This project has culminated in my formal introductory GIS training. Our group analyzed gentrification in Toronto, by looking at social and economic changes that have happened in the city over the past decade of censuses (2006 and 2016). To really hone in on the differences we decided to look at Old Toronto (the original city boundaries) to see how the urban core of the city had changed. Our goal was to try and answer “How has Old Toronto experienced gentrification through economic and demographic shifts from 2006 to 2016?” through the comparison of median incomes, average rents, and percentage of minority groups in the city between censuses.

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Link to the full report

Because it is not an easy task and required the creation of not just three, but six maps, we organized our team through a series or topic of the map. I focused on demography, analyzing the percentage of minorities in the city over time, and my other members looked at the different economic factors as well. There was a considerable amount of prep work required to gather the data as it needed lots of city and census data to compile. Before any analysis, we had to clip all of our information to Old Toronto, as most datasets either had the whole city, or the entire census metropolitan area.

I learned a lot in the process of this project. I first learned to be very diligent about sorting through your data, or you might be caught up retracing past steps. As well, I was able to use QGIS for the first time to compile my map, which was a great experience and I enjoyed the flexibility with the layout options compared to ArcMap. The only issue with this was trying to make my maps as similar to my project members, which was a little time-consuming. Originally we had a larger scope of the project, incorporating a wildcard factor of gentrification: Starbucks locations. This proved to be of little use to us as the data was relatively static (it is very hard to find a database of Starbucks that shows the different opening dates of locations), and we wouldn’t be able to do diligence in comparing our other census gathered data. In the end, it was a great learning experience and is directly tied to my planning aspirations.

In Summary:

• I learned how to work with a team on a GIS project, including delegating specific tasks for a more efficient workflow.
• We were able to compile and synthesize multiple sources of data through an extensive process of clipping and joining information from tabular to spatial data.
• We were able to present and articulate our findings in a formal report.