Est-ce qu'il fait beau dans le métro? ("Is it nice in the metro?") is a participatory planning study I worked on with two classmates. Inspired by a similar effort in San Francisco, we surveyed 50 random Montrealers and asked them to draw their fantasy metro expansions on a map, by marking the locations of ten new stations they would have built.
(The title is a homage to a delightfully retro transit ad campaign from 1976.)
Our goals were to determine to what extent official visions for the future of the city's rapid transit network aligned with the views of its citizens, and how are these views are determined. I was responsible for plotting and analyzing the results in GIS, and writing the final report.
Scanned example of a paper survey
All points digitized in GIS
In total, I digitized 500 points based on the paper maps we used to conduct the survey, and generated a heat map indicating point density; or in other words, where public demand for new metro service is greatest.
We concluded that there is overlap between public demand and current plans, particularly on the eastern Blue Line extension to Anjou). However, other areas of high demand (such as an extension of the western Orange Line to Bois-Franc) are not government priorities, demonstrating that people are capable of thinking about urban issues independent of official discourses.
Number of participants by FSA (green = 1, yellow = 2, red = 3)
The final heat map comparing public demand to planned expansions (shown as dashed lines)
Furthermore, since we collected the first three characters of participants' home postal codes (known as FSAs), I could calculate how statistically correlated people's responses were to the area they lived in, assuming that most would be motivated by self-interest.
In GIS, I created a hub-and-spoke network between every marked station point and the centre of every FSA, and ran a T-test to see if the average distance between someone's home FSA and their preferred station locations (denoted as 'FSA-linked points') was significantly different from the average distance between all station locations and all FSAs ('all points').
Sample means (μ), standard deviations (σ), and sizes (n)
The equations for a T-test and 95% confidence interval
The results of this test were favourable, and we concluded with 95% confidence that the mean distance between stations and their respondent's associated FSA was between 0.29 and 1.13 km shorter than the mean distance between those stations and all FSAs.
In practical terms, though, this was less of a difference than we had anticipated. It reinforced our qualitative conclusion that Montrealers are critically engaged with the whole of their surroundings, and there is value in adding a participatory framework to the urban planning process.