Transport planners love to talk about urban density, but what does Melbourne’s urban density actually look like? Google for a Melbourne urban density map and you won’t find much.
The ABS publication Melbourne.. A Social Atlas has a density map (see pages 12-13) at the Census Collection District (CCD) level, but only has five colour graduations so subtleties are quickly lost.
So I’ve decided to draw one myself.
Arguably the best source of data for housing density is the ABS’s experimental mesh blocks, which are smaller than Census Collection Districts (CCD). Mesh blocks are designed to have more uniform land use, which gets around the problem of a CCD which might contain a mix of residential, parkland and commercial land use showing up as low density. But I’ll come back to this.
So here is a 2006 population density map of Melbourne at the mesh block level:
(I’m using people per square km, which is 100 times larger than people per hectare if you need to convert).
You’ll need to click to zoom in, and you might want to then zoom in again with your favourite image viewer to see the detail.
- Many areas on the very fringe show as low density, but this might be because that area was under development at the time of the census, and only some people had moved in.
- Everyone talks about low density sprawl on the fringe, but even back in 2006 there was evidence of higher density development in the outer suburbs. Have a look at the Craigieburn area in the north or around Narre Warren and you will see many patches of green. New blocks on the urban fringe are now actually quite small in places compared to those in the middle suburbs. Two storey townhouses are actually not uncommon in new estates.
- In the north-west (around Delahey/Sydenham), you can see a north-south divide where there is higher density on the eastern side. This corresponds with the municipal boundary between Brimbank and Melton. Presumably they’ve had different urban development policies.
- The biggest clumps of density are in the inner city, particularly Carlton and Carlton North, Fitzroy, St Kilda, Richmond, and Kensington (the western side of which enjoys a 5½ days per week route 404 bus service).
- Looking at the Central Activities Districts (CADs), there are clumps of density near the Dandenong and Box Hill CADs. But nothing to speak of inside Ringwood, Frankston, or Broadmeadows CADs (in 2006).
- Other curious pockets of density in the suburbs include west of Highpoint Shopping Centre, Sunshine, Glenhuntly/Carnegie, and Glen Iris.
- The lowest density suburbs in Melbourne are found in the middle and outer eastern suburbs (particularly Upwey/Belgrave), and in the north-east around well off areas such as Eltham, Toorak and Eaglemont. North west Reservoir seems to be a problem area – high socio-economic disadvantage and low density (not to mention a bus route that runs 5½ days a week).
- Interesting to see relatively higher densities south of the Dandenong rail line.
For comparison purposes, I’ve also created a version based on larger Census Collection Districts (CCDs):
(note: this map doesn’t show anything outside the Melbourne SD)
What’s the difference you ask? You cannot see a great deal of difference, though the CCD map makes Melbourne look a little less dense.
But if you zoom in you can spot differences in some areas where a CCD is part residential, part not. Here’s an example in the Black Rock/Beaumaris area:
The CCD map on the left shows a few darker red blocks next to the whitespace, but that low density is not visible in the mesh blocks on the right, because the mesh blocks split the parkland and houses. You can also see that the CCDs run to the shoreline, while the beach area has been split into separate mesh blocks.
The advantage of the mesh block map is that it pretty much shows housing density, as most pieces of land that are not residential have been removed (including suburban parks).
But the advantage of CCD density is that it includes local parkland, which is a measure of open space within and immediately surrounding residential areas.
A better way of looking at the density equation is a cumulative distribution chart, as created by Fedor Manin on his blog We Alone on Earth (also referenced on Human Transit).Rather than having to worry about whether low density areas on the fringe are “urban” or not, you can just look at density by population share, and the fringe areas will quickly tail out anyway. On this basis the problems of using an administrative boundary of a city (which often contains a large areas of rural land) largely go away, but then you don’t get a single number.
I’ve lined up all mesh blocks and CCDs in the Melbourne SD in order of density, and created a cumulative profile of density for each.
You can see a big difference between CCDs and mesh blocks (note the X axis is logarithmic). On a mesh block basis, about half of Melbourne’s population lives at a density of greater than 3200/km2, whereas on a CCD basis, only 30% of Melbourne’s population lives at a density greater than 3200/km2. Take note anyone doing a comparison between cities!
Here’s a chart on the same data showing a population distribution across densities, using mesh blocks and CCDs:
You can see the most common density for mesh blocks is slightly higher than for CCDs. The peak for mesh blocks is between 2818-3162 people/km2 on my intervals. That’s an funny sounding interval because I’ve used logarithmic intervals (if you use even intervals of 100 people/km2, the peak is between 2900 and 3300 people/km2)
So what is the average density of Melbourne?
What is Melbourne? Should we include satellite urban areas around the city? For example, is Sunbury part of Melbourne? It is within the Melbourne SD (Statistical District) but not within the Melbourne “Urban Centre” as defined by ABS. Do you want to include non-residential areas (urban density), or not? (residential density)
Here are six very different measures of the urban density of Melbourne, including some measures that have minimum density threshold to restrict the calculation to “residential” areas. The maps above use 1000 people/km2 as a threshold for colouring, and this appears to include all “residential” areas, except for some very large block estates.
|Geography||Area (km2)||Population||Density (pop/km2)|
|Mesh blocks within all Urban Centres/Localities within Melbourne SD||2,357||3,506,207||1,488|
|“Melbourne” Urban Centre||2,153||3,368,069||1,564|
|CCDs within Melbourne SD, with population density > 100 people/km2||2,151||3,514,658||1,634|
|Meshblocks within Melbourne SD, with population density > 100 people/km2||1,566||3,511,982||2,242|
|Meshblocks within “Melbourne” Urban Centre, with population density > 100 people/km2||1,350||3,358,317||2,487|
|Meshblocks within Melbourne SD, with population density > 1000 people/km2||1,084||3,316,516||3,060|
You can quickly see why trying to calculate an average density is a fraught exercise! Though the first two are trying to measure “urban density”, while the later are attempting to measure “residential density” (and note the threshold for residential density makes a big difference).
A density profile chart (as above) is clearly a good way to get around the defined area problem. But you still need to be consistent in the land parcel size you use when comparing cities. Not easy when comparing cities with different statistics agencies.
Land use map of Melbourne
Before I finish up, the other beauty of the mesh block data is that it contains a land use classification for each mesh block.
So it is really easy to produce a land use map of Melbourne (and Geelong for good measure):
What are those two black blobs I hear you ask? Essendon and Moorabbin Airports. Tullamarine and Avalon airports are actually classified agricultural.
And you will see residential areas stretching a fair way east of Frankston, and north of Craigieburn – though these are not actually developed. So it’s not perfect.
In fact, according to the data, there is a mesh block in Melbourne with 358 people living in an area of 420 square metres (852,700 people/km2). That’s 1.17 square metres of land space per person. Really? No, what appears to have happened is that almost every resident of the Burnside Retirement Village was registered to one tiny parcel of land. I suppose that’s census data for you!
Hi Chris, another great contribution. I’ve agonised for some time over the appropriate way to calculate the gross density of Melbourne. One problem you find is that the ABS fiddled the definition of urban centres some time ago to include ex-urban areas that were previously excluded as not connected to the urban area. It’s really interesting how much higher a number you get when you use meshblocks rather than CCDs. Though what you’ve calculated is probably closer to the geographers’ “net residential density” than the “gross urban density” for which there are comparative figures.
Chris, interesting maps. You ought to change the colour of the tram lines though, they are coming up as dark green lines that are difficult to distinguish from dense development (… ironic). The 404 is interesting because as well as being rare (it stops at about 6:30!) it is also doesn’t run anywhere particularly helpful (and I say that despite living adjacent to it). Kensington Banks is (in general) an interesting case study for the failure to adapt inner-urban transport routes to in-fill development.
Tony, what measure of density you use depends on the application. Every measure of density tells you something useful about the urban form, as too will the ratio between different measures. That is, a single number isn’t necessarily a useful thing to have.
Russ, I’ve changed the tram lines to black, and increased the overall resolution a little too.
I have had a request to show the change in population density between 2001 and 2006. Unfortunately the boundaries of census collection districts changed a fair bit between 2001 and 2006, and there are no meshblocks for 2001.
But for what it is worth, I have created a map that shows the change in density for CCDs that did not change in size between 2001 and 2006. You’ll see lots of grey areas where a comparison isn’t possible, particularly in the fringe growth areas. Still, there are some interesting results in other areas. There are often density reductions in places that have hotels or hospitals – the 2001 data used is based on place of enumeration, not place of usual residence (I did this quickly, sorry guys).
I know this is old, but one interesting thing to come back to is those patches of high density sprawl.
This is really noticeable in Auckland, NZ as well. While some innercity neighbourhoods still have 400sqm lots with bungalows, on the fringe you increasingly see apartment blocks (some 5+ stories tall) and small row houses. Actually pretty high density.
My bet would be that developers recognize that high density housing is in demand (for economic reasons), but that the NIMBYness in and the (to a lesser extent*) brownfield nature of innercity sites makes high density difficult.
* Redeveloping isn’t as prevalent in Auckland, as say, Japan, but it isn’t that prohibitive. Especially considering the huge stock of leaky buildings that don’t meet code (and thus present little opportunity cost) and large patches of unused land.
How did you create these? I’d like to do a similar density profile for Sydney.
You need some sort of GIS software, data from the ABS website, and some data analysis skills. Here’s some free GIS software info: http://gisgeography.com/free-gis-software/