Claus Rinner – Page 5 – GIS2 at Toronto Metropolitan University

10 December 2014

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.

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.

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.

6 December 20146 December 2014

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.

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:

27 October 201417 December 2015

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.

30 May 201430 May 2014

Toronto’s Traffic Lights Re-Visited and Animated

My map of Toronto’s traffic signals described in a post on April 4th, 2014, was recently published on the title page of Cartouche, the newsletter of the Canadian Cartographic Association (CCA). This is my first-ever published map that is stand-alone, not included in an article or other text document! Here is a screenshot of the newsletter title:

Motivated by this unexpected outcome and using the occasion of the launch event of Maptime Toronto on May 29th, 2014, I wanted to try animating the dots representing the traffic signals. More precisely, each traffic light should iterate through a green-yellow-red sequence, and each mid-block pedestrian crossing should go through an off-blinking-off sequence. I was aiming for an animated GIF image with ten frames displayed in a continuous loop.

To create the colour sequences for each dot in QGIS, I copied the last digit of an existing feature ID from the City of Toronto traffic signals data table into a new field to act as a random group assignment. Using a suggestion by Michael Markieta, I then created nine additional integer fields and cycled through the group numbers by adding 1. To keep these numbers in the 0…9 range, I used QGIS’ “modulo” function, e.g. Cycle1 = (“Cycle2” + 1) % 10. I then assigned the green, yellow, and red dot symbols from the static traffic lights map as a categorized “style” to different group numbers. Finally, I manually iterated the symbology through the ten group columns and took a screenshot each time. I put these together in the animated GIF shown below.

I must admit that I am not super convinced of the outcome. Maybe, ten frames are not enough to overcome the clocked appearance of the traffic signal system. But at least, things are moving now :)

It is important to note that this animation does not show the real-time status of the traffic lights! In fact, there is only one dot for an entire intersection that would include two to four sets of vehicle traffic lights, plus pedestrian lights, etc. – all represented by the same green-yellow-red cycle on the map. I also made the assumption that the green and red phases are the same length (4 out of 10 ticks each, with the remaining 2 ticks used for the yellow phase). You will note that the mid-block crossings have an active phase with three on-off cycles followed by a longer off phase. In this case, it would be fancier to individually control each crossing and have it come on randomly.

29 May 2014

Big Data – Déjà Vu in Geographic Information Science

A couple of years ago, one of my first blog posts here was a brief note on “Trends in GIScience: Big Data”. Although not at the core of my research interests, the discussions and developments around big data continue to influence my work. In an analysis of “The Pathologies of Big Data”, Adam Jacobs notes that “What makes most big data big is repeated observations over time and/or space”. Indeed, Geographic Information Systems (GIS) researchers and professionals have been working with large datasets for decades. During my PhD in the late 1990s, the proceedings of the “Very Large Data Bases” (VLDB) conference series were a relevant resource. I am not sure what distinguishes big data from large data, though I don’t have the space nor time to discuss this further.

Instead, I want to draw a first link between big data and my research on geovisual analytics. In an essay on “The End of Theory”, Chris Anderson famously argued that with sufficiently large data volumes, the “numbers [would] speak for themselves”. As researchers, we know that data are a rather passive species and the most difficult stage in many research projects is to determine the right questions to ask of your data, or to guide the collection of data to begin with. The more elaborate critiques of the big data religion include a recent article by Tim Harford on “Big data: are we making a big mistake?” Harford points to the flawed assumption that n=all in big data collection (not everybody tweets, has a smartphone, or even a credit card!) and argues that we are at risk of repeating statistical mistakes, only at the larger scale of big data. Harford also characterizes some big data as “found data” from the “digital exhaust” of people’s activities, such as Web searches. This makes me worried about the polluted analyses that will be based on such data!

On a more positive note, cartographers have argued for using interactive visualization as a means to analyse complex spatial datasets. For example, Alan MacEachren’s 1994 map use cube defines geovisualization as the expert use of highly interactive maps to discover unknown spatial patterns. On this basis, I understand geovisual analytics as an efficient and effective approach to “making the data speak”. For example, in Rinner & Taranu (2006) we concluded that “an interactive mapping tool is worth a thousand numbers” (p. 647), which may actually underestimate the potential of map-based data exploration. Along similar lines, I noted in Rinner (2007) that data (read: small data) can quickly become complex (read: big data), when they are subject to analytical processing. For example, in a composite index created from a few indicators for the 140 social planning neighbourhoods in the Wellbeing Toronto tool, changes in the indicator set, weights assigned to indicators, and normalization and standardization applied, will create an exponentially growing set of potential indices. The interactive, geovisual nature of the tool will help analysts to draw reasonable conclusions for decision-makers.

A second link exists between big data and my research on the participatory Geoweb. In this research, we examine how the Geoweb is changing interactions between government and citizens. On the one hand, government data are being released in open data catalogues for all to enjoy – i.e., use for scrutinizing public service, developing value-added products or services, or just to play with cool map and app designs. On the other hand, governments start to rely on crowdsourcing to fill gaps in data where shrinking budgets are limiting authoritative data collection and maintenance. In this context of “volunteered geographic information” (VGI), we argue that we need to consider the entire VGI system, including the hardware and software, user-generated data, and the application and people involved, in order to fully understand the emerging phenomenon. We also took up the study of different types of VGI, such as facilitated VGI in contrast to ambient VGI. Of these two types, ambient or “involuntary” VGI is connected with big data and the “digital exhaust” discussed above, as it consists of information collected from large numbers of users without their knowledge.

Again, geographers are in a strong position to examine big data resulting from ambient VGI, as location plays a major role in the VGI system. The 2014 annual meeting of the Association of American Geographers (AAG) included a high-profile panel on big data, their impact on real people, asymmetries in location privacy, and the role of “big money” in big data analytics. In contrast to previous discourse, in which geographers often limited themselves to deploring the disconnect between the social sciences and the developments in computer science and information technology, at AAG 2014 a tendency to more confident commentary and critique of big data and other unreflected IT developments was tangible. We need to understand the societal risks of global data collection and (geo)surveillance, and explain why if you let the data speak for themselves, you may earn a Big Silence or make bad decisions.

Both, my research on Wellbeing Toronto and place-specific policy-making as well as the Geothink partnership studying the Geoweb and government-citizen interactions are funded by the Social Sciences and Humanities Research Council of Canada (SSHRC). While supporting research into the opportunities provided by big data, I think that SSHRC is best positioned among the granting councils to also fund critical research on the risks and side effects of big data.

21 May 201417 December 2015

Ryerson Geographers at the Upcoming CAG Meeting

Guest post by Dr. K. Wayne Forsythe:

The Canadian Association of Geographers (CAG) 2014 Annual Meeting will be held at Brock University from May 26-30. It is part of the larger 2014 Congress of the Humanities and Social Sciences.

A number of Ryerson Geographers are taking part. The papers and sessions are as follows:

1) TUE-08:30 POSTER SESSION – Physical Geography, Environmental Geography, Climate Change (Mackenzie Chown Complex C407). Posters will be displayed all day.

K. Wayne Forsythe, Meghan McHenry, Stephen J. Swales, Joseph M. Aversa, Daniel J. Jakubek, Ryerson University.
Bathymetric Visualization of Contaminated Sediments in Lake Ontario

2) TUE-13:30 Geographies of Health and Wellbeing I (Mackenzie Chown Complex D400).
Chair: Gavin J. Andrews, McMaster University

Eric Vaz, Ryerson University; Michael Cusimano, University of Toronto; Tony Hernandez, Ryerson University.
Spatial heterogeneity of self-reported health in Toronto: Exploratory analysis of anthropogenic land use phenotypes

3) TUE-15:30 Geographies of Health and Wellbeing II (Mackenzie Chown Complex D400).
Chair: Allison Williams, McMaster University

Peter Kedron, Rajiv Lalla, Adam Mckay, Ryerson University
A Study of Within Group Inequality in the Geographic Distribution of HIV/AIDS in Thailand

4) WED-10:30 Selling the City (Mackenzie Chown Complex D400).
Chair: Phillip Gordon Mackintosh, Brock University

Chris Daniel, Tony Hernandez, Ryerson University
Scale effects on retail co-location analysis

5) WED-13:30 Critical Legal Geographies (Mackenzie Chown Complex D303).
Sponsorship: Indigenous Peoples Working Group; Historical Geography Study Group; Social Justice Research Institute (SJRI), Brock University
Special Session Organizers: Vanessa Sloan Morgan, Dalhousie University; Laura Schaefli,
Queen’s University
Chair: Vanessa Sloan Morgan, Dalhousie University

Valentina Capurri, Ryerson University
The Chester Case: the Canadian Immigration Act and the interconnections between law and spatiality in the lives of immigrant applicants with disabilities

6) WED-15:30 Possibilities and Limits of Scholarly Activism In and Outside of the Classroom II: How to Bring Academy to Activism (Mackenzie Chown Complex C405).
Sponsorship: Social Justice Research Institute (SJRI), Brock University
Special Session Organizers: Ebru Ustundag, Brock University; Emily Eaton, University of Regina
Moderator: Ebru Ustundag, Brock University
Panelists:
Fran Klodawsky, Carleton University
Valentina Capurri, Ryerson University
Vanessa Sloan Morgan, Dalhousie University
Emily Eaton, University of Regina

7) THU-10:30 Urban Inequalities in Canadian and US Cities – Exploring the Interconnections among Housing, Food Insecurity, and Environmental Justice I: Exploring the Links Between Housing and Food Security (Mackenzie Chown Complex C405).
Sponsorship: Social Justice Research Institute (SJRI), Brock University
Special Session Organizers: Sutama Ghosh, Peter Kedron, Ryerson University
Chair: Peter Kedron, Ryerson University

Brian Ceh, Tony Hernandez, Ryerson University
Measuring food deserts and implications of local, independently-owned grocers on the food landscape: The case of Toronto, Ontario

Discussant: Sutama Ghosh, Ryerson University

8) THU-13:30 Urban Inequalities in Canadian and US Cities – Exploring the Interconnections among Housing, Food Insecurity, and Environmental Justice II: ‘Mapping’ Links Between Housing and Environmental Justice (Mackenzie Chown Complex C405)
Special Session Organizers: Sutama Ghosh, Peter Kedron, Ryerson University
Chair: Sutama Ghosh, Ryerson University

Victoria Fast, Ryerson University
Building collaboration into the Food Security Equation: Participatory Mapping of Local Food Systems using Volunteered Geographic Information (VGI)

Heather Hart, Peter Kedron, Ryerson University
Understanding the statistical bias of geographic scale in environmental inequity research

Cosmin Marmureanu, Ryerson University
Poverty, Housing, and Urban Forestry: Interrogating Intertwined Social and Environmental Justice in Toronto’s Inner Suburbs

Discussant: Peter Kedron, Ryerson University

9) FRI-15:30 Thinking About Learning (Mackenzie Chown Complex C407)
Chair: Dragos Simandan, Brock University

Rajiv Lalla, Ryerson University
Proximity to LGBT Social Resources as a proxy for defining Queer Communities in Ontario: A GIS Perspective

The presentations span the breadth of Geography, Environmental Studies and GIScience, and involve students/alumni from the Geographic Analysis and Master of Spatial Analysis (MSA) programs, in addition to students in the MAsc and PhD in Environmental Applied Science and Management. See you in St. Catharines!

K. Wayne Forsythe Ph.D.
Professor, Program in Geographic Analysis, Graduate Program in Spatial Analysis, and President, Canadian Association of Geographers – Ontario Division (CAGONT)
Department of Geography, Ryerson University, 350 Victoria Street
Toronto, Ontario, CANADA M5B 2K3

http://www.geography.ryerson.ca/wayne/forsythe.htm

4 April 201410 April 2014

Infomap or Cartographic? My Take on Mapping Toronto’s Traffic Lights

Toronto writer/blogger Chris Bateman recently publicized a beautiful white-on-black map of all Toronto traffic lights, which was created by our very own Master of Spatial Analysis (MSA) student William Davis. Chris’ brief yet insightful post on blogTO can be found at http://www.blogto.com/city/2014/03/a_map_of_every_traffic_signal_in_toronto/. Inspired by William’s idea and the creative map designs by several MSA students in my cartography course in the fall semester, I thought I’d give the traffic lights map a try. Another trigger for my experiment was a comment from blogTO reader “Red Menace” about the traffic lights, complaining that “Most of them are red too.” Here is how I proceeded:

Visit the City of Toronto’s open data catalogue, click on “GET THE DATA”, and find “Traffic Signals Tabular”. I would love to provide a direct link, but they changed URLs to include some lengthy session IDs, which I cannot post here – currently, http://toronto.ca/open still works as an entry point.
Download “All traffic signals – CSV”, “Traffic signals with APS – CSV”, and “Pedestrian crossovers – CSV”. According to the readme file, APS refers to “active traffic signal enabled with sound (Accessible Pedestrian Signals)”. CSV is a tabular file format (Comma-Separated Values).
Start the open-source geographic information system QGIS 2.2. In the Layer menu, use “Add Delimited Text Layer…” to open each of the three CSV files, discarding the first line and assigning the Longitude and Latitude fields to the x and y coordinates respectively.
Upon preliminary display, change the coordinate reference system of the QGIS project to UTM Zone 17N and display all traffic signals as red dots, pedestrian crossovers as yellow dots, and sound-enabled signals as green dots.
In QGIS’ print composer, add new map, rotate by +18 degrees, set background to black, and fiddle with map extent and scale until everything fits. Then export as image, et voila!

Click image to open larger version.
Contains information licensed under the Open Government Licence – Toronto.

With red dots representing “normal” traffic lights, green dots overlaying those lights that are friendly to visually impaired pedestrians, and yellow dots showing the locations of mid-block crosswalks, my map focuses a bit more on conveying thematic information than on a fashionable graphic design. While I am afraid that design gurus (in particular our trend-setting students!) may sniff at it, I like to think of it as an “infomap” or “cartographic” (read: carto-graphic), analogous to the now ubiquitous “infographic”.

Update 10 April 2014: I want to share another version, in which I created a halo around the red and yellow dots by defining a semi-transparent, 1mm wide outline of the same colour.

Click image to open full version.
Contains information licensed under the Open Government Licence – Toronto.

31 March 20144 April 2014

Ryerson Geographers gearing up for Tampa

A record number of Geography faculty and graduate students are going to attend the Association of American Geographers (AAG) annual meeting 2014 in Tampa, Florida, next week. Here is the line-up of our research presentations (alphabetically by presenting author):

David M Atkinson*, Paul Treitz, Neal Scott
Modelling Biophysical Variables and Carbon Dioxide Exchange in Canadian Arctic Tundra Landscapes Using Remote Sensing Data
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=59749
Harald Bauder*
Possibilities of Open Borders and No Border
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=55376
Brian Ceh*, Tony Hernandez
A New Urbanism: Evidence from Canadian Cities
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=57532
Victoria Fast*
Building a Virtual Climate Change Adaptation Community to Promote Urban Agriculture Initiatives
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=56481
Wayne Forsythe*, Meghan McHenry, David M Atkinson, Joseph M Aversa, Stephen J Swales, Peter Kedron, Daniel J Jakubek
Utilizing Bathymetry Data for the Geovisualization of Contaminated Sediment Patterns in the Laurentian Great Lakes of North America
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=57372
Christopher S. Greene*, Andrew A Millward
Quality or quantity? Investigating the role of tree canopy density to moderate temperature in the urban microclimate
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=57624
Mary Grunstra*, Brian Ceh, Eric Vaz
Spatial Distribution of Disinfection Byproducts in Drinking Water: Case of Ontario, Canada
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=57534
Claus Rinner, Heather Ann Hart*, Suzanne Kershaw, Cara Mirabelli, Elizabeth Lin, Alexia Jaouich
The Role of Maps in Mental Health Care System Improvement and Policy Input
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=57391
Tony Hernandez*, Maurice Yeates
E-Retail and the Future of the Canadian Mall
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=58108
Peter Kedron*
Firm Value-Chain Reorganization, Regional Industrial Transformation, and the Geography of Innovation in the Canadian Biofuel Industry
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=55919
Bradley D Macpherson*
A Web-based Visualization of Weighted Centrality Scores Using TileMill and MapBox
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=57835
Claus Rinner, Michael Markieta*, Kruti Desai, Marcy Burchfield, Rian Allen
Widgets for Wicked Problems: The Neptis Geoweb Tool and Datasets
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=57390
Colleen Middleton*, Stephen Swales, Wayne Forsythe
The Use of Geographical Information System (GIS) Analysis to Delimit a Protected Area for the Old-Growth Red Pine Forest in Wolf Lake, Temagami, Ontario, Canada
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=59344
Andrew Allan Millward*, Michelle Blake
The Potential for Perennial Vines to Mitigate Summer Warming of an Urban Microclimate
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=57207
Claus Rinner*, Duncan MacLellan, Krista Heinrich, Kathryn Barber
Place-Based Policy-Making with Area-Based Composite Indices – Conceptual Challenges and Community Uptake of “Wellbeing Toronto”
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=57736
Vadim Sabetski*, Andrew Millward
Virtual Daylighting: Documenting Urban Tree Root Locations Using Ground-Penetrating Radar (GPR)
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=57576
James W. N. Steenberg*, Andrew A. Millward
Urban Forest Ecosystem Classification using City Neighborhoods
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=57176
Stephen Swales*, K. Wayne Forsythe
Evaluation of the Geography of Demand in Canada Using Diverse Data Sources
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=58362
Eric Vaz*, Brian Ceh
A Spatial Analysis of the influence of urban centrality for the business landscape of Mumbai, India
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=57057
Lu Wang*
Exploring ethnic variations in healthcare access in Canada: a comparison among multiple ethnic groups
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=59028
Shuguang Wang*, Tony Hernandez
Conceptualizing Ethnic Retailing
http://meridian.aag.org/callforpapers/program/AbstractDetail.cfm?AbstractID=55980

The presentations span the breadth of Geography, Environmental Studies, and GIScience, and involve students and alumni from the Master of Spatial Analysis (MSA), MAsc and PhD in Environmental Applied Science and Management, and PhD in Policy Studies. We are looking forward to meeting geographers from around the globe in Tampa!

30 November 201317 December 2015

Normalization vs. Standardization – Clarification (?) of Key Geospatial Data Processing Terminology using the Example of Toronto Neighbourhood Wellbeing Indicators

In geospatial data processing, the terms “normalization” and “standardization” are used interchangeably by some researchers, practitioner, and software vendors, while others are adamant about the differences in the underlying concepts.

Krista Heinrich, newly minted Master of Spatial Analysis (MSA) and a GIS Analyst at Esri Canada, wrote her MSA major research paper on the impact of variable normalization and standardization on neighbourhood wellbeing scores in Toronto. More specifically, within a SSHRC-funded research project on multi-criteria decision analysis and place-based policy-making, we examined the use of raw-count vs. normalized variables in the City of Toronto’s “Wellbeing Toronto” online tool. And, we explored options to standardize wellbeing indicators across time. Here is what Krista wrote about these issues in a draft of her paper:

In most analysis situations involving multiple data types, raw data exist in a variety of formats and measures, be it monetary value, percentages, or ordered rankings. This in turn presents a problem of comparability and leads to the requirement of standardization. While Böhringer, & Jochem (2007), emphasize that there is no finite set of rules for the standardization of variables in a composite index, Andrienko & Andrienko (2006) state that the standardization of values is a requirement.

Several standardization techniques exist including linear scale transformations, goal standardization, non-linear scale transformations, interval standardization, distance to reference, above and below the mean, z scores, percentage of annual differences, and cyclical indicators (Dorini et al, 2011; Giovanni, 2008; Nardo et al., 2005; Malczewski, 1999). It should be noted however, that there is inconsistency among scholars as to the use of terms such as normalization and standardization.

While Giovannini (2008) and Nardo et al. (2005) categorize standardization solely as the use of z-scores, they employ the term normalization to suggest the transformation of multiple variables to a single comparable scale. Additionally, Ebert & Welsch (2004) refer to Z score standardization as the definition of standardization and place this method, along with the conversion of data to a 0 to 1 scale, referred to as ‘ranging’, as the two most prominent processes of normalization. According to Ebert & Welsch (2004), “Normalization is in most cases a linear transformation of the crude data, involving the two elementary operations of translation and expansion.” In contrast, other scholars classify the transformation of raw values to a single standardized range, often 0.0-1.0, as standardization (Young et al., 2010A; Malczewski, 1999; Voogd, 1983) while Dailey (2006), in an article for ArcUser Online, refers to the normalization of data in ArcMap as the process of standardizing a numerator against a denominator field. […]

In this paper, we employed the term standardization to define the classification of raw values into a single standardized scale and in particular, through the examination of linear scale transformations and their comparison with Z score standardization. The term normalization is used in this paper to describe the division of variables by either area or population, as is referred to by Dailey (2006), therefore regularizing the effect that the number of individuals or the size of an area may have on the raw count values in an area. “

In other words, the way we use the two terms, and the way we think they should be used in the context of spatial multi-criteria decision analysis and area-based composite indices, standardization refers to making the values of several variables (indicators, criteria) comparable by transforming them to the same range of, e.g., 0-to-1. In contrast, normalization refers to the division of a raw-count variable by a reference variable, to account for different sizes of enumeration areas.

Unfortunately, I have to admit that in my cartography course, following the excellent textbook by Slocum et al. (2009), I am using the term “standardization” for the important concept of accounting for unit sizes. For example, choropleth maps should only be made for standardized (i.e., normalized!) variables, never for raw-count data (a great rationale for which is provided at http://www.gsd.harvard.edu/gis/manual/normalize/). Furthermore, high-scoring blog posts at http://www.dataminingblog.com/standardization-vs-normalization/ and http://www.benetzkorn.com/2011/11/data-normalization-and-standardization/ define normalization as the rescaling to the 0-to-1 range (our definition of standardization) and standardization as the z-score transformation of a variable. Oops, did I promise clarification of these terms ?-)

In case you are wondering about Krista’s results regarding the Wellbeing Toronto tool: It depends! She discusses an example of a variable where normalization changes the spatial patterns dramatically, while in another example, spatial patterns remain very similar between raw-count and normalized variables. Standardization was used to make wellbeing indicators from 2008 comparable to those from 2011, as we will report at the Association of American Geographers (AAG) annual meeting in April 2014. Our abstract (URL to be added when available) was co-authored by Dr. Duncan MacLellan (Ryerson, Politics and Public Admin department), my co-investigator on the above-mentioned research grant, and Kathryn Barber, a student in Ryerson’s PhD in Policy Studies program.

21 September 2013

Research Plans for GeoThink Theme 4: “Open Everything”

I wrote the following blog post for the Web site of our 2013-2018 SSHRC Partnership Grant on “How the Geospatial Web 2.0 is Reshaping Government-Citizen Interactions”, also known as “GeoThink”. The post first appeared at http://geothink.ca/open-everything/.

Hello, I am Dr. Claus Rinner, an Associate Professor in the Department of Geography and program director of the Master of Spatial Analysis (MSA) at Ryerson University. My research focuses on the decision support function of maps and geographic information systems (GIS), and the underlying concepts of cartography, geovisualization, public participation, and multi-criteria decision analysis. I plan to contribute to the GeoThink research partnership through students at all levels of study.

Edgar Baculi, a second-year undergraduate student in Ryersons BA in Geographic Analysis, is co-funded by Geothink and the Ontario work-study program. Edgar started an exploration of the City of Toronto’s open data portal, toronto.ca/open, with attention to the data formats and data types available for download. He found that 91 of Toronto’s 133 open datasets have a geospatial component. About one half of these are available in ESRI’s shapefile format. Edgar plans to extend his contents analysis to the open data catalogues of other municipal partners of GeoThink. This complements a planned longitudinal survey of municipal open data initiatives by two other GeoThink researchers, Dr. Peter Johnson and Dr. Pamela Robinson, within Theme 4. Edgar will also start to examine the demand side of open data in terms of their use by local journalists in news reporting and by Ryerson professors in Geography classes and GIS labs.

Together with Dr. Pamela Robinson of Ryerson’s School of Urban and Regional Planning, I am also collaborating with the Neptis Foundation, a key GeoThink partner. With funding from Neptis, incoming MSA student Michael Markieta has upgraded and installed the Neptis Geoweb tool on a Ryerson server for use in research and by other GeoThink partners. The tool includes a mapping interface with a rich collection of datasets for the Toronto region, including a settlement development layer that Neptis combined from the individual land-use plans of dozens of Ontario municipalities. The tool also includes a discussion forum, and Michael’s Master’s research will examine the analytical and decision support function of such participatory Geoweb tools.

My PhD student Victoria Fast will also be involved in the GeoThink project. Victoria recently presented a novel framework for understanding volunteered geographic information (VGI) through a “systems perspective” (http://digitalcommons.ryerson.ca/geography/47/). On this basis and a survey of existing VGI projects, Victoria wants to outline a path for effective deployment of the Neptis Geoweb tool in climate change adaptation planning, an important consideration for municipalities and regions worldwide.

If you would like to participate in research around mapping tools for land use planning and decision support, open data formats, implications of participatory mapping for news media, or tools for urban and regional climate change adaptation, please contact me at crinner at ryerson dot ca.