin: Evaluating Sustainable Development Across the Continuous United States: Application of the United Nations’ Indicators of Sustainable Development (Dr. Shaker)
  • Kiyomi French: Analysis of Distribution Centre Locations for a Major Retailer in Canada (Prof. Swales)
  • Adrien Friesen: Smart Track Station Evaluation in Toronto: Ridership Forecasting and Feasibility Analysis of Station Catchment Areas (Dr. S. Wang)
  • Alexa Hinves: Developing a Methodology for Measuring Access to Services: A Case Study of Access to Food Retail Services in the City of Toronto (Dr. Hernandez)
  • Elmer Lara Palacios: The Social and Spatial Patterning of Stress in Canada (Dr. L. Wang)
  • Jacob Levy: A Spatial Analysis of Distribution of Practicing International Medical Graduates in Canada, Ontario, and Toronto (Dr. L. Wang)
  • Daniel Liadsky: Exploring Toronto’s Foodscapes: Measuring The Food Environment and Healthy Eating Behaviours (Dr. Ceh)
  • Bernardo Melendez: Analyzing Change in Bank Branch Networks in the Toronto CMA (Dr. S. Wang)
  • Jessica Miki: PySAL an Open Source Development Framework for Spatial Analysis for Health Data (Dr. Vaz)
  • Nicia Moran: Site Selection using Geographic Information Systems and Multi-Criteria Decision Model (Prof. Swales)
  • Tyler Munn: Spatial Analysis of 911 STEMI Calls for Toronto Paramedic Services (Dr. L. Wang)
  • Ricardo Sanchez: Transformation of Book Retailing in Canada (Dr. S. Wang)
  • Maxwell Stiss: Ground Level Retail and Mid-Rise Development Trends along the ‘Avenues’ of the City of Toronto from 2010-2014 (Dr. Hernandez)
  • Shannon Strelioff: Examining Street Level Robbery Predictors in Durham, Ontario using Statistical and Risk Terrain Modeling (Dr. L. Wang)
  • Kirk Suitor: The Spatio-Temporal Analysis of Toronto Housing Prices (Dr. Kedron)
  • Christine Valancius: Comparing the Cooling Ability of Green Spaces in Suburban and Urban Areas using LST and NDVI (Dr. Forsythe)
  • Yishi Zhao: Cluster Analysis of Injury using Self-Organizing Maps – A Case Study of Extended Golden Horseshoe (Dr. Vaz)

Among the achievements of the Fall 2015 MSA class is Daniel Liadsky’s Ryerson Gold Medal, as described at http://www.ryerson.ca/news/news/General_Public/20151019-gold-medal-recipient-to-bring-technical-skills-to-nonprofit-sector.html, as well as Yishi Zhao’s 2nd place in the National Geographic student mapping competition (official announcement still not posted anywhere) and her MSA Award of Distinction, presented at the Department of Geography and Environmental Studies Awards Night on November 4, 2015.

I would also like to note that four students are extending their MSA research phase by one or two semesters to write an MSA thesis. The first student to complete this option, Heather Hart, graduated in Spring 2015 with a thesis on “Maps as Evidence in Health Care Service Improvement and Monitoring” (supervised by Dr. Rinner), which was also recently added to the list at http://www.ryerson.ca/graduate/programs/spatial/abstracts/index.html.

GIS Day 2015 at Ryerson – A Showcase of Geographic Information System Research and Applications

November 3rd, 2015

Ryerson students, faculty, staff, and the local community are invited to explore and celebrate Geographic Information Systems (GIS) research and applications. Keynote presentations will outline the pervasive use of geospatial data analysis and mapping in business, municipal government, and environmental applications. Research posters, software demos, and course projects will further illustrate the benefits of GIS across all sectors of society.

Date: Wednesday, November 18, 2015
Time: 1:00pm-5:00pm
Location: Library Building, 4th Floor, LIB-489 (enter at 350 Victoria Street, proceed to 2nd floor, and take elevators inside the library to 4th floor)

Tentative schedule:

  • 1:00 Soft kick-off, posters & demos
  • 1:25 Welcome
  • 1:30-2:00 Dr. Namrata Shrestha, Senior Landscape Ecologist, Toronto & Region Conservation Authority
  • 2:00-2:30 posters & demos
  • 2:30-3:00 Andrew Lyszkiewicz, Program Manager, Information & Technology Division, City of Toronto
  • 3:00-3:30 posters & demos
  • 3:30-4:00 Matthew Cole, Manager, Business Geomatics, and William Davis, Cartographer and Data Analyst, The Toronto Star
  • 4:00 GIS Day cake!
  • 5:00 End

GIS Day is a global event under the motto “Discovering the World through GIS”. It takes place during National Geographic’s Geography Awareness Week, which in 2015 is themed “Explore! The Power of Maps”, and aligns with the United Nations-supported International Map Year 2015-2016.

Event co-hosted by the Department of Geography & Environmental Studies and the Geospatial Map & Data Centre. Coffee/tea and snacks provided throughout the afternoon. Contact: Dr. Claus Rinner

Geospatial Data Preparation for 3D Printed Geographies

September 19th, 2015

I am collaborating with my colleague Dr. Claire Oswald on a RECODE-funded social innovation project aimed at using “A 3D elevation model of Toronto watersheds to promote citizen science in urban hydrology and water resources”. Our tweets of the first prototypes printed at the Toronto Public Library have garnered quite a bit of interest – here’s how we did it!


The process from geography to 3D print model includes four steps:

  1. collect geospatial data
  2. process and map the data within a geographic information system (GIS)
  3. convert the map to a 3D print format
  4. verify the resulting model in the 3D printer software

So far, we made two test prints of very different data. One is a digital elevation model (DEM) of the Don River watershed, the other represents population density by Toronto Census tracts. A DEM for Southern Ontario created by the Geological Survey of Canada was downloaded from Natural Resources Canada’s GeoGratis open data site at http://geogratis.gc.ca/. It came in a spatial resolution of 30m x 30m grid cells and a vertical accuracy of 3m.

The Don River watershed boundary from the Ontario Ministry of Natural Resources was obtained via the Ontario Council of University Libraries’ geospatial portal, as shown in the following screenshot.

Download of watershed boundary file

The population density data and Census tract boundaries from Statistics Canada were obtained via Ryerson University’s Geospatial Map and Data Centre at http://library.ryerson.ca/gmdc/ (limited to research and teaching purposes).

The Don River watershed DEM print was prepared in the ArcGIS software by clipping the DEM to the Don River watershed boundary selected from the quaternary watershed boundaries. The Don River DEM was visualized in several ways, including the “flat” greyscale map with shades stretched between actual minimum and maximum values, which is needed for conversion to 3D print format, as well as the more illustrative “hillshade” technique with semi-transparent land-use overlay (not further used in our 3D project).

DEM of Don River watershedHillshade of Don River valley at Thorncliffe Park

The population density print was prepared in the free, open-source QGIS software. A choropleth map with a greyscale symbology was created, so that the lighter shades represented the larger population density values (yes, this is against cartographic design principles but needed here). A quantile classification with seven manually rounded class breaks was used, and the first class reserved for zero population density values (Census tracts without residential population).


In QGIS’ print composer, the map was completed with a black background, a legend, and a data source statement. The additional elements were kept in dark grey so that they would be only slightly raised over the black/lowest areas in the 3D print.


The key step of converting the greyscale maps from the GIS projects to 3D print-compliant STL file format was performed using a script called “heightmap2stl.jar” created by Markus Fussenegger. The script was downloaded from http://www.thingiverse.com/thing:15276/#files, and used with the help of instructions written by James Dittrich of the University of Oregon, posted at http://adv-geo-research.blogspot.ca/2013/10/converting-dems-to-stl-files-for-3d.html. Here is a sample run with zero base height and a value of 100 for the vertical extent.

Command for PNG to STL conversion

The final step of pre-print processing involves loading the STL file into the 3D printer’s proprietary software to prepare the print file and check parameters such as validity of the structure, print resolution, fill options for hollow parts, and overall print duration. At the Toronto Public Library, 3D print sessions are limited to two hours. The following screenshot shows the Don River DEM in the MakerBot Replicator 2 software, corresponding to the printer used in the Library. Note that the model shown was too large to be printed in two hours and had to be reduced below the maximum printer dimensions.

Don River watershed model in 3D printing software

The following photo by Claire Oswald shows how the MakerBot Replicator 2 in the Toronto Reference Library’s digital innovation hub prints layer upon layer of the PLA plastic filament for the DEM surface and the standard hexagonal fill of cavities.

DEM in printing process - photo by C. Oswald

The final products of our initial 3D print experiments have dimensions of approximately 10-20cm. They have made the rounds among curious-to-enthusiastic students and colleagues. We are in the process of improving model quality, developing additional models, and planning for their use in environmental education and public outreach.

The printed Don River watershed model

3D-printed Toronto population density map

Geography at Ryerson – Your Social Innovation Powerhouse

August 26th, 2015

Innovation in higher education and scholarly research has always been a hallmark of the Department of Geography and Environmental Studies at Ryerson. Recent faculty and student achievements underline our position as a social innovation powerhouse on campus.

In the competition for “RECODE at Ryerson University” grants, @RyersonGeo faculty are leading three of the eight successful applications. That is 37.5% of these social innovation projects across campus, a proportion even more impressive if you consider the competitive process with eight grants selected among 33 applications, a success rate of only 24%.

oswald_3d-printed-DEM-tweet With her RECODE grant, Dr. Claire Oswald, in collaboration with Dr. Claus Rinner and 3D printing startup company Think To Thing, plans to use “A 3D elevation model of Toronto watersheds to promote citizen science in urban hydrology and water resources”. Undergraduate students from our Geographic Analysis and Environment and Urban Sustainability programs will help with processing geospatial data to create a tangible model of the Don River watershed. The model is to be used for school and community outreach on pressing urban water issues.

shaker_roncesvalles-OSMDr. Richard Shaker received a RECODE grant for “A prototype for reaching sustainability through local business improvement initiatives: Roncesvalles Village”. In collaboration with the Roncesvalles Business Improvement Area in Toronto, Dr. Shaker’s team will develop metrics of sustainability of local restaurants to support sustainable community planning and management.

millward_citytrees-homepageThe goal of Dr. Andrew Millward’s proposal is to advance “The Citytrees Project: a tool of social innovation that engages people to work collectively and make our cities greener and more resilient”. RECODE funding will assist with forming new community partnerships and collecting tree data with GPS in collaboration with the Toronto Parks and Trees Foundation.

In addition to the faculty grants, our students were equally active and successful in applying for funding from the RECODE student competition.

Jennifer Fisher, a student in our BA in Environment and Urban Sustainability, received a grant to create “Soul Roots”, an urban agriculture project that employs “alternative farming practices to create large yield crops on a contaminated land site”. Working with Provincial and municipal partners in Toronto’s Parkdale community, the project also aims to demonstrate the social and economic impact of local food production.

Sarah Brigel, another student in the EUS program, is using RECODE funds to develop a pilot for her “Microbe-Hub Campus Compost Initiative”. The project aims to divert all organic waste from the Faculty of Arts’ Jorgenson Hall 14-storey building using a closed-loop vermicomposting system.

Another playing field for social innovation made @RyersonGeo is the Faculty of Arts’ SocialVentures Zone. Of the seven student-led social enterprises currently being incubated in the Zone, two were founded by our students, including Jennifer’s “Soul Roots”.

The other SocialVenturesZone project is Claire Stevenson-Blythe’s “Reciprocity”, an app-based platform to help people with signing up for local environmental volunteer opportunities. Claire’s enterprise is focused on engaging active citizenship and sharing solutions for the sustinability issues of our time.

Geography in its analytic, applied, and urban-focused form practiced at Ryerson is destined to inspire and train future social innovators and sustainability leaders. Stay tuned for more news!

Background on the RECODE at Ryerson University initiative: http://www.ryerson.ca/research/media/archive/2014/1106recode.html

List of student projects in the SocialVentures Zone: http://www.ryerson.ca/svz/projects/index.html

Looking for a secure, laid-back, and meaningful job in a growing field? Get into Geography!

July 10th, 2015

This text was first posted as a guest contribution to WhyRyerson?, the Undergraduate Admissions and Recruitment blog at Ryerson University. Images were added after the initial posting.

Geography@Ryerson is different. Atlases, globes, and Google Maps are nice pastimes, but we are more interested in OpenStreetMap, CartoDB, and GeoDA. We map global flight paths, tweets, invasive species, and shoplifters. As a student in Geographic Analysis you will gain real-world, or rather real-work, experience during your studies. This degree is unique among Geo programs in Ontario, if not in Canada, for its career focus.


Mapping global flight paths.
(Source: Toronto Star, 24 May 2013

The BA in Geographic Analysis has a 40-year record of placing graduates in planning and decision-making jobs across the public and private sectors. Jobs include Data Technician, Geographic Information Systems (GIS) Specialist, Geospatial Analyst, Mapping Technologist, GIS Consultant, Environmental Analyst, Market Research Analyst, Real-Estate Analyst, Crime Analyst, and many more. You name the industry or government branch, we’ll tell you what Geographers are doing for them. And these jobs are secure: Many are within government, or, if they are in the private sector, they tend to be in units that make businesses more efficient (and therefore are essential themselves!).

And these are great jobs, too. In November 2013, GIS Specialists were characterized as a low-stress job by CNN Money/PayScale. There were half a million positions in the US, with an expected 22% growth over 10 years, and a median pay of US$53,400 per year. In their previous survey, Market Research Analysts had made the top-10, with over a quarter million jobs, over 40% expected growth, and a median pay of US$63,100. The 2010 survey described GIS Analyst as a stress-free job with a median salary of US$75,000.


Mapping Technologist, one of Canada’s best jobs!
(Source: Canadian Business, 23 April 2015)

Closer to home, in April 2015 Canadian Business magazine put Mapping Technologists among the top-10 of all jobs in Canada! They note that “The explosion of big data and the growing need for location-aware hardware and software has led to a boom in the field of mapping”. With a median salary of CA$68,640, a 25% salary growth, and a 20% increase in jobs over five years, “this class of technology workers will pave the way”. According to Service Canada, “Mapping and related technologists and technicians gather, analyze, interpret and use geospatial information for applications in natural resources, geology, environment and land use planning. […] They are employed by all levels of government, the armed forces, utilities, mapping, computer software, forestry, architectural, engineering and consulting firms”. Based on the excellent reputation of our program in the Toronto area, you can add the many jobs in the business, real-estate, social, health, and safety fields to this list!


Sample applications of Geographic Analysis
(Source: Google image search)

While you may find the perspective of a well-paid, laid-back job in a growing field attractive enough, there is more to being a Ryerson-trained Geographer. Your work will help make important decisions in society. This could be with the City of Toronto or a Provincial or Federal ministry, where you turn geospatial data into maps and decision support tools in fields such as environmental assessment, social policy, parks and forestry, waste management, immigration, crime prevention, natural resources management, utilities, transportation, … . Or, you may find yourself analysing socio-economic data and crime incidents for a regional police service in order to guide their enforcement officers, as well as crime prevention and community outreach activities. Many of our graduates work for major retail or real-estate companies determining the best branch locations, efficient delivery of products and services, or mapping and forecasting population and competitors. Or you could turn your expertise into a highly profitable free-lance GIS and mapping consultancy.

Geography is one of the broadest fields of study out there, which can be intimidating. Geography@Ryerson however is different, as we provide you with a “toolkit” to turn your interest in the City, the region, and the world, and your fascination with people and the environment, into a fulfilling, secure, laid-back, yet meaningful job!

Toronto elevation model in Minecraft

June 8th, 2015

Minecraft is a fascinating video game that remains popular with the pre-teen, teen, and post-teen crowds. You build and/or exploit a 3D world by manipulating blocks of various materials such as “stone”, “dirt”, or “sand”. In the footsteps of my colleague Pamela Robinson in the School of Urban and Regional Planning, and her student Lisa Ward Mather, I became interested in ‘serious’ applications of Minecraft. Lisa studied the use of the game as a civic engagement tool. Apparently, the blocky 3D nature of Minecraft worlds can be useful in planning to give viewers an idea of planned building volumes while making it clear that preliminary display are not architectural plans.

Taking a geographic perspective, I am interested in the potential of Minecraft to educate kids about larger areas, say the City of Toronto. In this post, I outline the conversion of a digital elevation model (DEM) into a Minecraft terrain. I imagine the output as a novel way for ‘gamers’ to explore and interact with the city’s topography. Some pointers to related, but not Toronto-specific work include:

  • GIS StackExchange discussion on “Bringing GIS data into Minecraft“, including links to the UK and Denmark modeled in Minecraft
  • A video conversation about “Professional Minecraft GIS“, where Ulf Mansson combined OpenStreetMap and open government data
  • Workflow instructions for converting “Historical Maps into Minecraft” using WorldPainter, which automatically converts DEMs into Minecraft terrain (if I had seen this before I started implementing the Python script outlined below…)
  • An extensive webinar on “Geospatial and Minecraft” by FME vendor Safe Software, touching on creating Minecraft worlds from DEMs, GPS, LiDAR, building information management, and the rule-based CityEngine software

The source data for my modest pilot project came from the Canadian Digital Elevation Model (CDEM) by Natural Resources Canada, accessed using the GeoGratis Geospatial Data Extraction tool at http://geogratis.gc.ca/site/eng/extraction. In QGIS, I converted the GeoTIFF file to ASCII Grid format, which has the advantage of being human-readable. I also experimented with clipping parts from the full DEM and/or reducing the raster resolution, since the first attempts at processing would have taken several hours. The QGIS 2.2 raster translate or clip operations ran a GDAL function along the following lines (see http://www.gdal.org/gdal_translate.html and http://www.gdal.org/formats_list.html for details):

gdal_translate -projwin [xmin ymin xmax ymax] -outsize 25% 25% -of AAIGrid [input_file.tif] [output_file.asc]

On the Minecraft side, you need an account (for a small cost), a working copy of the game, and an installation of MCEdit. Player accounts are sold and managed by the game’s developer company, Mojang, see https://minecraft.net/store/minecraft. The Minecraft software itself is launched from the Web – don’t ask about the details but note that I am using version 1.8.7 at the time of writing. MCEdit is a free tool for editing saved Minecraft worlds. It has an option to add functionality through so-called ‘filters’.

The MCEdit filter I wrote is “dem_gen.py”, a Python script that collects a few input parameters from the user and then reads an ASCII GRID file (currently hard-coded to the above-mentioned Toronto area DEM), iterates through its rows (x direction) and columns (y direction in GIS, z in Minecraft), and recreates the DEM in Minecraft as a collection of ‘columns’ (z direction in GIS, y in Minecraft). Each terrain column is made of stone at the base and dirt as the top-most layer(s), or of other user-defined materials.

I have freshly uploaded the very first version 0.1 to GitHub, see https://github.com/crinner/mc_dem_gen. (This also serves as my first developer experience with GitHub!) The general framework for an MCEdit filter and the loop creating the new blocks were modified from the “mountain_gen.py” (Mountain Generator) filter found at http://www.mediafire.com/download.php?asfkqo3hk0lkv1f. The filter is ‘installed’ by placing it in the filter subfolder in the MCEdit installation. The process then simply involves creating an empty world (I used a superflat world with only a bedrock layer) and running the DEM Generator filter. To run any filter in MCEdit, select an area of the world, press ‘5’, and select the filter from the list.


Converting the 2,400 by 1,600 pixel CDEM dataset shown in the above screenshot of my QGIS project took about half a day on a middle-aged Dell Latitude E6410 laptop.  The screenshot below shows that many data “chunks” are missing from this preliminary result, perhaps an issue when saving the terrain in MCEdit.


With a coarser DEM resolution of 600 by 400 pixels and using a newer Dell XPS 12 tablet (!), the processing time was reduced to 10 or so minutes and the result is promising. In the following screenshots, we are – I believe – looking at the outlets of the Humber River and Don River into Lake Ontario. Note the large vertical exaggeration that results from the horizontal dimensions being shrunk from around 1 block = 20m to 1 block = 80m, while vertically 1 block corresponds to 5m.



There remain a number of challenges, including a problem translating the geographic x/y/z coordinate system into the game’s x/-z/y coordinate system – the terrain currently is not oriented properly. More thought also has to be put into the scaling of the horizontal dimensions vis-a-vis the vertical dimension, adding the Lake Ontario water level, and creating signs with geographic names or other means of orientation. Therefore, your contributions to the GitHub project are more than welcome!

Update, 10 June 2015: I was made aware of the #MinecraftNiagara project, which Geospatial Niagara commissioned to students in the Niagara College GIS program. They aim to create “a 1:1 scale representation of Niagara’s elevation, roads, hydrology and wooded areas” to engage students at local schools with the area’s geography. It looks like they used ArcGIS and the FME converter, as described in a section of this blog post: http://geospatialniagara.com/backlog-of-updates/. Two screenshots of the Lower Balls Falls near St. Catharines were provided by @geoniagara’s Darren Platakis (before and after conversion):

minecraftNiagara-screenshot1    minecraftNiagara-screenshot2