Lately I’ve been playing around with the 3D visualisation tool in QGIS to see what it can do. First I downloaded the population density by meshblock data from the 2013 census. As I’ve said about a hundred times now, this would make make much more sense with the 2018 census data, but unfortunately Stats still aren’t able to provide anything.
I mapped this by colour with white denoting high density residential and black denoting low density residential. Then I extruded the meshblocks up based on density, with the taller blocks denoting higher density and the lower blocks lower density. I did this for the whole country, and have shown a selection of cities below. These are all at the same scale with consistent heights and colourings, so are comparable.
These show a few things. Firstly, Christchurch does not have the high density core that Auckland and Wellington have. This is of course partly due to the 2013 census being only just after the earthquakes that levelled most of the city centre. But even pre-earthquake (and post rebuild) I suspect it still wouldn’t have intense core that Auckland and Wellington have.
Even in the suburbs, Christchurch has a lower ambient density than Auckland and Wellington. The map for Christchurch is mostly a dull grey, while Auckland and Wellington are a slightly brighter shade. People talk about Auckland’s “leafy” low-density suburbs – Christchurch’s are even lower-density and possibly leafier.
Christchurch is compact. While mountains and sea force Auckland and Wellington outwards in irregular splurts, residents in Christchurch are clustered tightly around the central city, with few people living more than about 10 kilometres away. Wellington and Auckland both have a significant proportion of their populations living 10km+ from the city centre.
Christchurch’s densest areas are the inner suburbs immediately surrounding the central city – Addington, Sydenham, Linwood, St Albans. The Riccarton corridor is dense as well, and there is a big spike at Studentville around the university. There are occasional other localised spikes caused by things like retirement villages. As a general rule, the older suburbs tend to be higher density, while the newer suburbs tend to be lower density.
All up I think the QGIS 3D visualisation tool is quite cool. It doesn’t really provide any new information than what we already know, but it visualises it in a way that can reveal patterns which we may not have noticed before.
Next up – I’ll have a look at employment density. After that I’ll map out some of the options for mass rapid transit and see how they relate to residential and employment densities.
What do you see in these images?