Aaron Licker posted these maps, showing where each party got their votes. Click here for a closer look.
The map on the lower right showing the leading vote-getters (Sim, Kennedy and Sylvester) interested me the most. It looks pretty close to the results I remember in the elections from the 1990s, with the NPA majorities coming not just from the west side but also the southeast quadrant.
In fact, if there was a dividing line between the right and left, it wasn’t Main Street (or Cambie or Ontario, depending on your definition.)
It was Kingsway.
Maps based on land area are hard to interpret when population density varies a lot. I’d love to see these maps re-done with absolute vote numbers rather than percentages. For instance, are there a lot of voters in Stanley Park? It’s shaded just like the West End. Not many voters living on golf courses, either. I suspect it’d be better to populate the map with dots, one per 1,000 votes, colour-coded per candidate. That would convey the candidates’ varying fortunes in different areas, and also show where the voters are really concentrated.
Hi Dominic, here are two for you:
Population Density and Council Placements
https://twitter.com/LGeospatial/status/1062120317408043008
and
Dot density…
https://twitter.com/LGeospatial/status/1061766325876383746
Yep. Environment influencing politics.
Kennedy Stewart’s map is the inverse of Ken Sim’s.
What’s ironic is that the area that Coalition Vancouver did best in (E and SE) is the area that’s the easiest to drive in yet their platform was from the stance of “the poor oppressed motorist”. Clearly they need more alternative transportation in that area.
Would be interesting to have layers of detail – perhaps ribbons of texture versus solid colors – which can be used to show patterns of Civic, provincial and federal voters concentrations. Some techie must know how – plus then do options of each with census layer of age, gender, income, even language or faith? The 3-d movie makers may have a program?
Author
Price Tags would love to feature such maps.