MSA Poster Day 2015

composite-photo_msa-poster-day2015

On Wednesday, 29 April 2015, 22 Master of Spatial Analysis (MSA) students presented their research ideas/plans for their major research papers or theses to the Department. The students’ posters represented a mind-blowing diversity of research topics, with the important common denominator of using spatial analysis concepts and techniques. Techniques ranged from self-organizing maps to location-allocation, risk terrain modeling, cluster analysis, and various forms of regression analysis. Proposed tools included ArcGIS, MapInfo, QGIS/PySAL, and R. Finally, the fields of application span sustainable development to informal caregiving, housing deprivation, food access, regional transit planning, road salt usage, traffic injuries, ground-penetrating radar, urban heat island, and book retailing and mall tenant mix. Enjoy studying the following list of all poster titles!

msa-poster-day2015_working-titles

The MSA Best Poster Award 2015 went to Daniel Liadsky for the poster on “Neighbourhood Effects on Fruit and Vegetable Consumption in the Toronto CMA” shown below (click to enlarge). Congratulations, Daniel!!

daniels-winning-poster

Notes for #NepalQuake Mapping Sessions @RyersonU Geography

This is an impromptu collection of information to support a series of meetings of Ryerson students, faculty, and alumni of the Department of Geography and Environmental Studies with getting started with OpenStreetMap (OSM) improvements for Nepal. As part of the international OSM community’s response, contributions may help rescuers and first-responders to locate victims of the devastating earthquake.

Note that I moved the reports on our mapping sessions out into a separate post at http://gis.blog.ryerson.ca/2015/05/04/notes-from-nepalquake-mapping-sessions-ryersonu-geography/.

Information from local mappers: Kathmandu Living Labs (KLL), https://www.facebook.com/kathmandulivinglabs. KLL’s crowdmap for reports on the situation on the ground: http://kathmandulivinglabs.org/earthquake/

Humanitarian OpenStreetMap Team (HOT): http://hotosm.org/, http://wiki.openstreetmap.org/wiki/2015_Nepal_earthquake

Guides on how to get started with mapping for Nepal:

Communications among HOT contributors worldwide: https://kiwiirc.com/client/irc.oftc.net/?nick=mapper?#hot. Also check @hotosm and #hotosm on Twitter.

Things to consider when mapping:

  • When you start editing, you are locking “your” area (tile) – make sure you tag along, save your edits when you are done, provide a comment on the status of the map for the area, and unlock the tile.
  • Please focus on “white” tiles – see a discussion among HOT members on the benefits and drawbacks of including inexperienced mappers in the emergency situation, http://thread.gmane.org/gmane.comp.gis.openstreetmap.hot/7540/focus=7615 (via @clkao)
  • In the meantime (May 3rd), some HOT tasks have been designated for “more experienced mappers” and few unmapped areas are left in other tasks; you can however also verify completed tiles or participate in tasks marked as “2nd pass” in order to improve on previous mapping.
  • Don’t use any non-OSM/non-HOT online or offline datasets or services (e.g. Google Maps), since their information cannot be redistributed under the OSM license
  • Don’t over-estimate highway width and capacity, consider all options (including unknown road, track, path) described at http://wiki.openstreetmap.org/wiki/Nepal/Roads. Here is a discussion of the options, extracted from the above-linked IRC (check for newer discussions on IRC or HOT email list):

11:23:18 <ivansanchez> CGI958: If you don’t know the classification, it’s OK to tag them as highway=track for dirt roads, and highway=road for paved roads

11:26:06 <SK53> ivansanchez: highway=road is not that useful as it will not be used for routers, so I would chose unclassified or track

12:31:12 <cfbolz> So track is always preferable, if you don’t have precise info?
12:32:11 <cfbolz> Note that the task instructions directly contradict this at the moment: “highway=road Roads traced from satellite imagery for which a classification has not been determined yet. This is a temporary tag indicating further ground survey work is required.”

Another example of a discussion of this issue: http://www.openstreetmap.org/changeset/30490243

  • Map only things that are there, not those that may/could be there. Example: Don’t map a helipad object if you spot an open area that could be used for helicopter landing, create a polygon with landuse=grass instead (thanks to IRC posters SK53 and AndrewBuck).
  • Buildings as point features vs. residential areas (polygons): To expedite mapping, use landuse=residential, see IRC discussion below.
    hotosm_how-to-map-remote-buildings
    More about mapping buildings: http://wiki.openstreetmap.org/wiki/Nepal_remote_mapping_guide
  • Be aware that your edits on OSM are immediately “live” (after saving) and become part of the one and only OSM dataset. In addition, your work can be seen by anyone and may be analyzed in conjunction with your user name and locations (and thus potentially with your personal identity)

Note that I am a geographer (sort of) and GIScientist, but not an OpenStreetMap expert (yet). If you have additions or corrections to the above, let me know!

Ryerson Geographers at AAG 2015

The Department of Geography and Environmental Studies is sending a sizable delegation of researchers down south (or should that be west?) to Chicago, to spread the word about our awesome research in applied and other geographies! The annual meeting of the Association of American Geographers (AAG) also is the premier venue to pick up research trends and network with colleagues representing the full breadth of the discipline.

Here is the “Ryerson program” in detail, with an update to the “Retail and Business Geography I” session. In all, there are about 14 faculty members and 7 students presenting (not including co-authors), and we are involved in 29 sessions (including organizer, chair, panelist, etc.)!

TUESDAY

Paper Session: Trees in the City 1: Biophysical Conditions
Tuesday, 4/21/2015 at 8:00 AM
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=21902

Abstract Title: The Effectiveness of Tillage Radish® to Improve the Growing Medium for Urban Trees
Author(s):
Shawn Mayhew-Hammond, MASc* – Urban Forest Research & Ecological Disturbance (UFRED) Group, Ryerson University
Andrew A Millward, Ph.D. – Urban Forest Research & Ecological Disturbance (UFRED) Group, Ryerson University

Abstract Title: Virtual Daylighting: Enhancing Arboriculture Consulting Practices Through Tree Root Location with Ground-Penetrating Radar (GPR)
Author(s):
*Vadim Sabetski – Ryerson University
Andrew Millward, Dr. – Ryerson University

Abstract Title: Influence of Organic Mulch on Soil Characteristics in a Forested Urban Park
Author(s):
*Andrew A Millward, Ph.D. – Urban Forest Research & Ecological Disturbance (UFRED) Group, Ryerson University
Todd Irvine, MFC, ISA Certified Arborist – Bruce Tree Expert Company Ltd.

Paper Session: Trees in the City 2: Mapping and Measurement
Tuesday, 4/21/2015 at 10:00 AM
Abstract Title: Enabling Environmental Agents: Can Citytrees Help our Cities Grow?
Author(s):
Nikesh N. Bhagat* – Urban Forest Research & Ecological Disturbance (UFRED) Group, Ryerson University
Andrew A Millward, Ph.D. – Urban Forest Research & Ecological Disturbance (UFRED) Group, Ryerson University
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=63163

Paper Session: 1457 Geographies of Media III: Multicultural media, international migration, and transnationalism
Tuesday, 4/21/2015, from 12:40 PM – 2:20 PM
Discussant(s): Sutama Ghosh – Ryerson University
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=22272

Paper Session: Trees in the City 4: Human- Forest Relationships
Tuesday, 4/21/2015 at 14:40 PM.
Abstract Title: Assessing Urban Forest Ecosystem Change and the Vulnerability of Ecosystem Service Supply in a Residential Neighborhood
Author(s):
James Steenberg* – Ryerson University
Andrew Millward, PhD – Ryerson University
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=64090

WEDNESDAY

Paper Session: 2178 Retail and Business Geography I
Wednesday, 4/22/2015, from 8:00 AM – 9:40 AM
Organizer(s):
Tony Hernandez – Ryerson University
Murray Rice – University of North Texas
Chair(s): Tony Hernandez – Ryerson University
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=21599

Abstract Title: The Mixed Use Challenge: Turning Tides of Retail Development
Author(s):
Christopher Daniel* – Ryerson University – CSCA
Tony Hernandez, Ph.D. – Ryerson University – CSCA

Abstract Title: The Polarizing Canadian Market: High-end Retail Change
Author(s):
*Stephen Swales – Ryerson University
Wayne Forsythe – Ryerson University

Paper Session: 2184 Biofuels, Bioenergy, and the Emerging Bio-Economy I: Visions
Wednesday, 4/22/2015, from 8:00 AM – 9:40 AM
Organizer(s):
Peter Kedron – Ryerson University
Jennifer Baka – London School of Economics
Kirby Calvert
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=21162

Paper Session: 2284 Biofuels, Bioenergy, and the Emerging Bio-Economy II: Landscapes
Wednesday, 4/22/2015, from 10:00 AM – 11:40 AM
Organizer(s):
Peter Kedron – Ryerson University
Jennifer Baka – London School of Economics
Kean Birch – York University
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=21518

Paper Session: Geographies of Activism and Protest II
Wednesday, 4/22/2015 at 10:00 AM
Abstract Title: Indigenous Armed Resistance as Activism
Author(s): Valentina Capurri* – Ryerson University
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=61291

Panel Session: 2278 The Huff Model: from origins to modeling legacy
Wednesday, 4/22/2015, from 10:00 AM – 11:40 AM
Organizer(s):
Tony Hernandez – Ryerson University
Anthony Lea
Daniel A. Griffith – U. of Texas at Dallas
Chair(s): Tony Hernandez – Ryerson University
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=21725

Panel Session: 2478 Dr. David Huff: a tribute to his contribution to applied geographical and business research
Wednesday, 4/22/2015, from 1:20 PM – 3:00 PM
Organizer(s):
Tony Hernandez – Ryerson University
John Frazier – Binghamton University
Chair(s): Tony Hernandez – Ryerson University
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=21724

Paper Session: 2484 Biofuels, Bioenergy, and the Emerging Bio-Economy III: Transitions I
Wednesday, 4/22/2015, from 1:20 PM – 3:00 PM
Organizer(s):
Peter Kedron – Ryerson University
Kean Birch – York University
Sharmistha Bagchi-Sen – SUNY-Buffalo
Chair(s): Peter Kedron – Ryerson University
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=21163

Paper Session: 2584 Biofuels, Bioenergy, and the Emerging Bio-Economy IV: Transitions II
Wednesday, 4/22/2015, from 3:20 PM – 5:00 PM
Organizer(s):
Peter Kedron – Ryerson University
Kirby Calvert
Jennifer Baka – London School of Economics
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=21517

Abstract Title: Geographies of bioenergy from corn to high-tech biofuels
Author(s): Peter Kedron* – Ryerson University

Paper Session: Land Use Change and Ecosystem Services
Wednesday, 4/22/2015 at 17:20 PM.
Abstract Title: Spatiotemporal patterns and landscape metrics on First Nation reserves: The case of southern Ontario
Author(s): Eric Vaz* – Ryerson University
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=64724

THURSDAY

Paper Session: Immigrants, ethnicity, gender, race and health disparities in North American Cities
Thursday, 4/23/2015 at 8:00 AM.
Abstract Title: Composition and locational strategies of International Medical Graduates (IMGs) in Canada
Author(s):
Lu Wang* – Ryerson University
Jacob Levy – Ryerson University
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=63112

Panel Session: 3132 Immigration and Law, Migrant Activism, ‘Citizenship after Orientalism’
Thursday, 4/23/2015, from 8:00 AM – 9:40 AM
Discussant(s):
Leif Johnson
Harald Bauder – Ryerson University
Pierpaolo Mudu – University of Washington – Tacoma
Sutapa Chattopadhyay – UNU-Merit & Maastricht University
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=21859

Panel Session: 3178 Faculty Opportunities for Research and Teaching in Location Intelligence
Thursday, 4/23/2015, from 8:00 AM – 9:40 AM
Organizer(s):
Murray Rice – University of North Texas
Tony Hernandez – Ryerson University
Panelist(s): Tony Hernandez – Ryerson University
Simona Epasto – University of Macerata
William Graves – UNC-Charlotte
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=21524

Paper Session: 3276 2nd Special Session Retail aspects in Urban Geography and Urban Planning IV: Spatial impact of key supply and demand trends in retailing
Thursday, 4/23/2015, from 10:00 AM – 11:40 AM
Discussant(s): Tony Hernandez – Ryerson University
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=22018

Paper Session: Weather, Climate, and Health IV: Interventions and Solutions
Thursday, 4/23/2015 at 15:20 PM
Abstract Title: An analysis of the influence of multi-scalar characteristics of city trees on microclimatic variation within Toronto’s urban forest: a hierarchical approach
Author(s):
Christopher Greene* – Ryerson University
Peter J. Kedron, PhD – Ryerson University
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=67177

FRIDAY

Paper Session: 4102 Retail and Business Geography II
Friday, 4/24/2015, from 8:00 AM – 9:40 AM
Organizer(s):
Tony Hernandez – Ryerson University
Murray Rice – University of North Texas
Chair(s): Tony Hernandez – Ryerson University
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=22641

Abstract Title: Location Strategies of Foreign Retailers in Canada
Author(s):
Joseph Aversa* – Ryerson University
Tony Hernandez – Ryerson University

Abstract Title: Reconstructing Target’s Location Strategy in Canada
Author(s):
*Peter Pavlakidis, MSA – Environics Analytics
Shuguang Wang, Dr. – Co-Presenter

Abstract Title: Rethinking Retail Geography
Author(s): Tony Hernandez* – Ryerson University

Panel Session: 4202 Rethinking Ethnic Entrepreneurship
Friday, 4/24/2015, from 10:00 AM – 11:40 AM
Organizer(s):
Antonie Schmiz – Goethe-Universitaet Frankfurt a.M.
Tony Hernandez – Ryerson University
Panelist(s):
Shuguang Wang – Ryerson University
Zhixi Zhuang – Ryerson University
Felicitas Barbara Hillmann – Free University Berlin
Veronique Schutjens – University of Amsterdam, The Netherlands
Linda Szabó – Central European University
Charlotte Rauchle – Humboldt-University Berlin, Geography Department
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=21603

Paper Session: Food Networks and Politics I: Urban Scenarios
Friday, 4/24/2015 at 10:00 AM.
Abstract Title: Food Consumption and the Retail Food Environment: Examining Toronto’s Food Scapes
Author(s):
Daniel Liadsky* – Ryerson University
Brian Ceh – Ryerson University
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=68349

Poster Session: Geographic Information Science and Technology (GIS&T) Poster Session
Friday, 4/24/2015 at 10:00 AM
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=69026

Abstract Title: Conceptualizing Volunteered Geographic Information and the Participatory Geoweb
Author(s):
Victoria Fast* – Ryerson University
Claus Rinner – Ryerson University
Blake Byron Walker – Simon Fraser University

Abstract Title: The Role of Maps and Composite Indices in Place-Based Decision-Making
Author(s):
Claus Rinner* – Ryerson University, Geography
Heather Hart – Ryerson University, Geography
Meghan McHenry – Ryerson University, Geography
Carmen Huber – Ryerson University, Geography
Duncan MacLellan – Ryerson University, Politics

Panel Session: 4437 The Housing and Economic Experiences of Immigrants in U.S. and Canadian Cities
Friday, 4/24/2015, from 1:20 PM – 3:00 PM
Panelist(s):
Margaret W. Walton-Roberts – Wilfrid Laurier University
Wan Yu – Arizona State University
Sutama Ghosh – Ryerson University
John Frazier – Binghamton University
John Miron – University of Toronto
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=22612

Paper Session: Restore Urban River’s Water Quality to Swimmable/Fishable
Friday, 4/24/2015 at 13:20 PM
Abstract Title: Using Geospatial Techniques for Water Research: Disinfection Byproducts in Drinking Water in Ontario, Canada
Author(s):
Brian Ceh* – Ryerson University
Mary Grunstra – Ryerson University
Eric Vaz – Ryerson University
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=66101

Panel Session: 4513 Student Opportunities for Study and Career Development in Location Intelligence
Friday, 4/24/2015, from 3:20 PM – 5:00 PM
Organizer(s):
Murray Rice – University of North Texas
Tony Hernandez – Ryerson University
Simona Epasto – University of Macerata
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=21527

SATURDAY

Paper Session: Mental Health Geographies
Saturday, 4/25/2015 at 8:00 AM
Abstract Title: Crowd mapping mental health promotion through the Thought Spot project
Author(s):
Heather A Hart* – Ryerson University
Victoria Fast – Ryerson University
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=67972

Paper Session: Dialectics in Geography: Opportunities and Limitations
Saturday, 4/25/2015 at 14:00 PM
Abstract Title: Reflections on Dialectics as Theory and/or Method
Author(s): Harald Bauder* – Ryerson University
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=61298

Panel Session: 5531 Radical teaching
Saturday, 4/25/2015, from 4:00 PM – 5:40 PM in Columbian, Hyatt, West Tower, Bronze Level
Panelist(s):
Harald Bauder – Ryerson University
Sutapa Chattopadhyay – UNU-Merit & Maastricht University
Pierpaolo Mudu – University of Washington – Tacoma
http://meridian.aag.org/callforpapers/program/SessionDetail.cfm?SessionID=21860

Paper Session: The Role of Geography in Shaping Sustainability Agendas in the Higher Education – session 2
Saturday, 4/25/2015 at 16:00 PM.
Abstract Title: Examining Patterns of Sustainability Across Europe: A Multivariate and Spatial Assessment of 25 Composite Indices
Author(s): Richard Ross Shaker, Ph.D.* – Ryerson University
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=61926

 

About Quick-Service Mapping and Lines in the Sand

A walk on the beach along the still-frozen Georgian Bay has helped me sort some thoughts regarding fast food cartography, quick-service mapping, and naturally occurring vs. artificial lines in the sand … but first things first: This post refers to a debate about Twitter mapping and neo-cartography that is raging on blogs across the planet and will flare up in the Geoweb chat on Twitter this Tuesday, https://twitter.com/hashtag/geowebchat. Update: #geowebchat transcript prepared by Alan McConchie available at http://mappingmashups.net/2015/04/07/geowebchat-transcript-7-april-2015-burger-cartography/.

Lines in the sand (Photos: Claus Rinner)
Lines in the sand (Photos: Claus Rinner)

A few days ago, The Atlantic’s CityLab published an article entitled “Why Most Twitter Maps Can’t Be Trusted”, http://www.citylab.com/housing/2015/03/why-most-twitter-maps-cant-be-trusted/388586/. There have been other cautions that Twitter maps often just show where people live or work – and thus where they tweet. Along similar lines, a comic at xkcd illustrates how heatmaps of anything often just show population concentrations – “The business implications are clear!”, https://xkcd.com/1138/.

The CityLab article incited Andrew Hill, senior scientist at CartoDB and mapping instructor at New York University, to respond with a polemic “In defense of burger cartography”, http://andrewxhill.com/blog/2015/03/28/in-defense-of-burger-cartography/. In it, Hill replies to critics of novel map types by stating “The dogma of cartography is certain to be overturned by new discoveries, preferences, and norms from now until forever.” He likens the good people at CartoDB (an online map service) with some action movie characters who will move cartography beyond its “local optima [sic]”. Hill offers his personal label for the supposedly-new “exploratory playfulness with maps”: burger cartography.

Examples of CartoDB-based tweet maps in the media (Source: Taylor Shelton)
Examples of CartoDB-based tweet maps in the media (Source: Taylor Shelton)

The core portion of Hill’s post argues that CartoDB’s Twitter maps make big numbers such as 32 million tweets understandable, as in the example of an animated map of tweets during the 2014 soccer world cup final. I find nothing wrong with this point, as it does not contradict the cautions against wrong conclusions from Twitter maps. However, the rest of Hill’s post is written in such a derogatory tone that it has drawn a number of well-thought responses from other cartographers:

  • Kenneth Field, Senior Cartographic Product Engineer at Esri and an avid blogger and tweeter of all things cartography, provides a sharp, point-by-point rebuttal of Hill’s post – lamenting the “Needless lines in the sand”, http://cartonerd.blogspot.co.uk/2015/03/needless-lines-in-sand.html. The only point I disagree with is the title, since I think we actually do need some lines in the sand (see below).
  • James Cheshire, Lecturer and geospatial visualization expert at University College London, Department of Geography, supports “Burger Cartography”, http://spatial.ly/2015/03/burger-cartography/, but shows that “Hill’s characterisation of cartography … is just wrong”.
  • Taylor Shelton, “pseudopositivist geographer”, PhD candidate at Clark University, and co-author of the study that triggered this debate, writes “In defense of map critique”, https://medium.com/@kyjts/in-defense-of-map-critique-ddef3d5e87d5. Shelton reveals Hill’s oversimplification by pointing to the need to consider context when interpreting maps, and to the “plenty of other ways that we can make maps of geotagged tweets without just ‘letting the data speak for themselves’.”

Extending the fast food metaphor, CartoDB can be described as a quick-service mapping platform – an amazing one at that, which is very popular with our students (more on that in a future post). I am pretty sure that CartoDB’s designers and developers generally respect cartographic design guidelines, and in fact have benefited commercially from implementing them. However, most of us do not live from fast food (= CartoDB, MapBox, Google Maps) alone. We either cook at home (e.g., R with ggplot2, QGIS; see my previous post on recent Twitter mapping projects by students) or treat ourselves to higher-end cuisine (e.g., ArcMap, MapInfo, MAPublisher), if we can afford it.

I fully expect that new mapping pathways, such as online public access to data and maps, crowdmapping, and cloud-based software-as-a-service, entail novel map uses, to which some existing cartographic principles will not apply. But dear Andrew Hill, this is a natural evolution of cartography, not a “goodbye old world”! Where the established guidelines are not applicable, we will need new ones – surely CartoDB developers and CartoDB users will be at the forefront of making these welcome contributions to cartography.

MacEachren's Some Truth with Maps (Source: Amazon.com)
MacEachren’s Some Truth with Maps (Source: Amazon.com)

While I did not find many naturally occurring lines in the Georgian Bay sand this afternoon, I certainly think society needs to draw lines, including those that distinguish professional expertise from do-it-yourselfism. I trust trained map-makers (such as our Geographic Analysis and Spatial Analysis graduates!) to make maps that work and are as truthful as possible. We have a professional interest in critically assessing developments in GIS and mapping technologies and taking them up where suitable. The lines in the sand will be shifting, but to me they will continue to exist: separating professional and DIY cartographers, mapping for presentation of analysis results vs. exploratory playing with maps, quantitative maps vis-a-vis the map as a story … Of course, lines in the sand are pretty easy to cross, too!

Twitter Analytics Experiments in Geography and Spatial Analysis at Ryerson

In my Master of Spatial Analysis (MSA) course “Cartography and Geographic Visualization” in the Fall 2014 semester, three MSA students experimented with geospatial analysis of tweets. This post provides a brief account of the three student projects and ends with a caution about mapping and spatially analyzing tweets.

Yishi Zhao wrote her “mini research paper” assignment about “Exploring the Thematic Patterns of Twitter Feeds in Toronto: A Spatio-Temporal Approach”. Yishi’s goal was to identify the spatial and thematic patterns of geolocated tweets in Toronto at different times of day, as well as to explore the use of R for spatio-temporal analysis of the Twitter stream. Within the R platform, Yishi used the streamR package to collect geolocated tweets for the City of Toronto and mapped them by ward using a combination of MapTools, GISTools, and QGIS. Additionally, the tm package was used for text mining and to generate word clouds of the most frequent words tweeted at different times of the day.

Toronto tweets per population at different times of day - standard-deviation classification (Source: Yishi Zhao)
Toronto tweets per population at different times of day – standard-deviation classification (Source: Yishi Zhao)
Frequent words in Toronto tweets at different times of day (Source: Yishi Zhao)
Frequent words in Toronto tweets at different times of day (Source: Yishi Zhao)

One general observation is that the spatial distribution of tweets (normalized by residential population) becomes increasingly concentrated in downtown throughout the day, while the set of most frequent words expands (along with the actual volume of tweets, which peaked in the 7pm-9pm period).

MSA student Alexa Hinves pursued a more focused objective indicated in her paper’s title, “Twitter Data Mining with R for Business Analysts”. Her project aimed to examine the potential of geolocated Twitter data towards branding research using the example of singer Taylor Swift’s new album “1989”. Alexa explored the use of both, the streamR and twitteR packages in R. The ggplot2, maps, and wordcloud packages were used for presentation of results.

Distribution of geolocated tweets and word cloud referring to Taylor Swift (Source: Alexa Hinves)
Distribution of geolocated tweets and word cloud referring to Taylor Swift (Source: Alexa Hinves)

Alexa’s map of 1,000 Taylor Swift-related tweets suffers from a challenge that is common to many Twitter maps – they basically show population distribution rather than spatial patterns that are specific to tweet topics or general Twitter use. In this instance, we see the major cities in the United States lighting up. The corresponding word cloud (which I pasted onto the map) led Alexa to speculate that businesses can use location-specific sentiment analysis for targeted advertising, for example in the context of product releases.

The third project was an analysis and map poster on “#TOpoli – Geovisualization of Political Twitter Data in Toronto, Ontario”, completed by MSA cand. Richard Wen. With this project, we turn our interest back to the City of Toronto and to the topic of the October 2014 municipal election. Richard used similar techniques as the other two students to collect geolocated tweets, the number of which he mapped by the 140 City neighbourhoods (normalized by neighbourhood area – “bubble map” at top of poster). Richard then created separate word clouds for the six former municipalities in Toronto and mapped them within those boundaries (map at bottom of poster).

#TOpoli map poster - spatial pattern and contents of tweets in Toronto's mayoral election 2015 (Source: Richard Wen)
#TOpoli map poster – spatial pattern and contents of tweets in Toronto’s mayoral election 2015 (Source: Richard Wen)

Despite the different approach to normalization (normalization by area compared to Yishi’s normalization by population), Richard also finds a concentration of Twitter activity in downtown Toronto. The word clouds contain similar terms, notably the names of the leading candidates, now-mayor John Tory and candidate Doug Ford. An interesting challenge arose in that we cannot tell just from the word count whether tweets with a candidate’s name were written in support or opposition to this candidate.

The three MSA students used the open-ended cartography assignment to acquire expertise in a topic that is “trending” among neo-cartographers. They have already been asked for advice by a graduate student of an environmental studies program contemplating a Twitter sentiment analysis for her Master’s thesis. Richard’s project also led to an ongoing collaboration with journalism and communication researchers. However, the most valuable lesson for the students and myself was an increased awareness of the pitfalls of analyzing and mapping tweets. These pitfalls stem from the selective use of Twitter among population subgroups (e.g., young professionals; globally the English-speaking countries), the small proportion of tweets that have a location attached (less than 1% of all tweets by some accounts), and the limitations imposed by Twitter on the collection of free samples from the Twitter stream.

I have previously discussed some of these data-related issues in a post on “Big Data – Déjà Vu in Geographic Information Science”. An additional discussion of the cartography-related pitfalls of mapping tweets will be the subject of another blog post.

A Raster-Based Game of Life Using Python in QGIS

Blog post authored by Richard Wen and Claus Rinner

A great way to demonstrate the manipulation of geospatial raster data is Conway’s Game of Life [1]. The “game” starts with a grid (“board”) of binary cells, which represent either alive (populated) or dead (empty) states. Each cell interacts with its eight adjacent neighbours to determine its next state. At each iteration of the game clock, the following rules are applied [1]:

  • A live cell with less than two or more than three live neighbours dies (under-population, overcrowding).
  • A live cell with two or three live neighbours continues to live.
  • A dead cell with three live neighbours becomes alive (reproduction).

The free and open-source Geographic Information System (GIS) software package QGIS [2] offers support for scripting with the Python programming language (pyQGIS module), which enables the use of powerful libraries such as NumPy and GDAL for dealing with raster data. Numerical Python (NumPy) [3] is a package developed for Python that is geared towards scientific computation with support for multi-dimensional arrays and matrices. The Geospatial Data Abstraction Library (GDAL) [4] is a library for translating raster and vector geospatial data formats available as a binding for Python.

Using NumPy, GDAL, and pyQGIS, we implemented the Game of Life, where NumPy manipulates the arrays, GDAL handles reading and writing of the raster data, and pyQGIS visualizes the rasters and their relative changes. The source code was written by Master of Spatial Analysis student Richard Wen with input from Dr. Claus Rinner and is available at https://github.com/rwenite/QGIS_RasterArray. The project was inspired by Anita Graser’s visit to Ryerson’s Lab for Geocomputation in October 2014, during which Anita developed a vector-based version of the Game of Life in QGIS (see http://anitagraser.com/2014/11/16/more-experiments-with-game-of-life/).

Our implementation takes an object-oriented approach, in which an object of a Game of Life class is instantiated and the gaming board is updated with the cycle() method using the QGIS python console. The core function is the manipulation of individual raster cells based on a coded algorithm – in this case, the rules defined by the Game of Life.

Let’s start by initializing and cycling a gaming board using default parameters:

# Instantiate a starting board
x = GameofLife()

game-of-life_fig1a

# Cycle the board twice
x.cycle(2)

game-of-life_fig1

The gaming board may be initialized with a random raster, a filled raster, a custom raster, or from a pre-defined raster file:

# The default is a random raster, we can set the width and height as well
x = GameofLife(width=3,height=5)
# Cycle the board
x.cycle()

game-of-life_fig2

# Fill a cells object with 1s
y = Cells(inRaster=1)
# Create a raster with the filled cells object in the directory
y.toRaster("path\\to\\filledraster\\file.tif")
# Instantiate a starting board with the filled raster
x = GameofLife(raster="path\\to\\filledraster\\file.tif")
# Cycle the board
x.cycle()

game-of-life_fig3

# Generate a raster from a list of tuples
y=Cells(inRaster=[
(0,0,0,0,0,0,0,0),
(0,0,0,0,0,0,0,0),
(0,0,1,0,0,1,0,0),
(0,0,0,0,0,0,0,0),
(0,0,1,0,0,1,0,0),
(0,0,0,1,1,0,0,0),
(0,0,0,0,0,0,0,0),
(0,0,0,0,0,0,0,0)])
# Create a raster with the custom cells object in the directory
y.toRaster("path\\to\\customraster\\file.tif")
# Instantiate a starting board with the custom raster
x = GameofLife(raster="path\\to\\customraster\\file.tif")

game-of-life_fig3b

# Instantiate a starting board with a raster
x = GameofLife(raster="path\\to\\raster\\file.tif")

game-of-life_fig4a

Date source: City of Toronto Open Data [5]

Some other interesting features include changing animation speed, jumping cycles, and applying customized layer styles:

# Adjust delay to 3 seconds
x.speed=3
# Cycle 10 times normally
x.cycle(10)
# Cycle 5 times and display every 2nd cycle
x.cycle(5,2)
# Set the style to the defined qml file
x.style = “path\\to\\qml\\style\\file.qml”

This post focuses on the functionality of the program, while its inner workings can be grasped from comments in the Python source code posted at https://github.com/rwenite/QGIS_RasterArray. The code was written and tested for QGIS 2.6; feedback on any issues is most welcome. The use of a NumPy array to iterate through the grid cells was found in an answer by user “gene” on GIS StackExchange [6]. Reading and processing raster data does have its challenges. When dealing with large grids, reading raster data in blocks rather than as a whole is advisable, because there may not be enough RAM to store an entire file at once [7].

The aim of implementing the Game of Life with Python and QGIS is to demonstrate some fundamental concepts of raster data analysis and cellular automata modeling, both of which have important applications in Geography and GIS. Existing QGIS functionality and scripts for raster processing seem to focus more on low-level input/output operations than higher-level analysis functions. For example, we did not find advanced local and focal raster operations in QGIS’ raster calculator. Thus, we envision that the RasterArray code could serve as a basis for expanding raster analysis in QGIS. The code will also be used in a yet-to-be-written lab assignment in GEO641 “GIS and Decision Support” in Ryerson’s BA in Geographic Analysis program.

 

References:

[1] Wikipedia, Conway’s Game of Life
http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life

[2] QGIS
http://www2.qgis.org/en/site/

[3] NumPy, Numerical Python
http://www.numpy.org/

[4] GDAL, Geospatial Data Abstraction Library
http://trac.osgeo.org/gdal/wiki/GdalOgrInPython

[5] Toronto Open Data, Regional Municipal Boundary
http://www.toronto.ca/open

[6] How to do loops on raster cells with python console in QGIS?
http://gis.stackexchange.com/questions/107996/how-to-do-loops-on-raster-cells-with-python-console-in-qgis

[7] Chris Garrard, Utah State University, Reading Raster Data with GDAL
http://www.gis.usu.edu/~chrisg/python/2008/os5_slides.pdf

 

Ryerson Geographic Analysis students put restaurants, airports, cities, and cropland on the map!

Blog post authored by Claus Rinner and Victoria Fast

In response to a recent lab assignment in GEO441 “Geographic information Science”, 49 second-year Geographic Analysis students selected a crowdmapping application and actively contributed valuable geographic information.

The most popular choice was the global OpenStreetMap initiative (http://www.openstreetmap.org). From updating the name and hours of their favourite restaurant or adding their local bank to a plaza, to identifying community gardens, adding a newly built hospital or geocoding new condos, the students used their local knowledge of the GTA to update and expand the freely accessible OpenStreetMap dataset.

sdiz-osm-changeset

For example, second-year Geographic Analysis student Stephanie Dizonno added a restaurant, George’s Pizza, to a set of businesses already represented along Toronto’s Dundas Street East.

ksmith-osm-airportSome of the more unusual edits were made by GEO441 student Kyle Smith, who is a recreational pilot. Kyle corrected and added key features to a local airport, such as a taxiway, the airport restaurant, and the apron, which we learned is the paved area used for aircraft parking. An essential part of his contribution was to update “crucial attribute data about the airport’s characteristics using the Canadian Flight Supplement,” writes Kyle.

In addition to OpenStreetMap, other students elected to contribute to Wikimapia, Cropland Capture, Night Cities, and the David Rumsey Map Collection. For example, instead of the point, line, polygon, and/or attribute data added to OpenStreetMap, the Cropland Capture online game (http://www.geo-wiki.org/games/croplandcapture/) has ‘players’ indicate whether or not a given satellite image includes agricultural land. Mooez Munshi highlights the relevance of his contribution: “The geographic data collected will help in building a map that shows all of the world’s cropland.”

dbocknek-historical-maps-overlay

Geographic Analysis student Daniel Bocknek elected to geographically reference a 100-year old map from the David Rumsey Map Collection (http://www.davidrumsey.com/view/georeferencer) showing the Aberfoyle area in Scotland. After identifying at least three control points on both the historic map and a contemporary basemap such as OpenStreetMap or Google Maps, the historic map is automatically geo-referenced and can be integrated with other GIS data as shown in Daniel’s screenshot above.

A similar approach is used by the Night Cities application (http://crowdcrafting.org/app/nightcitiesiss/) to geo-locate photographs of world cities taken at night by astronauts on board the ISS. In his GEO441 assignment, Navdeep Salooja explains that this project involves “citizen scientists”, like himself, in research about global night-time light pollution.

Overall, the 49 Ryerson students contributed important bits (and bytes) to the growing body of volunteered geographic information, while experiencing the broad applicability of geographic knowledge and principles of geographic information science to real-world issues.

Thought Spot – Crowdmapping of Mental Health and Wellness Resources

Thought Spot is a project designed by post-secondary students to support mental health and wellbeing among Toronto-area youth. The main feature is the online map at http://mythoughtspot.ca/, which is based on the Ushahidi crowdsourced mapping platform. The Thought Spot project was initiated at the Centre for Addiction and Mental Health (CAMH), in collaboration with the University of Toronto, OCAD, and Ryerson. The map allows students to find mental health and wellness resources in ­their geographic area, without the need for an intermediary (parent, teacher, physician). The mapped information originates from ConnexOntario and Kids Help Phone data as well as data that were crowdsourced from members of the target audience.

thoughspot-screenshot

Ryerson Master of Spatial Analysis (MSA) candidate Heather Hart took a lead role in designing the Thought Spot map (shown above), bringing unique geospatial expertise to the table of the project’s student advisory board. Through her MSA practicum placement with a different research group at CAMH, Heather got in contact with the Thought Spot team and brought the funding for her own summer position to Ryerson, to devote half of her time to ensuring that the project’s crowdmapping would be successful. Heather’s involvement culminated in co-organizing a Thought Spot hackathon at Ryerson’s Digital Media Zone in October 2014, which led to the ongoing development of a mobile version of the Thought Spot map.

photo-thoughtspot-heather

This photo shows Heather at GIS Day at Ryerson on November 19th, 2014, presenting the Thought Spot project to an interested University audience. In collaboration with Environmental Applied Science and Management PhD candidate Victoria Fast, Heather has now also submitted a conference abstract about “Crowd mapping mental health promotion through the Thought Spot project”. The abstract brings together Victoria’s extensive expertise in volunteered geographic information systems and Heather’s on-the-ground experience with the Thought Spot project. Their presentation at the annual meeting of the Association of American Geographers in April 2015 is part of the “International Geospatial Health Research” theme.

It is wonderful to see two enterprising Geography graduate students contribute to supporting mental health and wellbeing on campus, a goal that the University is committed to. At the same time, the Thought Spot project informs Heather’s thesis research on the role of maps in evidence-based health care decision-making and Victoria’s dissertation on crowdmapping of local food resources.

Thirty-Two Thousand One Hundred Eighty-Nine Points and Counting

In another little mapping experiment with QGIS and open data from the City of Toronto, I visualized the 32,189 locations of [type-of-incident-withheld] that were recorded in Toronto from 1990 to 2013. I put out a little quiz about this map on Twitter, so I will only reveal what the points represent towards the end of this post. However, the dataset is readily available from Toronto’s open data catalog, both in tabular and GIS-ready Shapefile format.

According to a report by Global News, City crews on occasion have to deal with 20-25 of these incidents a day. As part of their data journalism, Global News created a hexagonal heatmap of the 1990-2013 data, see their article [type of incident will be disclosed].

In contrast, I mapped each point individually using lighter shades of blue for more recent years. While it is often recommended to use the darker and/or more saturated end of a colour scheme for the more important values (arguably the more recent incidents), with the ever more popular black map background, this approach is inverted: the lighter symbols will create the greater contrast, and thus appropriately represent the more important, often the larger, values. The boundaries shown in the background are City wards.

blue-dots-across-toronto_96dpi

As I finish teaching GEO241, our 2nd-year Cartography course in the BA in Geographic Analysis program, I am still having trouble identifying the thematic map type implemented here. It is not a dot density map, as a dot density map uses a unit value (could be seen as 1 dot = 1 incident) and places dots within the area for which the data were collected, but not at the exact location of occurrence. The same reasoning applies to Dr. John Snow’s map of cholera death in London 1854, which is not a dot (density) map either.

Instead, I think this map can be considered a proportional symbol map, where the point symbols at real point locations — not conceptual points such as Census tract centroids — are defined in proportion to a variable (BREAK_YEAR), yet not in terms of their size but in terms of their lightness. Clicking on the above teaser will open the full map with the title Water Main Breaks, City of Toronto, 1990-2013. So yes, there were a whopping 32,189 water main breaks in the City of Toronto during those 24 years! This situation is expected to worsen with the aging municipal infrastructure, see for example the Toronto Star’s 2010 article with a map showing downtown water mains built pre-1900. And it is not a new phenomenon either, as shown by this lovely photograph from the City of Toronto Archives (Fonds 200, Series 372, Subseries 72, Item 31), dated May 3, 1911:

Fonds 200, Series 372, Subseries 72 - Toronto Water Works photog

Guest lecture on Dynamic Transportation Systems, OpenStreetMap, and QGIS

The Department of Geography and Environmental Studies and the Centre for Geocomputation at Ryerson University welcome Anita Graser, MSc, Scientist at the Austrian Institute of Technology (AIT), Mobility Department – Dynamic Transportation Systems, for the following guest lecture.

Title: GIScience for Dynamic Transportation Systems
Date: Friday, 31 October 2014, 10am-12noon
Location: Room JOR-440, 4th floor, Jorgenson Hall, 380 Victoria Street, Toronto

Abstract

Anita Graser (@underdarkGIS) is a scientist, open source GIS advocate, and author of “Learning QGIS 2.0”. In this presentation, Anita will give an overview of her work at the AIT and in the QGIS project, where she is currently serving on the project steering committee. The talk covers measuring, analyzing, visualizing, and understanding mobility data. These topics will be discussed in the context of Anita’s recent work such as analyses of floating car data and assessments of OpenStreetMap for vehicle routing purposes.