Are Australian cities sprawling with low-density car-dependent suburbs?

Wed 30 January, 2019

Many people talk about urban growth in Australian cities being car-dependent low-density suburban sprawl. But how true is that in more recent times? Are new greenfield density targets making a difference? Are cities growing around their rapid public transport networks? And how do growth areas compare to established areas at a similar distance out from city centres?

This post takes a look at what census data can tell us about outer urban growth areas in terms of population density, motor vehicle ownership, distance from train/busway stations, and journey to work mode shares.

How much of city population growth is in outer areas?

Firstly a recap, here is the percentage of annual population growth in each city that has occurred in “outer” areas (defined by groupings of SA3s around the edges of cities – refer my previous post for maps showing outer areas) for Greater Capital City Statistical Areas.

Sydney has had less than a third of its population growth in outer areas since around 2003, while Perth has mostly had the highest outer growth percentage (since 1996), and more recently pretty much all population growth in Perth has been on the fringe. You can see how the other cities sit in between.

However, not all of this “outer” population growth was in urban growth on the fringe. For that we need to distinguish between urban growth and infill development, even in “outer” areas. So we really need a better definition of outer growth areas.

How to define outer urban growth areas

I have built groupings of SA1s (Statistical Area Level 1) that try to represent outer urban greenfield residential development. SA1s are the smallest census geographic areas (average population 400) for which all census data variables are available.

I’ve selected 2016 SA1s that meet all of the following criteria:

  • Brand new SA1 or significant population growth: The 2016 SA1 is new and cannot be matched to a 2011 SA1 (by location/size and/or ABS correspondences), or if it can be matched, the population at least doubled between 2011 and 2016. Brand new SA1s are very common in urban growth areas as new SA1s are created to avoid oversized SA1s on last census boundaries (except this doesn’t always happen – more on that shortly).
  • In an SA2 with significant population growth: The SA2 (Statistical Area Level 2 – roughly suburb sized with typically 3,000 to 25,000 residents) that contains the SA1 had population growth of at least 1000 people between 2011 and 2016 (based on 2016 boundaries). That is, the general area is seeing population growth, not just one or two SA1s.
  • Are on – or close to – the urban fringe. I’ve filtered out particular SA2s that I’ve judged to be contain all or mostly in-fill development rather than greenfield development, or that are largely surrounded by existing urban areas and are not close to the urban fringe. I’ll be the first to admit that some of the inclusions/exclusions are a little arbitrary.

The criteria aren’t perfect, but it seems to work pretty well when I inspect the data. I’m calling these “Growth SA1s” or outer urban growth in this post.

For urban centres, I’m using Significant Urban Area 2016 boundaries (rather than Greater Capital City boundaries), and I’ve bundled Yanchep with Perth, Melton with Melbourne, and the Sunshine Coast and Gold Coast with Brisbane to form South East Queensland (SEQ).

Where are these outer urban growth areas?

What follows are maps for each city with the density of these growth SA1s shown by colour.

Melbourne’s northern and western growth areas:

Technical note: The maps do not show non-growth SA1s with fewer than 5 people per hectare, or “growth SA1s” with fewer than 1/hectare, although these SA1s are including in later analysis.

And the south of Melbourne:

Note: not shown on these Melbourne maps are isolated tiny growth SA1s in Rosebud and Mooroolbark.

Here are Sydney’s growth SA1s – all in the western suburbs:

Next up South East Queensland, starting in the north with the Sunshine Coast:

Northern Brisbane:

Outer urban growth is scattered in southern Brisbane and northern Gold Coast:

Gold Coast – Tweed Heads:

Perth’s northern and eastern growth areas:

Perth’s southern growth areas:

Note: Canning Vale East is an inclusion you could debate – the previous land use of the growth SA1s appear to have been rural based on satellite imagery.

Northern Adelaide:

Southern Adelaide:

And finally Canberra:

So how much of each cities’ population growth has been in outer growth areas?

Here’s a breakdown of the population growth for my six urban areas:

Over the five-year period, outer urban growth areas accounted for 19% of Sydney’s population growth, 43% of Melbourne’s, 37% of SEQ’s, 60% of Perth’s, 27% of Adelaide’s and 69% of Canberra’s.

Technical note: These “outer urban growth” figures are different to the chart at the top of this post which had a coarser definition of “outer” and used Greater Capital City boundaries. Some of my “outer urban growth” areas actually don’t quality as “outer” in the coarser definition, and I’ve also excluded several “outer” SA2s from “outer urban growth” where I’ve deemed the growth to be mostly infill. Hence the differences.

In case you are wondering, it’s not easy to create a longer-term time-series analysis about the proportion of population growth in “outer urban growth” areas because the classification of SA2s would have to change on a year-by-year basis which would be messy and somewhat arbitrary.

A challenge for density analysis: some SA1s are over-sized

You might have noticed some SA1s in the maps above are very large and show a low average density of 1-5 persons per hectare (I’ve coloured them in a light cyan). Many of these SA1s had thousands of residents in 2016, which is way more than the ABS guideline of 200 to 800 residents. Unfortunately what seems to have happened for 2011 and 2016 in some cities is that the ABS did not create enough SA1s to account for new urban areas. Some Melbourne SA1s had a population over 4000 in 2016. Many of these SA1s contain a combination or urban and rural land use, so their calculated density is rather misleading.

I’m designating any SA1s with more than 1000 residents and larger than 100 hectares as “oversized”, and I’ve exclude these from some density analysis below. Here’s a chart showing the proportion of outer growth area populations that are in oversized SA1s:

You can see it is a substantial problem in Sydney, Melbourne, Perth and South East Queensland, but miraculously not a problem at all in Adelaide or Canberra (I’m sure someone in ABS could explain why this is so!).

If you are interested, in 2011 it was a bigger problem in Melbourne, and only Canberra was fully clean.

So how dense are outer urban growth areas?

Firstly, I am excluding over-sized SA1s from this analysis for the reasons just mentioned.

Secondly, all cities will also have growth areas that were partially developed at the time of the census (ie some lots with occupied houses and other lots empty) so the densities measured here may be understated of the likely fully built-out density of these SA1s. That said, those areas perhaps are more likely to be in over-sized SA1s, but it’s hard to be sure. So keep this in mind when looking at growth area densities.

You can see dramatic differences, with Sydney, Canberra, and Melbourne showing higher densities, and South East Queensland with much lower densities. As we saw on the maps above, South East Queensland’s outer growth areas are very dispersed, so perhaps more of them are growing slowly and more of them are partially built-out? It’s hard to be sure.

But perhaps what is most remarkable is that Canberra had the highest densities in outer urban growth areas of any city – nothing like what you might consider suburban sprawl. Here’s what was 144.5 people per hectare in 2016 in Wright on Canberra’s new western growth front looks like:

(pic from Google Streetview, dated December 2016)

The densest SA1 in Sydney’s growth areas was 101 persons/ha. Nothing like this was seen in other cities.

Canberra’s outer growth areas are actually, on average, denser than the rest of Canberra (on a population weighted density measure):

The same was also true by a slim margin in both Perth and Adelaide, but they have relatively “suburban” densities for both growth and established areas. The growth areas of Sydney and Melbourne are more dense than Perth and Adelaide, but not compared to the rest of these cities as a whole. That’s probably got to do a lot with the large cities having dense inner suburbs.

So perhaps it is better to compare the urban growth areas with established areas a similar distance from city centres, which the following chart does (I’ve filtered out 5 km distance intervals without growth areas of at least 2000 population, and apologies for rather squashed Canberra label):

Technical note: for South East Queensland I’ve measured distances from the Brisbane CBD.

Outer growth areas were much more dense than the rest of each city at most distances from the city centre, except in Sydney.

One issue with the above chart is that different distance intervals have different populations – for example only 2,815 people were in growth SA1s at a distance of 45-50 km from the Perth CBD (just above my threshold of 2000), so the low population density of that interval is not hugely significant.

To get around that issue, I’ve calculated the overall population weighted density of non-growth SA1s that are within these 5 km distance intervals from the CBD (including all of SEQ beyond 15 km from the CBD). The following chart compares those calculations with the population weighted density of the growth areas overall:

This shows that urban growth areas are on average more dense than other parts of the city at similar distance from the CBD, except in South East Queensland. And remember, many of the growth SA1s will be partially built out, so their expected density is understated.

Are outer urban growth areas near rapid public transport?

The next chart shows the proportion of growth SA1 population by distance from the nearest train or busway station:

Technical notes: Distances are measured from the centroid of each SA1 to a point location defined for each station (sourced from August 2016 GTFS feeds). For oversized SA1s these distances might be a little longer than reality for the average resident. I haven’t excluded oversized SA1s because I want to see the population alignment of growth areas overall. Canberra excluded due to lack of separated rapid transit.

What sticks out clearly is that just over half the of the population in Perth’s outer growth areas was more than 5 km from a station in 2016. That is to say Perth has had the least alignment of outer urban growth areas and rapid public transport networks of all five cities. I’m not sure many urban planners would recommend such a strategy.

However, Perth’s MetroNet program appears to be trying to rectify this with new lines and stations proposed near urban growth areas such as Yanchep, Canning Vale East, Ellenbrook, Byford, and Karnup (Golden Bay). It will however take some time to get to them all built and open.

South East Queensland was second to Perth in terms of urban growth remote from stations, with a lot of the growth scattered rather than concentrated around rail corridors. I haven’t included the Gold Coast light rail in my proximity calculation – it runs at an average speed of 27 km/h (which is slower than most train networks) and doesn’t serve outer urban growth areas.

Sydney and Adelaide had the highest proximity of growth areas to stations.

Around half of Melbourne’s growth SA1s that were more than 5km from a train station were in Mernda and Doreen, a corridor in which a rail extension opened in 2018. Many of the rest are not in the current designated growth corridors, or are where future train stations are planned. Melbourne’s current designated urban growth corridors are fairly well aligned to its train network. From a transport perspective this is arguably a better kind of sprawl than what Perth has been experiencing.

Adelaide’s outer growth areas more than 5 km from a station were in Mount Barker (satellite town to the east) and Aldinga (on the far south coast of Adelaide).

Are the outer urban growth areas better aligned to rapid public transport stations than non-growth areas at the same distance from city centres? Here’s the chart as above but with an extra column for non-growth areas within the same distance intervals from the CBD (as before).

The populations of urban growth areas are less likely to be within a couple of kilometres of a station (most of that land probably has long-established urban development), but curiously in Adelaide and South East Queensland the urban growth areas are more likely to be within 5 kilometres of a station than the non-growth areas, suggesting better rapid public transport alignment than older urban growth areas. Older urban areas in other cities are more closely aligned to stations, particularly in Perth.

As an interesting aside, here’s a breakdown over the last three censuses of population by distance from train/busway stations (operational in 2016 – so it overstates 2006 and 2011 slightly):

You can really see how Perth has had much population growth remote from its rapid public transport network, which probably goes some way to explaining the overall 1.2% journey to work mode shift towards private transport between 2011 and 2016.

So how did people in these outer growth areas get to work?

Technical note: The figures here for “private transport” are for journeys involving only private transport modes – i.e. they exclude journeys involving both private and public transport (eg car+train).

While private transport (mostly car driver only journeys) dominated journeys to work from almost all growth areas, Melbourne and Sydney were the only cities to see significant numbers of residents in outer growth areas with private transport mode shares below 80%.

South East Queensland’s outer urban growth areas were the most reliant on private transport to get to work, with an overall private transport mode share of 93%, followed by Adelaide on 92%, Canberra on 91%, Perth on 90%, Melbourne on 86%, and Sydney on 81%.

Here’s how the growth area mode shares compare to other areas a similar distance from city centres (note: the Y-axis is not zero-based):

Significantly, the growth areas of Sydney and Melbourne had lower private transport mode shares of journeys to work than other parts of the city a similar distance out – even though they are generally further away from train or busway stations (as we saw above)! That’s not to say they didn’t drive themselves to a train station to get to work.

Similar to population density, here is a summary of growth areas compared to other areas in the same distance interval from the CBD:

There’s really not a huge amount of difference within cities. Sydney’s growth areas had a mode share 1.5% lower than non-growth areas, while Canberra’s growth areas had a mode share 2.5% higher.

What are motor vehicle ownership rates like in the outer growth areas?

My preferred measure is household motor vehicles per persons aged 18-84 (roughly people of driving age).

Motor vehicle ownership rates are generally very high across the growth areas – with the notable exceptions of Melbourne and Canberra where around a quarter of the growth area population had a motor vehicle ownership rate of less than 80 (although that is still pretty high!). (I explored this in more detail in an earlier post on Melbourne)

South East Queensland, Perth, and Adelaide outer urban growth areas had the highest motor vehicle ownership rates. Perth’s urban growth areas overall averaged 96.7 motor vehicles per persons aged 18-84 – pretty close to saturation.

How does motor vehicle ownership compare to established areas a similar distance from the city centre? The following chart compares motor vehicle ownership between urban growth and other areas at the same distance from the CBD (note: the Y-axis is not zero-based):

Motor vehicle ownership tends to increase with distance from the CBD, and in Sydney and South East Queensland the growth areas have higher ownership compared to non-growth areas. But the opposite is true in Melbourne, Perth and Canberra.

The population at each distance interval varies considerably, so here is a summary of the data across all distance intervals that have growth SA1s for each city:

The growth areas of Melbourne, Perth and Canberra had slightly lower motor vehicle ownership than other areas a similar distance from the city, while the opposite was true in other cities. That said, motor vehicle ownership rates are very high across all cities.

 

Finally, I’ll look at the relationships between these measures for growth areas (see another post for analysis for whole cities).

How does motor vehicle ownership relate to distance from stations?

Technical note: for scatter plots I’ve filtered out SA1s with less than 50 population as they are more likely to have outlier results (one person can change a measure by 2% or more).

Lower rates of motor vehicle ownership are generally only found close to train/busway stations (and are dominated by Melbourne examples), but close proximity to a station does not guarantee lower rates of motor vehicle ownership. Quite a few Adelaide SA1s are found the top middle part of the chart – these are all in Mount Barker which has frequent peak period express buses to the Adelaide CBD operating along the South East Freeway – which is similar to rapid transit although without a dedicated right of way.

How do journey to work mode shares relate to distance from stations?

Here’s a scatter plot of private transport mode shares of journeys to work and distance from train/busway station:

This shows that lower private transport mode shares are only generally seen within proximity of train or busway stations, and areas remote from stations are very likely to have high private transport mode shares. But also that proximity to a station does not guarantee lower private transport mode shares of journeys to work (particularly in SEQ).

Technical aside: You might have noticed that almost no SA1s report 99% private mode share. How can that be? The ABS make random adjustments to small figures to avoid identification of individuals which means you never see counts of 1 and 2 in their data. To get a mode share of 99% you’d need at least 300 journeys to work with “3” being non-private (or a similar but larger ratio). Very few SA1s have 300+ journeys to work, and even for over-sized SA1s, they are very unlikely to have only 3 or 4 non-private journeys to work. A mode share of 100% is much easier because you can get that no matter the total number of journeys.

How does population density relate to distances from train/busway stations?

Densities above 45 persons/ha were mostly only found within 5 km of stations, and almost entirely in Sydney and Melbourne. The highest densities were very close to train stations in Sydney. In the middle area of the chart you can see quite a few Perth SA1s that are around 30-40 persons/ha but remote from stations. These are all in the Ellenbrook area of Perth’s north-east, generating a lot of car traffic.

How does motor vehicle ownership relate to private transport mode shares of journeys work to work?

For interest, here is the relationship as a scatter plot:

There is certainly a relationship, but it’s not strong (r-squared = 0.22). Other factors are at play.

Conclusions

  • Perth and Canberra are seeing most of their population growth on the fringe, with Sydney, Adelaide, Melbourne, and South East Queensland seeing most of their population growth in established areas.
  • Growth areas in Sydney, Melbourne, and Canberra have higher than traditional urban densities, indeed Sydney and Canberra have a few very high density greenfield developments. Perth, Adelaide, and particularly South East Queensland have urban growth at relatively low densities. In fact, SEQ is the only major urban centre where growth areas are measured as less dense than non-growth areas at similar distances from the CBD.
  • Perth’s urban growth areas are largely remote from rapid transit stations, and this is likely contributing directly to very high and increasing rates of motor vehicle ownership and private transport mode shares. Melbourne’s current urban growth corridors are closely aligned to train stations (thanks to the opening of the Mernda line), and this is also largely true of Sydney and Adelaide.
  • Almost all outer urban growth areas had high rates of motor vehicle ownership. Overall, Melbourne, Perth, and Canberra’s outer urban growth areas had slightly lower rates of motor vehicle ownership compared to other areas at the same distance from the CBD. Only Sydney, Melbourne and Canberra have some growth areas with lower motor vehicle ownership and/or lower private transport mode shares of journeys to work – and these were all close to train or busway stations.

I hope you’ve found this at least half as interesting as I have.

For a similar and more detailed analysis around these topics, see this excellent 2013 BITRE research report on changes between 2001 and 2006.

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What explains variations in journey to work mode shares between and within Australian cities?

Thu 6 December, 2018

Private and public transport journey to work mode shares vary considerably both between Australian cities and within them. Are these differences related to factors such as population density, motor vehicle ownership, employment density, proximity to train stations, proximity to busway stations, jobs within walking distance of homes, and distance from the city centre?

This posts sheds some light on those relationships for Australia’s six largest cities. I’m afraid it isn’t a short post (so get comfortable) but it’s fairly comprehensive (over 30 charts).

I should stress up front that a strong relationship between a certain factor and high or low mode shares does not imply causation. There are complex relationships between many of these factors, for example motor vehicle ownership rates are generally lower in areas of higher residential density (which I will also explore), and more factors beyond what I will explore here.

If you are interested in seeing spatial mode share patterns, see previous posts for Melbourne, Brisbane, and Sydney. You might also be interested in my analysis explaining the mode shifts between 2011 and 2016.

Population density

Higher population densities are commonly associated with higher public transport use. This stands to reason, as high density areas have more potential users per unit of area, but also higher density is likely to mean high land prices, which in turn increases the cost of residential parking. But higher public transport mode share can only happen if government’s invest in higher service levels, and this isn’t guaranteed to happen (although it often does, through pressures of overcrowding).

My preferred measure is population weighted density, which is the weighted average density of land parcels in a city, weighted by their population (this gets around problems of including sparsely populated urban land). I’ve measured it at census district (CD) geography for 2006 and Statistical Area Level 1 (SA1) geography for 2011 and 2016, using 2011 Significant Urban Area boundaries to define cities. The 2006 density figures are not perfectly comparable with 2011 and 2016 because CDs are slightly larger than SA1s, so the density values will be calculated as slightly smaller.

Here is the relationships at city level (the thin end of each worm is 2006 and the thick end 2016, with 2011 in the middle):

The relationship is very strong for Melbourne and Sydney over time. Between 2011 and 2016, Perth and Brisbane saw increased population density but reduced public transport mode share (mostly because of changes in the distribution of jobs between the centre and the suburbs).

Brisbane was a bit of an outlier in 2006 and 2011 with high public transport mode share relative to its lower population density.

Canberra is also perhaps a bit of an outlier, with much lower public transport mode share compared to similarly low density cities. This might be explained by the smaller total population, lower jobs density, and lack of rapid public transport services segregated from traffic.

But Canberra does have higher active transport mode share, so it’s worth doing the same analysis with private transport mode shares:

Brisbane was still an outlier in the relationship in 2006 and 2011, but Canberra is more in line with other data points.

Another interesting note is that Canberra went from being the least dense city in 2006 to the third most dense in 2016.

Drilling down to SA2 geography (SA2s are roughly the size of a suburb), here’s a chart showing all SA2s in all cities across the three census years (filtered for CDs and SA1s with at least 5 persons per hectare). I’ve animated it to highlight one city at a time so you can compare the cities, and I’ve used a log scale on the X-axis to spread out the data points (only the Sydney and Melbourne CBDs go off the chart to the right).

(if these animated GIF charts are not clear on your screen, you can click to enlarge the image, then use “back” to come back to this page).

You can see a fairly strong relationship, although it is very much a “cloud” rather than a tight relationship – there are other factors at play.

What I find interesting is that Sydney has had a lot of SA2s with population weighted densities around 50-100 but private mode shares over 55% (toward the upper-right part of the cloud of data points) – which are rare in all other cities. That’s a lot of traffic generation density, which cannot be great for road congestion. In a future post I might focus in on the outlier SA2s that are in the top right of these charts (can public transport do better in those places?).

In case you are wondering about the Brisbane SA2 with low density and low private transport mode share (middle left of chart) it is the Redland Islands where car-carrying ferries are essential to get off an island, and are counted as public transport in my methodology. The Canberra outlier in the bottom left is Acton (which is dominated by the Australian National University).

Employment density

I’ve calculated a weighted job density in the same way I’ve calculated population weighted density, but using Destination Zones (which can actually be quite large so it certainly isn’t perfect). Weighted job density is a weighted average of job densities of all destination zones, weighted by the number of jobs in each zone. In a sense it is the density at which the average person works

(technical notes: I’ve actually only counted jobs as people who travelled on census day and reported their mode(s) of travel. Unfortunately I only have 2006 data for Sydney and Melbourne)

This chart suggests a very strong relationship at the city level, with all cities either moving up and left (Adelaide, Perth and Brisbane) or down and right (Sydney, Melbourne, Canberra).

So is the relationship as strong when you break it down to the Destination Zone level? The next chart shows jobs density and private mode share for all destination zones for 2016. Note that there is a log scale on the x-axis, and Adelaide dots are drawn on top of other cities in the top left which explains why that dense cloud of dots appears mostly green.

There’s clearly a strong relationship, although again the data points form a large cloud rather than tightly bunch around a line, so other factors will be at play.

It’s also interesting to see that the blue Sydney dots are generally lower than other cities at all job densities. That is, Sydney generally has lower private transport mode shares than other cities, regardless of employment density.

Which leads us to the next view: the private transport mode shares for jobs in different density ranges in each city for 2011 and 2016.

(click to enlarge if the chart appears blurry)

You can see a fairly consistent relationship between weighted job density and mode shares across all cities in both 2011 and 2016.

At almost all job density ranges, Sydney had the lowest average private transport mode share, while Adelaide and Perth were generally the highest (data points are not shown when there are fewer than 5 destination zones at a density range for a city). This shows that something other than jobs density is impacting private transport mode shares in Sydney. Is it walking catchment, public transport quality & quantity, or something else?

For more on the relationship between job density and mode share, see this previous post.

Proximity to public transport

Trains generally provide the fastest and most punctual public transport services (being largely separated from road traffic and having longer stop spacing), and are the most common form of rapid transit in Australian cities. So you would expect higher public transport mode shares around train stations.

Here is a chart showing average journey to work public transport mode shares by home distance from train stations. It’s animated over the three census years, with a longer pause on 2016.

Technical note: A limitation here is that I’ve measured all census years against train stations that were operational in 2016 – so the 2006 and 2011 mode shares will be under-stated for the operational stations of those years. For example, in Melbourne the following stations opened between 2011 and 2016: Williams Landing, South Morang, Lynbrook, and Cardinia Road.

You can see that public transport shares went up between 2006 and 2011 in most cities at all distances from train stations. In both Perth and Brisbane there were new train lines opened between 2006 and 2011, which will explain some of that growth.

But if you watch carefully you will see public transport mode shares near train stations fell in both Brisbane and Perth between 2011 and 2016. That is, there was a mode shift away from public transport, even for people living close to train stations. As discussed previously, this is most likely related to there being only small jobs growth in the CBDs of those cities between 2011 and 2016, compared to suburban locations.

You can also see that public transport mode shares aren’t that much higher for areas near train stations in Adelaide (I’ll come back to that).

We can do the same for train mode shares (any journey involving train):

Again, Sydney’s train stations seem to have the biggest pulling power, while Adelaide’s have the least.

Busways are the other major form of rapid transit in Australian cities, with major lines in Brisbane, Sydney and Adelaide. Here is a chart of public transport mode share by distance from busway stations, excluding areas also within 1.5 km of a train station:

Note for Adelaide this data only considers suburban stations on the O-bahn, and not bus stops in the CBD. For Sydney all “T-Way” station are included, plus the four busway stations on the M2 motorway for which buses run into the CBD (but not the relatively short busway along Anzac Parade in Moore Park). Sydney’s north west T-Ways opened in 2007

Proximity to a busway station appears to influence public transport mode share strongly in Brisbane and Adelaide, where busways are mostly located in the inner and middle suburbs and cater for trips to the CBD. Sydney’s busway stations are in the “outer” western suburbs, feeding Blacktown, Parramatta, but also relatively long distance services to the Sydney CBD via the M2.

Curiously, public transport mode shares were higher in places between 3 and 5 km from busway stations in Sydney, compared to immediately adjacent areas. I’m not sure that I can explain that easily, but it suggests equally attractive public transport options exist away from busway and train stations.

The station proximity influence appears to extend around 1 km, which possibly reflects the fact that few busway stations have park and ride facilities, and are therefore more dependent on walking as an access mode (although cycling may be another station access mode).

Over time Sydney public transport mode share lifted at all distances from busway stations, while in Brisbane it rose in 2011 and then fell again in 2016, in line with other city mode shares.

So are busway stations similar to train stations in their impact on public transport mode share? To answer this I’ve segmented cities into areas near train stations, near busway stations, near both, and near neither. I’ve used 1.5 km as a proximity threshold that might represent an extended walking catchment.

In Sydney, train stations appear to have a much stronger influence on public transport mode shares than busway stations, but the opposite is true in Brisbane and Adelaide. This possibly reflects the much higher service frequencies on Adelaide and Brisbane busways compared to their trains, and the fact Sydney’s busway stations are so far from the CBD (and thus have fewer workers travelling to the CBD where public transport dominates mode share).

Also of note in this chart is that for areas more than 1.5 km from a train or busway station, Sydney had a much higher public transport mode share compared to the other cities. These areas will be served mostly by on-road buses, but also some ferries and one light rail line. Adelaide has the least difference between mode share for areas near and not-near train or busway stations.

We can do the a similar analysis for workplaces:

The most curious pattern here is Adelaide – where public transport mode share was highest for jobs between 1.5-2.5 kms from train stations. This distance band is dominated by the centre of the Adelaide CBD (the station being on the edge, arguably a “corner”), for which bus was the dominant public transport access mode. Also, there was no destination zone small enough near Adelaide central train station to register as 0 – 0.5 km away, and only one that is 0.5 – 1 km away (I use distances between station data points and destination zone centroids). So the results might look slightly different if smaller destination zones were drawn in the Adelaide CBD.

In all other cities there was a very strong relationship between train station proximity and public transport mode share, as you would expect. And Sydney again stands out with high public transport mode shares for workplaces more distant from train stations.

If you are wondering, the bump in Sydney at 2.5 to 3 km includes the Kensington / Randwick area which has high employment density and a strong bus connection to the central city (partly assisted by the Anzac Parade busway). And the relatively high figure for Melbourne at 1 – 1.5 km includes parts of Docklands, Parkville, Southbank, and St Kilda Road, which all have high tram service levels.

Unfortunately destination zones around busway stations are generally too large to provide meaningful insights so I’m not presenting such data.

Motor vehicle ownership

It will come as little surprise that there is a relationship between household motor vehicle ownership and journey to work mode shares.

Here’s a summary chart for each city for the 2006, 2011 and 2016 censuses:

There appears to be a fairly strong relationship between the two factors at city level.

Sydney and Melbourne have seen the largest mode shift away from private transport, but only Melbourne has also seen declining motor vehicle ownership rates.

Canberra saw only weak growth in motor vehicle ownership between 2011 and 2016, and at the same time there was a shift away from private transport (and a large increase in population weighted density).

Perth and Brisbane saw increasing private transport mode share and increasing motor vehicle ownership between 2011 and 2016.

Here’s a more detailed look at the relationship over time for Melbourne at SA2 geography:

The outliers on the upper left are generally less-wealthy middle-outer suburban areas (lower motor vehicle ownership but high private mode share), while the outliers to the lower-right are wealthy inner suburbs where people can afford to own plenty of motor vehicles, but they didn’t use them all to get to work.

In the bottom left of the chart are inner city SA2s with declining private mode share and declining motor vehicle ownership. For motor vehicle ownership rates around 70-80 (motor vehicles per persons aged 18-84), there are many SA2s with private mode shares that declined 2006 to 2016, but not significantly lowering motor vehicle ownership rates. That suggests that just because people own many motor vehicles, they don’t necessarily use them to drive them to work.

Here is the same data for Sydney:

There are many SA2s with motor vehicle ownership rates around 50 to 70 where the private mode shares are dropping faster than motor vehicle ownership. But there are also many areas with high private mode shares and increasing rates of motor vehicle ownership.

How do the other cities compare? Here are all the SA2s for all cities on the same chart, with alternating highlighted cities:

You can see big differences between the cities, but also that Brisbane and Perth have many SA2s with very high private mode share and rapidly increasing motor vehicle ownership (ie moving up and right, although it’s a little difficult to see with so many lines overlapping). Melbourne and Sydney have plenty of SA2s moving down and left – reducing motor vehicle ownership and declining private transport mode share (which may make some planners proud).

Of course there will be a relationship between motor vehicle ownership and where people choose to live and work. People working in the central city may prefer to live near train stations so they can avoid driving in congested traffic to expensive car parks. People who prefer not to drive might choose to live close to work and/or a frequent public transport line. People who are happy to drive to work in the suburbs might avoid higher priced real estate near train stations or the inner city.

As an aside, we can compare total household motor vehicles to the number of people driving to work, to estimate the proportion of household motor vehicles actually used in the journey to work. Here is Melbourne:

SA2s with a lower estimate are generally nearer the CBD, are wealthier areas, have reasonable public transport accessibility, and/or might be areas with a higher proportion of people not in the workforce (for whatever reason). The areas where the highest proportion of motor vehicles are required for the journey to work are relatively new outer suburbs on the fringe (perhaps suggesting forced car ownership), where adult workforce participation is probably high and public transport accessibility is lower.

The proportion of cars used in the journey to work declined on average in many parts of Melbourne. Given that motor vehicle ownership rates in Melbourne barely changed between 2011 and 2016, this probably represents people mode shifting, rather than people acquiring more motor vehicles even though they don’t need them to drive to work.

Jobs within walking distance of home

It stands to reason that people would be more likely to walk to work if there were more work opportunities within walking distance of their home.

For every SA1 I’ve measured how many jobs are approximately within 1 km as a notional walking catchment (measured as the sum of jobs in destination zones whose centroid are within 1 km of the centroid of each home SA1, so it is not perfect). Here’s the relationship with walking mode share:

(there are a lot of dots overlapping in the bottom left-corner and Adelaide dots have been drawn on top so try not to get thrown by that).

You don’t have to have a lot of nearby jobs to get a higher walking mode share, but if you do, you are very likely to get a high walking more share. The exceptions (many jobs, but low walking share) include many parts of Parramatta (Sydney), and areas separated from nearby jobs by water bodies or other topographical barriers (eg Kangaroo Point in Brisbane).

Workplace distance from the city centre

As was seen in a previous post, workplaces closer to city centres had much lower private transport mode shares, which is unsurprising as these are locations with generally the best public transport accessibility, high land values that can lead to higher car parking prices (which impact commuters who pay them), and often higher traffic congestion.

Here is a chart showing private transport mode share by workplace distance from the city centre. I’ve used faded lines to show 2011 and 2006 results (2006 only available for Sydney and Melbourne).

Here’s a chart that shows the mode shifts between 2011 and 2016:

Inner Melbourne had the biggest mode shifts away from private transport (particularly in Docklands that falls into the 1-2 km range, which saw significant employment and tram service growth), but Sydney had more consistent mode shifts across most distances from the city centre. Adelaide and Canberra saw mode shifts away from private transport in the inner city but towards private transport further out.

Brisbane and Perth saw – on average – a mode shift to private transport across almost all distances from the city centre, with the highest mode shift to private transport in Brisbane actually for the CBD itself(!).

Home distance from the city centre

There’s unquestionably a relationship here too, and it’s probably mostly driven by public transport service levels being roughly proportional to distance from the CBD, but also the proportion of the population who work in the CBD being much higher for homes nearer the CBD.

Sydney had the lowest average private transport mode share at all distances up to 20 km from the CBD, followed by Melbourne and Brisbane, in line with overall mode shares.

The trends over time are also interesting. Brisbane saw mode shifts towards private transport at all distances more than 2 km from the city centre between 2011 and 2016. However there were not significant shifts for Perth outside the city centre – that is: modes shares by geography didn’t change very much. The mode shift away from public transport in Perth is best explained by the shift in jobs balance away from the city centre.

Here are public transport mode shares by home distance from city centres:

In most cities, public transport mode share peaked at a few kilometres from the city (as active transport has a higher mode in the central city).

Here are public transport mode shifts by distance from the city centre between 2011 and 2016:

The significant shift in central Melbourne is likely to be largely explained by the Free Tram Zone introduced in 2015. Outside of the city centre the mode shifts are surprisingly uniform across each city.

Here’s the same chart for 2006-2011, and you can clearly see the impact of the opening of the Mandurah railway line in Perth with significant mode shift beyond 30 km:

Curiously there was a massive shift to public transport for CBD residents in Melbourne (and this is before the free tram zone was introduced).

So which factors best explain the patterns in mode shares across cities?

What we’ve clearly seen is that higher public transport mode shares are seen for journeys to work…

  • to higher density workplaces
  • from areas of lower motor vehicle ownership
  • to workplaces closer to train stations
  • from higher density residential areas
  • from areas around train and busway stations
  • to and from areas closer to city centres (except from the central city where walking takes over)
  • from less wealthy areas (while I haven’t tested this directly, wealth seems to explain a lot of the outliers in the scatter plots)

I’ve listed these roughly in order of the strength of the relationships seen in the data, but I haven’t put them all in a regression model (yet, sorry).

Of course most of these factors are inter-related, so we cannot isolate causation factors. I’m going to run through many of them, because they are often interesting: (note I have sometimes used log scales)

Population density is roughly related to distance from the city centre:

Motor vehicle ownership has a strong relationship with population density (see this post for more analysis):

Motor vehicle ownership has a weaker relationships with distance from the city centre:

Motor vehicle ownership is related to home distance from train stations, except in Adelaide:

Technical note: For this chart (and some below) I’ve calculated average quantities for the variable on the Y axis, as there would otherwise there are too many data points on the chart and it becomes very hard to see the relationship (I would need to show all SA1s because SA2s are too large in terms of distance from stations). The downside is that these style of charts don’t indicate the strength of relationships.

Population weighted density is related to distance from train stations, especially in Melbourne and Sydney, but not at all in Adelaide:

There is a relationship – although not strong – between weighted job density and distance from city centres:

There’s some relationship between average weighted jobs density and distance from train stations, except in Adelaide:

Here’s the same data, but as a scatter plot with a point for each destination zone, scaled by the number of journeys to each destination zone, and a linear Y-axis:

Technical note: the X-axis appears green mostly because Adelaide data points are drawn on top of other cities, but those data points aren’t of much interest.

In most cities, destination zones with high jobs density (over 700 jobs/ha) were only found within 1 km of a train station – with the notable major exception of Adelaide (again!).

(If you are curious, the large Melbourne zone at 1.4 km from a train station and 659 jobs/ha is the Parkville hospital precinct – where incidentally a train station is currently under construction).

There is a relationship between motor vehicle ownership and proximity to busway stations, but it varies between cities:

But there’s not much relationship between population density and proximity to busway stations (except in the immediate vicinity of busway stations in Brisbane):

Final remarks: there’s something about Adelaide’s train network

A few key observations come through clearly about the catchments around Adelaide’s train stations:

  • In aggregate they do not have higher population density, unlike other cities.
  • In aggregate they do not have particularly high public transport mode shares, unlike other cities.
  • In aggregate they do not have lower rates of motor vehicle ownership, unlike other cities.
  • They do not include the area of highest job density in the CBD (a longer walk or transfer to tram or bus is required), unlike other cities.

Few cities have spare land corridors available for new at-grade rapid public transport lines, and so transport planners generally want to make maximum use of the ones they’ve got, before opting for expensive and/or disruptive tunnelling or viaducts solutions. It looks like Adelaide’s rail corridors are not reaching their people-moving potential.

By contrast, Adelaide’s “O-Bahn” busway does go into the job dense heart of the CBD and the busway station catchments do have higher public transport mode share and lower motor vehicle ownership. However they do not have higher population density, possibly because the stations are surrounded by car parks, green space, and one large shopping centre (Tea Tree Plaza).

Mode shares, population densities, and motor vehicle ownership rates would quite probably change significantly if Adelaide could address the fourth issue by building a train station near the centre of the CBD.

In fact, Auckland had a very similar problem with its previous main city station being located away from the centre of the CBD. They fixed that with Britomart station opening in 2003 and train patronage soon rose quite dramatically (off a very low base, and also helped by service upgrades, subsequent electrification, and many other investments).

Should Adelaide do the same? It would certainly not be cheap and you would have to weigh up the costs and benefits.


What might explain journey to work mode shifts in Australia’s largest cities?

Mon 28 May, 2018

[Updated 29 June 2018 with further analysis of parking levies and their impact]

Between 2011 and 2016, journey to work public transport mode shares went up significantly in Melbourne and Sydney but dropped significantly in Perth and Brisbane. Private transport mode shifts did the opposite. Can this be explained by the changing distribution of jobs within cities, or other factors such as changes in transport costs?

In a recent post focused on Brisbane I found that stronger growth in suburban jobs relative to central city jobs could explain around half of the city’s mode shift towards private transport, with other factors (mostly the changes in relative attractiveness of modes) explaining the rest.

So how is job distribution changing in other Australian cities? How much of the mode shifts can be attributed to changing job distribution and how much could be attributed to other factors like changes in transport costs, or increasing employment density?

(for details about how I define public, private and active transport, see the appendix in this post)

How is job distribution changing in Australian cities?

Here’s a view of the changing distribution of all jobs within each city by workplaces distance from the city centre.

(Unfortunately I only have 2006 data for Sydney and Melbourne)

The changes are relatively subtle, but if look at how the bands shift between years, you’ll see increasing centralisation in Sydney but a decentralisation in all other cities between 2011 and 2016.

The strongest decentralisation was in Brisbane and Perth, which also showed the biggest increases in private transport mode share.

However Melbourne saw both a slight decentralisation of jobs and a mode shift away from private transport between 2011 and 2016.

So we need to dig deeper to find out what’s going on here.

How does private mode share vary by distance from the city centre?

The following chart shows private transport mode shares by distance from the city centre for the last two or three censuses for each city. The darkest line for each city is for 2016, with lighter lines being previous years (I only have 2006 data for Melbourne and Sydney).

There’s a clear pattern in all cities that private mode shares are lower in areas closer to the city centre, with Sydney the lowest, followed by Melbourne, Brisbane, Perth, Adelaide, and Canberra (which is also the order of their population size).

Notably Sydney private mode share averaged lower than 90% out as far as 24km from the city centre, whereas Adelaide sees 90% mode shares as close as 2km from the city centre.

If you look carefully you can see that Brisbane increased private transport mode shares in the central city between 2011 and 2016, while private mode shares dropped or were stable in all other cities at most distances.

You can also see that the central city mode shifts away from private transport were largest in Melbourne, something I’ll come back to.

Here’s the same again but for public transport:

Sydney and Melbourne saw mode shifts to public transport at most distances from the city centre, unlike all other cities.

What mode shift can we attribute to changing job distributions?

A city’s mode share (measured by place of work) will be fundamentally impacted by two types of changes between censuses:

  • Changes in the volume of jobs in each SA2 – because different SA2s generally have different mode shares due to factors like proximity to the city centre and public transport access. If there is stronger jobs growth in areas that already had lower private mode shares, you would get a mode shift away from private transport, all other things being equal.
  • Changes in the mode share in each SA2 – because different modes became more or less attractive for commuters between census years. This might be due to changes in public transport service quality, transport infrastructure provision, and relative changes in the cost of public transport, private motoring, and commuter parking. It could also be influenced by broader demographic changes.

For each city I have calculated what the city-level private transport mode share would have been in 2016, had mode shares in each workplace SA2 remained exactly the same as 2011, but the job volumes in each SA2s had still changed. The city level mode shift due to SA2 volume changes is then the difference between this hypothetical 2016 mode share and the 2011 mode share. The remainder of the city-level mode shift between 2011 and 2016 results can then be attributed to mode shifts at the SA2 level.

Here’s a chart showing the mode shift impact of both volume changes at the SA2 level, and mode shifts at the SA2 level:

As we noted above, Sydney saw a slight trend to centralisation of jobs between 2011 and 2016, and it had the largest volume change attributed reduction in private mode share (-0.4%). However other factors were responsible for a further 2.5% of the mode shift away from private transport.

The story is similar in Melbourne but to a smaller magnitude in both aspects. Both of these cities also saw increasing inner city job density – which matters – and I’ll back come to that in a moment.

In Brisbane you can see that the total mode shift towards private transport was roughly equally attributable to SA2 volume changes and SA2 mode shifts (as I discussed in my earlier post).

Perth had an overall 1.3% mode shift to private transport, and the majority of this was due to significant jobs growth in the suburbs compared to the CBD (in fact, the SA2 with the largest jobs growth was Murdoch in the southern suburbs). But there were also other factors that led to a mode shift to private transport.

In Canberra – Queanbeyan, volume changes by themselves would have seen a mode shift to private transport, but other factors were larger and led to an overall mode shift away from private transport (although it is actually complicated because the 2011 census day was in a federal parliamentary sitting week, while 2016 was not).

Nothing much changed in Adelaide.

Next I’m going to explore what could be behind the mode shifts at SA2 level, in terms of job density and real transport costs.

Can increases in workplace density impact mode shares?

As discussed in my Brisbane analysis, if the relative attractiveness of modes hadn’t changed, you might still expect a mode shift to public transport in high density employment areas with increasing jobs numbers because you would expect the cost of parking provision to increase with increasing land use density (i.e. more competition for space).

Indeed, in Sydney and Melbourne a number of inner city SA2s became significantly more job dense between 2011 and 2016, and also saw mode shifts away from private transport:

(inspect this data in Tableau)

A similar thing happened in Civic (the main centre of Canberra).

But Adelaide and Perth saw both declining job density and declining private transport mode share, which suggests something else is at play.

Job density didn’t really go down in Brisbane – see my Brisbane post for an explanation (basically, ABS redrew the SA2 boundary along the Brisbane River).

Could changes in the real cost of transport be causing mode shifts?

The following chart shows the real change in urban transport fares in Australian cities since 2000, as measured by the ABS as part of the Consumer Price Index series (which unfortunately includes public transport, taxis, and “ride share” but is for a representative sample of journeys so hopefully mostly dominated by public transport fares):

The lines are somewhat saw-toothed because public transport fares generally only rise once a year, and become better value in real terms over the course of the following 12 months.

Many cities have seen above-CPI public transport fare increases at various times, most notably Brisbane in 2010-2014. Melbourne has had above CPI fare increases, but also reduced zone 1+2 fares in 2015 which lead to a reduction on the ABS measure (the fare reduction only really applied to people travelling across zones 1 and 2 – which roughly summarised means travel between the outer and inner suburbs). Brisbane fares peaked in 2014, which was followed by a freeze and then a large reduction in 2017.

By contrast, here is the (negative) growth in the cost of “private motoring” (which includes vehicles, fuel and maintenance):

Private motoring costs have declined in real terms since 2000, although they increased a little during the second half of 2017.

The next chart shows the change in ratio between the two costs. Urban transport fares have become less competitive than private motoring over time in all cities:

But if we are looking at changes between census figures, we should probably also look at cost changes between the times of each census. Here’s how prices changed in real terms between the September quarters of 2011 and 2016 (which cover the August census dates):

The real cost of private motoring dropped in all cities, but so did the real “average” cost of urban transport fares in Sydney and Melbourne (the Melbourne drop being mostly around large fare reductions for travel across zones 1 and 2).

The biggest differences in cost changes were in Brisbane and Perth (around 18%), which I think will go a fair way to explaining why these cities had the biggest shifts to private transport attributable to SA2 mode shifts.

Brisbane saw a rapid increase in public transport fares between 2011 and 2014 which is likely to have changed many commuting habits, but those habits may or may not have changed back when fares were subsequently reduced (e.g. if someone bought a car due to fare increases, they may not have subsequently sold their car when fares reduced). Perth certainly had less mode shift at the SA2 level compared to Brisbane, which might support this hypothesis.

What about changes in car parking costs?

The ABS CPI’s private motoring cost index does not include car parking costs – which would be difficult as they vary considerably with geography.

However we do know about central city car parking levies that governments charge in a bid to reduce road congestion and fund inner city transport initiatives. Sydney, Melbourne, and Perth apply levies to central city non-residential car parking spaces, and ultimately these levies will need to be recovered through parking prices.

I’ve calculated these levies in 2017 dollars (adjusting for inflation as measured in June quarters), and here’s how they have changed since 2000:

Melbourne increased its central city parking levy by 40% per space in 2014 (category 1), and created a new lower-priced levy area in some neighbouring areas to the north and south in 2015 (category 2, see map). This is likely to have contributed to the larger mode shifts away from private transport in the central city area of Melbourne compared to most other cities (particularly considering there were similar changes in average private motoring and urban transport fares in Melbourne between 2011 and 2016).

Sydney’s category 1 fee applies in the Sydney CBD area, Milsons Points and North Sydney. It was $2390 in 2017, and has only risen with indexation since 2009 (when it was doubled). A lower category 2 levy applies in the business districts centres of Bondi Junction, Chatswood, Parramatta, and St Leonards.

Perth has an annual licence fee per bay which ranged from $1039 to $1169 in 2017.  The Perth fee was increased by around 167% in 2010, and there were also above-inflation increases from 2014. The fee increased 63% in real terms between 2011 and 2016 for “long stay” spaces, and 69% for “tenant” spaces.

I am not aware of any such fees or levies in place in Brisbane or Adelaide (a proposal for Adelaide was voted down).

So how are CBD parking prices changing?

Unfortunately good data is a little hard to find, but this Colliers Car Parking White Paper provides “average daily rates” for CBDs for 2009-2015, and early bird rates for 2015. I expect most commuters would pay early bird rates – which average between 28% and 62% of daily rates depending on the city (quite some variation!). I’ve adjusted the pre-2015 figures for inflation to be in 2015 dollars:

In real terms, “average daily” parking costs have declined in Melbourne, rocketed up in Brisbane and Canberra, and moved less in Sydney and Perth. I don’t know whether these reflect trends in early bird prices. And we don’t know how prices changed between 2015 and the census year of 2016.

So how much are parking levies contributing to parking prices?

I have to make some assumptions (guesstimates) here. Regular weekdays represent about 60% of the days of the year. If we assume say 80% of the levy is recovered from weekday commuter parking (there generally being less demand for parking on weekends), we can calculate the average weekday commuter cost of the levy to be 27% of the Sydney early bird price, 25% of the Melbourne early bird price, and 15% of the Perth early bird price. Certainly not insignificant.

Here’s a summary of the levy and “average daily” price changes and mode shifts in the central city parking levy areas:

Changes 2011 to 2016
Parking levy area or CBD SA2 Levy real increase Average daily real price change (2011 to 2015) Private mode shift New private trips Private share of new trips
Perth 63% -5% -0.8% -60 -3%
Melbourne – category 1 40% -11% -5.3% 3200 5%
Melbourne – category 2 (new) n/a -6.4% 5315 30%
Sydney CBD 0% +1% -2.6% 6204 9%
Brisbane City SA2 n/a +64% +1.7% 3135 68%
Adelaide SA2 n/a -11% -1.5% 2567 35%
Canberra Civic SA2 n/a +71% -3.2% 746 30%

Firstly, “average daily” parking prices don’t seem to be following the changes in parking levies in Perth and Melbourne (category 1 area). Other factors influencing parking prices will include supply (influenced by competition for real estate and planning rules) and demand (influenced by employment density) with the market ultimately determining prices.

Car park operators appear to be absorbing the increased cost of the levy (although we don’t know the trends in early bird prices so we cannot be entirely sure). But that’s not to say that the levy hasn’t had any impact on prices – for example, the price reductions might have been larger if the levies had not increased.

Secondly, price changes do not appear to be correlated with mode shifts as you might expect (except Canberra). Brisbane prices increased dramatically, but so did private mode share! Price reductions in Perth, Adelaide, and Melbourne did not result in increased private transport shares.

Maybe other factors are driving mode shift away from private transport in those cities. Maybe early bird prices are trending differently to “average daily” prices. Maybe increased traffic congestion persuaded people to shift modes. Maybe there were significant price changes between 2015 and 2016. Maybe most existing public transport users were not aware of reductions in parking prices.

I don’t know what happened to parking prices in the new category 2 areas of Melbourne but there was a large mode shift away from private transport (-6.4%), and they may well be linked. Indeed, Infrastructure Victoria has recently recommended the category 2 area be expanded to include the inner-eastern suburbs of Richmond, South Yarra, Windsor and Prahran. And the Grattan Institute has recommended increasing the levy to match Sydney’s rates.

Curiously, when I look at City of Melbourne Census of Land Use and Employment (CLUE) data, the category 1 area (approximated with CLUE areas) had an increase of only around 367 non-residential parking bays between 2011-12 and 2015-16 (a four year period), a lot less than the additional 3200 private trips, which might suggest increased average occupancy.

Also, it is likely that a significant portion of people who drive to city centres are not paying for their parking costs (eg employer provided car parking). Employers may simply be absorbing price increases.

For more interesting discussion and research about car parking in the City of Melbourne, see a recent discussion paper and background report prepared by Dr Elizabeth Taylor.

Did changes in population distribution impact mode shares?

While this post has been focused on changes by workplace location, it is possible to separate the overall mode shifts into the two components by home location. Here are the results:

In Sydney, Melbourne, and Canberra, stronger population growth in areas that already had low private mode shares in 2011 made a small contribution to overall mode shifts away from private transport. These cities have all seen densifying population in inner city areas better served by public transport.

The distribution of population growth in Perth and Brisbane had a small effect in the opposite direction.

And again, nothing much changed in Adelaide.

What about active transport?

Cycling-only mode share was pretty stable in most cities (except Canberra up 0.2%). Walking-only mode share declined in Sydney (-0.2%), Brisbane (-0.3%), Adelaide (-0.4%), Perth (-0.3%) but was steady in Melbourne and increased in Canberra (+0.2%). So Canberra has the biggest shift to active transport.

Can you summarise all that?

If your head is spinning with all that information, here’s a summary of what some of the major factors could be in each city between 2011 and 2016. I say “could be” because I’ve not looked at every possible factor influencing mode share.

Sydney: the 2.9% mode shift away from private transport was probably mostly to do with increasing job density in employment centres (more on that in my next post), but was also partly by a shift to more centralised jobs, and increasing population density in places well served by public transport.

Melbourne: The 1.8% mode shift away from private transport probably had a fair bit to do with increasing central city job density, the significant spatial expansion of the central city parking levy area and rates (although we don’t know if early bird prices also rose), a reduction in some public transport fares, and strong population growth in areas well served by public transport.

Brisbane: The 1.9% mode shift towards private transport appears roughly half about the decentralisation of jobs, and half the reduced attractiveness of public transport – particularly following significant fare rises between 2010 and 2014, and possibly/arguably declines in service quality.

Perth: The 1.2% mode shift towards private transport was probably mostly due to a decentralisation of jobs, and partly due to public transport becoming less cost competitive with private transport (despite an increase in the central city parking levy). Urban sprawl is probably also a factor.

Adelaide: The 0.2% mode shift to private transport is probably mostly due to public transport becoming less cost competitive with private transport. Changes in job and population distribution, and employment density do not appear to have had a significant impact.

Canberra:  The 1.0% mode shift away from private transport was probably the result of competing forces of higher jobs growth in car-dominated workplace areas with increasing job density in dense employment centres, increasing central city parking prices, higher population growth in areas better served by public transport (and possibly cycling facilities), and also the fact census 2016 was not a parliamentary sitting week while 2011 was (so really, it’s hard to be too sure!).

You might want to add your own views about changes in the service quality of public transport and cycling infrastructure in each city. I also haven’t looked at the impact of major new public transport infrastructure and service initiatives (such as the opening of new train stations), which we know does impact mode shares at a local level (maybe that’s for a future post).

I hope you found this interesting. My next post will look at suburban employment centres, and their role in changing mode shares in cities.


How is the journey to work changing in Melbourne? (2006-2016)

Tue 5 December, 2017

Post last updated 11 May 2018. See end of post for details.

While journeys to work only represents around a quarter of all trips in Melbourne, they represent around 39% of trips in the AM peak (source: VISTA 2012-13). Thanks to the census there is incredibly detailed data available about the journey to work, and who doesn’t like exploring transport data in detail?

Between 2006 and 2016, Melbourne has seen mode shifts away from private transport and walking, and towards public transport and cycling. The following measures are by place of enumeration (and 2011 Significant urban area boundaries):

2006 2011 2016
Public transport (any) 14.16% 16.34% 18.15%
+2.18% +1.82%
Private transport (only) 80.43% 78.16% 76.20%
-2.28% -1.96%
Walk only 3.63% 3.46% 3.47%
-0.18% +0.01%
Bicycle only 1.34% 1.56% 1.63%
+0.23% +0.06%

This post unpacks where mode shifts and trip growth is happening, by home locations, work locations, and home-work pairs. It tries to summarise the spatial distribution of journeys to work in Melbourne. It will also look at the relationship between car parking, job density and mode shares.

I’m afraid this isn’t a short post. So get comfortable, there is much fascinating data to explore about commuting in Melbourne.

Public transport share by home location

Here’s an animated public transport mode share map 2006 to 2016 – you might want to click to enlarge, or view this map in Tableau (be patient it can take some time to load and refresh). For those with some colour-blindness, you can also get colour-blind friendly colour scales in Tableau.

The higher mode shares pretty clearly follow the train lines and the areas covered by trams, with mode share growing around these lines. Public transport mode shares of over 50% can be found in a sizeable patch of Footscray, and pockets of West Footscray, Glenroy, Ormond – Glen Huntly, Murrumbeena, Flemington, Docklands, Carlton, and South Yarra. Larger urban areas with very low public transport mode share can be found around the outer east and south-east of the city, particularly those remote from the rail network.

Here’s a map showing mode shift at SA2 level:

(explore in Tableau)

The biggest shifts to public transport in the middle and outer suburbs were in Wyndham Vale, Tarneit, South Morang, Lynbrook/Lyndhurst, Sanctuary Lakes (Point Cook – East), Truganina / Williams Landing, Rockbank, Pascoe Vale, and Glenroy. That’s almost a roll call of all the new train stations opened between 2011 and 2016. The exceptions are Rockbank (a small community at present which received significantly more frequent trains in 2015), Point Cook East (a bus service was introduced in 2015), and Pascoe Vale / Glenroy (where more people are commuting to the city centre and increasingly by public transport).

Inner suburban areas with high mode shifts include West Footscray, Yarraville, Seddon – Kingsville, Collingwood, Abbotsford, Kensington, Flemington, South Yarra – East, and Brighton. The Melbourne CBD itself had a 13% shift to public transport – and actually a 6% mode shift away from walking (which probably reflects the new Free Tram Zone in the CBD area).

The biggest mode shifts away from public transport (of 1 to 2%) were at Ardeer – Albion, Coburg North, Chelsea – Bonbeach, Seaford, Frankston, Dandenong, Hampton Park – Lynbrook, and Lysterfield. At the 2016 census there were no express trains operating on the Frankston railway line due to level crossing removal works, which might have slightly impacted public transport demand in Frankston, Seaford and Chelsea – Bonbeach. I’m not sure of explanations for the others, but these were not large mode shifts.

Here’s a chart showing mode split over time, by home distance from the CBD:

Public transport mode share by work location

Here’s a map showing work location public transport mode share (Destination Zones with less than 5 travellers per hectare not shown):

It’s no surprise that public transport mode share is highest in the CBD and surrounding area, and lower in the suburbs. But note the scale – public transport mode share falls away extremely quickly as you move away from the city centre.

Private transport mode shares are very high in the middle and outer suburbs:

Large areas of Melbourne have near saturation private transport mode share. In most suburban areas employee parking is likely to be free and public transport would struggle to compete with car travel times, even on congested roads (particularly for buses that are also on those congested roads).

There are some isolated pockets of relatively high public transport mode share in the suburbs, including

  • 34% in a pocket of Caulfield – North (right next to Caulfield Station),
  • 33% in a pocket of Footscray (includes the site of the new State Trustees office tower near the station),
  • 25% in a pocket of Box Hill near the station, and
  • 17% at the Monash University Clayton campus.

Explore the data yourself in Tableau.

Here’s an enlargement of the inner city area:

And here’s a map showing the mode shift between 2011 and 2016 by workplace location (for SA2s with at least 4 jobs per hectare):

The biggest shifts to public transport were in the inner city. The biggest shifts away from public transport were 1.4% in Ormond – Glen Huntly (rail stations temporarily closed) and North Melbourne.

Here’s a closer look at the inner city:

Docklands had the highest mode shift to public transport of 9% (almost all of it involving train) followed by Collingwood with 7%, and Parkville, Southbank, and Abbotsford with 6%.

North Melbourne saw a decline of 1.4% – at the same time private transport mode share and active (only) mode shares increased by 1%.

Another way to slice this data is by distance from the CBD. Here are main mode shares by workplace distance from the centre, over time:

For this and several upcoming pieces of analysis, I have aggregated journeys into three “main mode” categories:

  • Public transport (any trip involving public transport)
  • Private transport (any journey involving private transport that doesn’t also involve public transport)
  • Active transport only (walking or cycling)

Here are the mode shifts by workplace distance from the centre between 2006 and 2016:

The biggest mode shift from private to public transport was for distances of 1-2km from the city centre, which includes Docklands, East Melbourne, most of Southbank, and southern Carlton and Parkville (see here for a reference map). A mode shift to public transport (on average) was seen for workplaces up to 40km from the city centre. The biggest mode shift to active transport was for jobs 2-4 km from the city centre (but do keep in mind that weather can impact active transport mode shares on census day).

What about job density?

Up until now I’ve been looking at mode shifts by geography – but the zones can have very different numbers of commuters. What matters more is the overall change in volumes for different modes. A big mode shift for a small number of journeys can be a smaller trip count than a small mode shift on a large number of journeys.

Firstly, here’s a map of jobs per hectare in Melbourne (well, jobs where someone travelled on census day and stated their mode, so slight underestimates of total employment density):

Outside the city centre, relatively high job density destination zones include:

  • Heidelberg (Austin/Mercy hospitals with 10.2% PT mode share),
  • Monash Medical Centre in Clayton (8.3% PT mode share),
  • Northern Hospital (3.8% PT mode share),
  • Victoria University Footscray Park campus (21.1% PT mode share),
  • Swinburne University Hawthorn (39.8% PT mode share),
  • a pocket of Box Hill (19.9% PT mode share),
  • a zone including the Coles head office in Tooronga (11.2% PT mode share),
  • an area near Camberwell station (26.8% PT mode share),
  • a pocket of Richmond on Church Street (27.8% PT mode share), and
  • a pocket of Richmond containing the Epworth Hospital (39.5% PT mode share).

Explore this map in Tableau.

You’ll probably not be very surprised to see that there is a very strong negative correlation between job density and private transport mode share. The following chart shows the relationship between the two for each Melbourne SA2 with the thin end of each “worm” being 2006 and the thick end 2016 (note: the job density scale is exponential):

Correlation of course is not necessarily causation – high job density doesn’t automatically trigger improved public and active transport options. But parking is likely to be more expensive and/or less plentiful in areas with high employment density, and many employers will be attracted to locations with good public transport access so they can tap into larger labour pools.

The Melbourne CBD SA2 is at the bottom right corner of the chart, if you were wondering.

The Port Melbourne Industrial and Clayton SA2s are relatively high density employment areas with around 90% private transport mode shares.

Here’s a zoom in on the “middle” of the above chart, with added colour and labels to help distinguish the lines:

Not only is there a strong (negative) relationship between job density and private transport mode share, most of these SA2s are moving down and to the right on the chart (with the exception of North Melbourne which saw only small change between 2011 and 2016). However the correlation probably reflects many new jobs being created in areas with good public and active transport access, particularly as Melbourne grows its knowledge economy and employers want access to a wide labour market.

How does private transport mode share relate to car parking provision?

Do more people drive to work if parking is more plentiful where they work?

Thanks to the City of Melbourne’s Census of Land Use and Employment, I can create a chart showing the number of non-residential off-street car parks per 100 employees in the City of Melbourne (which I will refer to as “parking provision” as shorthand):

(see a map of CLUE areas)

Car parking provision per employee has increased in Carlton, North Melbourne and Port Melbourne and decreased in Docklands, West Melbourne (industrial), and Southbank. Docklands had the highest car parking provision in 2002 but this has fallen dramatically and land has been developed for employment usage. Southbank, which borders the CBD, has relatively high car park provisioning – much higher than Docklands and East Melbourne.

Here’s the relationship between parking provision and journey to work private transport mode share between 2006 and 2016:

It’s little surprise to see a strong relationship between the two, although Carlton is seeing increasing parking provision but decreasing private transport mode share (maybe those car parks aren’t priced for commuters?).

If all non-resident off street car parks were used by commuters, then you would expect the private transport mode share to be the same as the car parks per employee ratio.

Private transport mode shares were much the same as parking provision rates in Melbourne CBD, Docklands, and Southbank, suggesting most non-residential car parks are being used by commuters (with the market finding the right price to fill the car parks?). Private transport mode share was higher than car parking provision in East Melbourne, Parkville, South Yarra, North Melbourne, and West Melbourne (industrial). This might be to do with on-street parking and/or more re-use of car parks by shift workers (eg hospital workers).

Port Melbourne parking provision is very high (there is also lots of on-street parking). It’s possible some people park in Port Melbourne and walk across Lorimer Street (the CLUE border) to work in “Docklands” (which includes a significant area just north of Lorimer Street). It’s also likely that many parking spaces are reserved for visitors to businesses. Carlton similarly had higher parking provision than private transport mode share (again, could be priced for visitors).

(Data notes: For 2011, I have taken the average of 2010 and 2012 data as CLUE is conducted every even year. I’ve done a best fit of destinations zones to CLUE areas, which is not always a perfect match)

Where are the new jobs and how did people get to them?

Here’s a map showing the relative number of new jobs per workplace SA2, and the main mode used to reach them:

The biggest growth in jobs was in the CBD (+31,438), followed by Docklands (+22,993), Dandenong (+11,136), and then Richmond (+6,242).

And here’s an enlargement of the inner city:

(explore this data in Tableau)

The CBD added 31,438 jobs, and almost all of those were accounted for by public transport journeys, although 2,630 were by active transport, and only 449 new jobs by private transport (1%).

Likewise most of the growth in Docklands and Southbank was by public transport, and then in several inner suburbs private transport was a minority a new trips.

However, Southbank still has a relatively high private transport mode share of 46% for an area so close to the CBD. The earlier car parking chart showed that Southbank has about one off-street non-residential car park for every two employees. These include over 5000 car parks at the Crown complex alone (with $16 all day commuter parking available as at November 2017). It stands to reason that the high car parking provision could significantly contribute to the relatively high private transport mode share, which is in turn generating large volumes of radial car traffic to the city centre on congested roads. Planning authorities might want to consider this when reviewing applications for new non-residential car parks in Southbank.

Here’s a chart look looking at commuter volumes changes by workplace distance from the CBD (see here for a map of the bands).

(Note: the X-axis is quasi-exponential)

Public transport dominated new journeys to work up to 4km from the city centre. Private transport dominated new journeys to workplaces more than 4km from the city centre – however that doesn’t necessarily mean a mode shift away from public transport if the new trips have a higher public transport mode share than the 2011 trips. Indeed there was a mode shift towards public transport for workplaces in most parts of Melbourne.

Here is a map showing the private transport mode share of net new journeys to work by place of work:

Private transport had the lowest mode share of new jobs in the inner city. As seen on the map, some relative anomalies for their distance from the CBD include Box Hill (64%), Hampton (57%), Brunswick East (34%), Dingley Village (28%), and Albert Park (6%). Explore the data in Tableau.

Where did the new commuters come from and what mode did they use?

Here’s a map showing the (relative) net volume change of private transport journeys to work, by home location:

As you can see many of the new private transport journeys to work commenced in the growth areas, although there were also some substantial numbers from inner suburbs such as South Yarra, Richmond, Braybrook, Maribyrnong and Abbotsford.

There are many middle suburban SA2s with declines. These are also suburbs where there has been population decline – which I suspect are seeing empty nesting (adult children moving out) and people retiring from work. For example Templestowe generated 566 fewer private transport trips, 28 fewer active transport only trips, but only 70 new public transport trips.

Here’s a similar map showing change in public transport journeys:

The biggest increases were from the inner city, with the CBD itself generating the largest number of new public transport trips (including almost 2500 journeys involving tram). However there were a number of new public transport trips from the Wyndham area in the south-west (where new train stations opened).

Here’s a map of the total new trip volume and main mode split:

(explore in Tableau)

You can see that private transport dominates new journeys from the outer suburbs, but less so in the south-west where a new train line was opened. The middle and inner suburbs are hard to see on that map, so here is a zoomed in version:

You can see many areas where private transport accounted for a minority of new trips. Also, around half of new trips in several middle northern suburbs were by public transport.

Here’s how it looks by distance from the city centre:

Public transport dominated new journeys to work for home locations up until 10km from the city centre, was roughly even with private transport from 10km to 20km (hence a net mode shift to public transport). However private transport dominated new commuter journeys beyond 20km – most of which is from urban growth areas. The 24-30 km band covers most of the western and northern growth areas, while the 40km+ band is almost entirely the south-east growth areas.

Here is a view of the private transport mode share of net new trips:

(explore in Tableau)

The pink areas had a net decline in the number of private transport trips (or total trips) generated, so calculating a mode share doesn’t make a lot of sense. There are some areas with 100%+ which means more new private transport trips were generated than total new trips – ie active and/or public transport trips declined.

You can again see that private transport dominated new trips in the most outer suburbs, with notable exceptions in the west:

  • Wyndham in the south-west where two new train stations opened. 41% of new trips from Wyndham Vale and 30% of new trips from Tarneit were by public transport.
  • Sunbury in the north-west, to which the Metro train network was extended in 2012.  Around 37% of new trips from Sunbury -South were by public transport (that’s 307 trips).

How has the distribution of home and work locations in Melbourne changed by distance from the city?

Here’s a chart showing the number of journey to work origins and destinations by distance from the city centre by year. Note the distance intervals are not even, so look for the vertical differences in this chart:

You can see most of the worker population growth (origins) has been in the outer suburbs. The destination (job) growth was much more concentrated in the inner city between 2006 and 2011, but then more evenly distributed across the city in 2016.

The median distance of commuter home locations from the city centre increased from 18.2 km in 2006 to 18.6 km in 2016. The median distance from the city centre of commuter workplaces decreased from 13.3 km in 2006 to 12.8 km in 2011 but then increased back to 13.3 km in 2016.

Here’s another way at looking at the task. I’ve split Melbourne by SA2 distance from the CBD (to create 10km wide rings) for home and work locations (and further split out the CBD as a place of work) to create a matrix. Within each cell of the matrix is a pie chart – the size of which represents the relative number of commuter trips between that home and work ring, and the colours showing the main mode. I’ve then animated it over 2011 and 2016 (to make it five dimensional!).

I think this chart fairly neatly summarises journeys to work in Melbourne:

  • Private transport dominates all journeys that stay more than 5km from the city centre (all but top left corner)
  • Active transport is only significant for commuters who work and live in the same ring (diagonal top left – bottom right), or for trips entirely within 15 km of the centre (six cells in top left corner)
  • Public transport dominates journeys to the CBD, no matter how far away people’s homes are, but the number of such journeys falls away rapidly with home distance from the CBD. Very few people commute from the outer suburbs to the CBD.
  • Private transport commuters are mostly travelling between middle suburbs, not to the CBD or even the to within 5 km of the city. However on average they are travelling towards the centre. This will become clearer shortly.
  • Public transport otherwise only gets 15% or better mode share for trips to within 5 km of the centre or the relatively small number of outward trips from the inner 5km.

Here’s a look at the absolute change in number of trips between the rings:

You can see:

  • A significant growth in private transport trips, particularly within 5 – 25 km from the CBD.
  • A significant growth in public transport trips, mostly to the CBD and areas within 5 km from the CBD.

Where are commuters headed on different modes?

This next analysis looks at the distribution of origins and destinations for people using particular modes, which can be compared to all journeys.

The next chart looks at the distributions of work destinations by main mode for each census year (using a higher resolution set of distances from the CBD).

On the far right is the distribution of jobs across Melbourne (with roughly equal numbers in each distance interval), and then to the left you can see the distribution of workplace locations for people who used particular modes. You can see how different modes are more prominent in different parts of the city.

You might need to click to enlarge to read the detail.

In 2016, trips to within 2km of the city centre accounted for 19% of all journeys, but 62% of public transport journeys, 31% of walking journeys, and only 7% of private transport only journeys.

Train, tram, and bicycle journeys are biased towards the inner city, while private transport only journeys are biased to the outer suburbs. Walking and bus journeys are only slightly biased towards the inner city. This should come as no surprise given the maps above showing high public transport mode shares in the inner city and very high private transport mode shares in most of the rest of the city.

Over time, public transport journeys to work became less likely to be to the central city as public transport gained more trips to the suburbs. However bus journeys to work became more likely to be in the city centre (this probably reflects the significant upgrades in bus services between the Doncaster area and city centre).

Notes on the data:

  • Unless a mode is labelled “only”, then I’ve counted journeys that involved that mode (and possibly other modes).
  • Sorry I don’t have public transport mode specific data for 2006 so there are some blank columns.

Where do commuters using different modes live?

Here’s the same breakdown, but by home distance from the city centre:

Private transport commuters were slightly more likely to come from the middle and outer suburbs. Tram and bicycle commuters were much more likely to come from the inner city. Bus commuters were over-represented in the 15-25 km band – probably dominated by the Doncaster area. Train commuters were over-represented in distances 5-25 km from the city, and under-represented in distances 35 km and beyond. Journeys by both public and private transport were more likely to come from the middle suburbs.

51% of people walking to work live within 5 km of the city centre, and the growth in walking journeys to work has been much stronger in the inner city.

Here’s a chart showing the most common home-work pairs for distance rings from the CBD for public transport journeys. It’s like a pie chart, but rectangular, larger and much easier to label (I haven’t labelled the small boxes in the bottom right hand corner):

You can see the most common combination is from 5-15 kms to 0-5 kms. This is followed by 15-25 to 0-5 kms and 0-5 to 0-5 kms.

Here’s the same for private transport only journeys:


There is a much more even distribution.

Finally, here is the same for active-only journeys to work:

This is much more polarised, with almost 40% of active transport trips being entirely within 5 km of the city centre. The second most common journey is within 5-15km of the city followed by from 5-15 km to 0-5 km.

In future posts I will look at more specific mode shares and shifts in more detail, the relationship between motor vehicle ownership and journey to work mode shares, and much more!

I hope you have found this analysis at least half as interesting as I have.

(note: this post uses data re-issued in December 2017 after ABS pulled the original Place of Work data in November 2017 due to quality concerns)

This post was updated on 24 March 2018 with improved maps. Also, data reported at SA2 level is now as extracted at SA2 level for 2011 and 2016, rather than an aggregation of CD/SA1/DZ data (each of which has small random adjustment for privacy reasons, which amplifies when you aggregate, also some work destinations seem to be coded to an SA2 but not a specific DZ). This does have a small impact, particularly for mode shifts and mode shares of new trips. On 7 April 2018 this post was updated to count journeys by “Other” and “Bicycle, Other” as private transport to ensure completeness of total mode share (we don’t actually know what modes “Other” is, so this isn’t perfect).

This post was further updated on 11 May 2018 to include minor adjustments to DZ workplace counts in 2011 to account for jobs where the SA2 was known but the DZ was not, and to improve mapping from 2011 DZs to 2016 SA2s. Refer to the appendix in the Brisbane post for all the details about the data.


Where are the unoccupied dwellings in Australian cities?

Sat 4 November, 2017

Over one million private dwellings in Australia were unoccupied on census night in 2016 – 11.2% of all private dwellings – up from 10.2% in 2011.

This raises many questions. Where are these unoccupied dwellings and where are they now more prevalent? What type of dwellings are more likely to be unoccupied? How long have these dwellings been unoccupied? Do we know why these dwellings are unoccupied?

This post will focus on dwelling occupancy by geography, dwelling types and trends over time. In a future post I hope look into those last two questions in more detail.

I’ve prepared data for sixteen Australian cities, with various maps in Tableau (you will need to zoom and pan to your city of interest).

Why am I blogging about dwelling occupancy on a transport blog? Well partly because I’m interested in urban issues, but also because land use is very relevant to transport. If dwelling occupancy rates in the inner and middle suburbs were higher, there would be more people living closer to jobs and activities who might be less reliant on private motorised transport for their daily travel.

If you’d like to read more around the associated policy issues, Professor Hal Pawson from UNSW has a good piece in The Conversation highlighting the increasing number of empty properties and spare bedrooms, and advocates  replacing stamp duty with a broad-based land tax to improve housing mobility. Also read Eryk Bagshaw in the Fairfax press, Jonathan Jackson in Finfeed, and a piece in Business Insider where the Commonwealth Bank state that 17% of recently built dwellings are left unoccupied (not sure how that was calculated).

What are the dwelling occupancy rates in Australian cities?

Here’s a chart showing private dwelling occupancy rates for sixteen Australian cities (using 2011 Significant Urban Area boundaries) from the last three censuses:

Note the y-axis only runs from 84% to 94%, so the changes are not massive. However a small change in dwelling occupancy can still have a large impact on housing prices (rental and sales).

The Sunshine and Central Coasts have the lowest occupancy, almost certainly explained by many holiday homes in those regions, although all three have been trending upwards. Curiously, the Gold Coast – Tweed Heads had a significant increase in occupancy between 2011 and 2016 to take it above Perth, Townsville, and Darwin.

Hobart and Cairns also had increased occupancy between 2011 and 2016, but all large cities declined between 2011 and 2016. Perth, Darwin and Townsville had big slides – quite possibly related to the downturn in the mining industry and slowing population growth (all three have seen slowing population growth in recent years after a boom period). Then again, if there are more fly-in-fly-out workers in a city you might expect dwelling occupancy on census night to go down as a portion of them will be away for work on census night.

How does dwelling occupancy in capital cities compare to the rest of the country?

Private dwelling occupancy is significantly lower outside the capital city areas. While the capital city areas contain 63% of all private dwellings, they only contain 51% of unoccupied private dwellings.

How does dwelling occupancy vary by dwelling type?

Here’s a chart of 2016 dwelling occupancy by Greater Capital City Statistical Areas and the most common dwelling types:

In many cities there is a strong correlation between housing type and occupancy, with separate houses having the highest occupancy rates, and multi-storey flats/apartments having the lowest. The pattern is strongest in Perth – perhaps reflecting reduced demand for apartment living following the end of the mining boom(?).

The data suggests higher density apartments are more likely to not be occupied on census night, but it doesn’t tell us why. Of course different dwelling types have different spatial distributions, so is it the dwelling type that drives the occupancy rates? I’ll come back to that shortly.

Where are the unoccupied dwellings?

Quite simply, here is a map showing the density (at SA2 geography) of unoccupied dwellings in Melbourne over time (you might need to click to enlarge to read more clearly):

(I’ve not shaded SA2s with less than 1 unoccupied dwelling per hectare. You can look at other cities in Tableau by zooming out and then in on another city).

You can see a fairly significant increase in the number of unoccupied dwellings in the inner and middle suburbs (at least at densities above 1 per hectare).

From a transport perspective – this isn’t great. If people lived in those dwellings rather than dwellings on the fringe of Melbourne, the transport task would be easier as there would be many more people living closer to jobs and other destinations with non-car modes being more competitive.

But these areas with a relatively high density of unoccupied dwellings are also areas with a high density of dwellings in general. The density of unoccupied dwellings has risen in the same places where total dwelling density has risen:

(see in Tableau – you may need to change the geography type)

Given you would expect a small percentage of dwellings to be unoccupied for good reasons (eg resident temporarily absent, or property on the market), it makes sense that the density of unoccupied dwellings has gone up with total dwelling density.

But a decrease in the dwelling occupancy rate requires the number of unoccupied dwellings to be growing at a faster rate than the total number of dwellings. We already know that is happening at the city level through declining occupancy rates, so how does that look inside cities?

How does dwelling occupancy vary across Melbourne?

Here’s a map of dwelling occupancy in Melbourne and Geelong at CD/SA1 level geography:

(see also in Tableau)

You can see very clearly that occupancy is lowest on Mornington Peninsula beaches to the south – which almost certainly reflects empty holiday homes on census night (a Tuesday night in winter).

In fact, I’ve created a map of dwelling occupancy at SA2 level for all of Australia, and you can see many coastal holiday areas around Melbourne (and other cities) with low occupancy (with Lorne – Anglesea at 32% and Phillip Island at 40%):

The previous Melbourne map at CD/SA1 level is very detailed and so it’s not easy to see the overall trends. Also, apart from the Mornington Peninsula, occupancy rates are almost all above 80%.

So here is a zoomed-in map with a different (narrower) colour scale, with data aggregated at SA2 level (also in Tableau):

Things become much clearer.

The highest dwelling occupancy is generally on the fringe of Melbourne.

Apart from holiday home areas, the lowest occupancy in 2016 was concentrated in wealthier inner suburbs, including Toorak at 83% and South Yarra west at 84%. This was closely followed by the CBD, Docklands, East Melbourne, Southbank, and Albert Park between 84% and 86%. These areas have all had declining occupancy since 2011.

It can be a little difficult to see the changes in occupancy rates, so here is a non-animated map the change in dwelling occupancy rates between 2006 and 2016 (also in Tableau):

There are at least small declines in most parts of Melbourne. The biggest decline was 7% in Bundoora North (with lowest 2016 occupancy of 79% in these new units in University Hill ), followed by 5% in Doncaster (lowest around Doncaster Hill where there are new apartments, perhaps too new to be occupied on census night?), 4% in South Yarra East (lowest in the new apartments around South Yarra Station, again possibly because some are very new) and Prahran – Windsor.

Curiously, Docklands dwelling occupancy increased by 9% from 75% to 85% (rounding means that those numbers don’t perfectly add). Perhaps there were many new yet-to-be-occupied dwellings in 2006? For reference, Dockland’s 2011 occupancy was 84%, only slightly below the 2016 level.

The outer growth areas are a mixed bag of increases and decreases. This possibly depends again on how many brand new but not yet occupied dwellings there were in 2006 and 2016.

What are the dwelling occupancy patterns in other cities?

Sydney

You can see lower occupancy around the CBD, North Sydney, Manly, and the northern beaches, and higher occupancy in the western suburbs.

The largest declines are evident in the city centre and North Ryde – East Ryde:

Brisbane

Brisbane has some big declines to the north-east of the city centre, Rochedale – Burbank, Woodridge, Logan, and Leichhardt – One Mile. The Redland Islands in the east are presumably a popular place for holiday homes.

Perth

Low occupancy is evident around Mandurah in the south (a popular holiday home area). Lower occupancy has spread around the inner city, and beach-side suburbs of Scarborough, Cottesloe, Fremantle, and Rockingham (many of which are areas with higher concentrations of Airbnb properties).

The biggest declines were in Maylands, Victoria Park – Lathlain – Burswood, and South Lake – Cockburn Central. For the first two of these areas the decline was mostly in flats/units/apartments.

Adelaide

The lowest occupancy is on the south coast and in Glenelg. The biggest decline was in Fulham (-5%), followed by Payneham – Felixstowe (-4%):

[Canberra, Hobart and Darwin added 6 November 2017]

Canberra

Dwelling occupancy was lowest around Parliament House (the census was not during a sitting week in 2016), and highest in the outer northern and southern suburbs. The 2006 census was during a sitting week, so it’s little surprise that big dwelling occupancy reductions were seen around Capital Hill between 2006 and 2016.  There was also a 5% decline in Farrer and a 6% growth in Gungahlin between 2006 and 2016 (Gungahlin’s dwellings almost doubled between 2006 and 2011, so the 2006 result might reflect brand new dwellings awaiting occupants).

Hobart

Dwelling occupancy was lowest in central Hobart, with the biggest decline of 4% in Old Beach – Otago, but overall there was little change between 2006 and 2016 (average occupancy did drop slightly in 2011 though).

Darwin

Darwin dwelling occupancy was lowest in the city centre at 82% in 2016, while Howard Springs had 100% occupancy (in 2016). Declines are evident between 2006 and 2016 across most parts of Darwin.

Gold Coast

Here’s a map of 2016 occupancy at SA1 level, with the original broader colour scale:

You can see quite clearly that the beach-side areas have low occupancy, while the inland areas have much higher occupancy (some at 100%). Presumably many permanent residents cannot or choose not to compete with tourism for beach-side living.

Sunshine Coast

Similar patterns are evident on the Sunshine Coast, particularly around Noosa and Sunshine Beach in the north:

If you want to see other cities, move around Australia in Tableau for occupancy maps at CD/SA1 and SA2 geography (choose you year of interest), and occupancy change maps (at SA2 geography).

So are there lots of unoccupied inner city apartments in Melbourne?

Some commentators have spoken about many inner city apartments being unoccupied – perhaps through a glut or investors chasing capital gains and not interested rental incomes.

Here is dwelling occupancy in central Melbourne at SA1 geography for 2016, using the broader colour scale (also in Tableau):

There are quite a few pockets of very low occupancy, particularly areas shaded in yellows and greens. The average private dwelling occupancy for the City of Melbourne local government area was 87%, lower than the Greater Melbourne average of 91%.

The lowest occupancy is a block between Adderley, Spencer and Dudley Street in North Melbourne at 56%, which is probably related to the recent completion of an apartment tower not long before the census (from Google Street view we know it was under construction in April 2015 and completed by October 2016).

There are several patches of yellow  (65-70% occupancy) in the CBD, Docklands and Southbank.

But what about apartment towers? For that we need to drill down to mesh blocks – and thankfully 2016 census data is actually provided at this level.

Here’s a map showing dwelling occupancy of mesh blocks in the City of Melbourne (local government area) with at least 100 dwellings per hectare (as an arbitrary threshold for large apartment building – see the appendix for an example of this density):

(explore in Tableau)

Some notable low occupancy apartment towers include:

  • 48% for an apartment tower at 555 Flinders Street (Northbank Place Central Tower) between Spencer and King Street and the railway viaduct. It wasn’t brand new in 2016.
  • 47% in a block that includes the Melbourne ONE apartment tower, possibly because it was only just opened (as I write there are still apartments for sale)
  • 65% for one of the towers at New Quay, Docklands (which seems to include serviced apartments)
  • 66% for a tower at 28 Southgate Ave (corner City Road), and 67% for the Quay West tower next door (almost certainly popular places for Airbnb / serviced apartments).

Several of these towers include advertised serviced apartments, and I expect the towers would contain a mix of serviced apartments, owner-occupied apartments and rentals (regular and Airbnb). However ABS advises me that field officers do speak to building managers, and are therefore likely to not code serviced apartments as private dwellings.

That said, according to the 2016 census data there were only 11 non-private dwellings in Docklands that were classified as “Hotel, motel, bed and breakfast”, and zero non-private dwellings in the New Quay apartment towers.

I snapped this picture at 9pm on a Sunday in September 2017 of the apartments at New Quay (Docklands) that at the 2016 census had 65-70% occupancy:

Of course you wouldn’t expect lights to be on in all rooms in all occupied dwellings at 9pm on a particular Sunday, but I dare say it’s probably a time when fewer people would be out. It looks like a lot less than a quarter of rooms are lit. I know very few of these are on Airbnb (more on that in a future post!), but I don’t know how many are actually serviced apartments.

There’s huge variation in dwelling occupancy across these mesh blocks. So is the lower occupancy more concentrated in higher density areas? Here’s a scatter plot of all mesh blocks in the City of Melbourne by dwelling density and occupancy:

There’s not a strong relationship between density and occupancy. The variation in dwelling occupancy between mesh blocks will probably depend on a lot of local factors.

What about occupancy by dwelling type for the inner city?

(data points removed where dwelling counts were small, the isolated blue dot at the bottom is for Southbank).

There’s no evidence that flats / apartments have lower occupancy than other housing types in the central city. However there is evidence that inner city areas have relatively lower occupancy.

So how does the occupancy of apartment blocks of 4+ storeys vary across Melbourne?

Box Hill had the lowest apartment occupancy of 50% (perhaps some were brand new?), followed by Ringwood, Glen Waverley, and Brighton in the 70-75% range.  Croydon East, Templestowe , Seddon – Kingsville, Clayton, Carnegie, West Footscray, Braybrook and Frankston reported occupancy above 95%. The inner city areas were around 84-85% occupied, and these would make up the majority of such dwellings in Melbourne.

Apartments in blocks of 4+ storeys seem to have lower occupancy on average because most of them are located in the central city, which generally has lower dwelling occupancy.

Here’s a similar map (with a different colour scale) for dwelling occupancy of separate houses across the Melbourne region:

The lowest rates in metropolitan Melbourne are 82-83% in some inner city areas, while the urban growth shows up in pink and purple, mostly 94-96%.

Explore the 2016 occupancy rates at SA2 geography for different dwelling types for any part of Australia in Tableau. You can also view changes in occupancy rates since 2006 for separate houses, flats/units/apartments, and semi-detached/townhouses.

Why are there lower dwelling occupancy rates in the central city?

The census doesn’t answer this, and I’m not a housing expert, but I dare say there are plenty of plausible explanations:

  • Many dwellings are rented out on Airbnb (and/or other platforms) – but are not in high demand on a weeknight in mid-winter (more on that in this post).
  • Many dwellings are serviced apartments that are indistinguishable from regular private dwellings (in buildings with a mixture of dwelling use). ABS say they don’t count these as private dwellings, however they are not showing up as non-private dwellings.
  • Dwellings are more likely to occupied by executives who travel more frequently.
  • Dwellings might be second homes for people living outside the city.
  • Dwellings might be owned by employers for interstate staff visiting Melbourne.
  • Dwellings might be poorly constructed and uninhabitable (eg mould issues).
  • Investors who are not interested in rental income might deliberately leave properties vacant (something that is disputed).

But I’m just speculating.

What about dwelling occupancy in the centre of other cities?

Here’s a map of the Sydney CBD area at SA1 geography:

There are some very low occupancy rates in the north end of the CBD, but very high occupancy rates around Darling Harbour and Pyrmont.

Here’s central Brisbane:

Here are occupancy rates for different dwelling types for selected inner city SA2s in Sydney, Brisbane, Adelaide and Perth:

In all SA2s except Surrey Hills (Sydney) and South Brisbane, flats or apartments in 4+ storey blocks had the lowest dwelling occupancy in 2016. Only in Perth City SA2 (which is quite a bit larger than the CBD) is there a reasonably clear relationship between housing type and occupancy.

Summary of findings

Couldn’t be bothered reading all of the above, or forgot what you learnt? Here’s a summary of findings:

  • Dwelling occupancy, as measured by the census, has declined in most Australian cities between 2006 and 2016 (particularly larger cities).
  • Dwelling occupancy is generally very low in popular holiday home areas, but also relatively low in central city locations.
  • Dwelling occupancy is generally highest in outer suburban areas.
  • Higher density housing types generally have lower occupancy, but that is probably because they are more often found in inner city areas.
  • There are examples of low occupancy apartment towers in Melbourne, but there’s not a clear relationship between dwelling density and dwelling occupancy in central Melbourne.

In a future post I plan to look more at why properties might be unoccupied, and for how long they are unoccupied, drawing on Airbnb and water usage datasets.  I might also look at bedrooms and bedroom occupancy which is a whole other topic.

 

Appendix – About the census dwelling data

I’ve loaded census data about occupied and unoccupied private dwellings data into Tableau for 2006, 2011, and 2016 censuses for sixteen Australian cities at the CD (2006) / SA1 (2011,2016) level, which the smallest geography available for all censuses. I’ve mapped all these CDs and SA1s to boundaries of 2016 SA2s and 2011 Significant Urban Areas (as per my last post). Those mappings are unfortunately not perfect, particularly for 2006 CDs.

The ABS determine a private dwelling to be occupied if they have information to suggest someone was living in that dwelling on census night (eg a form was returned, or there was some evidence of occupation). Under this definition, unoccupied dwellings include those with usual residents temporarily absent, and those with no usual residents (vacant).

For my detailed maps I’ve only included CDs / SA1s with a density of 2 dwellings per hectare or more.

For reference, here is a Melbourne mesh block with 100 dwellings per hectare:

And here is a mesh block with 206 dwellings per hectare (note only a small part of mesh block footprint contains towers):


Are Australian cities becoming denser?

Tue 5 November, 2013

Please refer to a fully revised second edition of this post – published in April 2019.

[Updated April 2017 with 2015-16 population estimates. First published November 2013]

While Australian cities have been growing outwards with new suburbia, they have also been getting denser in established areas, and the new areas on the fringe are often more dense than growth areas used to be (see last post). So what’s the net effect – are Australian cities getting more or less dense?

This post also explores measures of population-weighted density for Australian cities large and small over time. It also tries to resolve some of the issues in the calculation methodology by using square kilometre geometry, looks at longer term trends for Australian cities, and then compares multiple density measures for Melbourne over time.

Measuring density

Under the traditional measure of density, you’d simply divide the population of a city by the metropolitan area’s area (in hectares). As the boundary of the metropolitan areas seldom change, the average density would simply increase in line with population with this measure. But that density value would also be way below the density at which the average resident lives because of the inclusion of vast swaths of unpopulated land within “metropolitan areas”, and so be not very meaningful.

Enter population-weighted density (which I’ve looked at previously here and here). Population-weighted density takes a weighted average of the density of all parcels of land that make up a city, with each parcel weighted by its population. One way to think about it is the residential density in which the “average resident” lives.

So the large low-density parcels of rural land outside the urbanised area but inside the “metropolitan area” count very little in the weighted average because of their small population relative to the urbanised areas. This means population-weighted density goes a long way to overcoming having to worry about the boundaries of the “urban area” of a city. Indeed, in a previous post I found that removing low density parcels of land had very little impact on calculations of population-weighted density for Australian cities. However, the size of the parcels of land used in a population-weighted density calculation will have an impact, as we will see shortly.

Calculations of population-weighted density can answer the question about whether the “average density” of a city has been increasing or decreasing. But as we will see below, using geographic regions put together by statisticians based on historical boundaries is not always a fair way to compare different cities.

Population-weighted density of Australian cities over time

Firstly, here is a look at population-weighted density of the five largest Australian cities (as defined by ABS Significant Urban Areas), measured at SA2 level (the smallest geography for which there exists a good consistent set of time-series estimates). SA2s roughly equate to suburbs.

According to this data, most cities bottomed out in density in the mid 1990s. Sydney, Melbourne and Brisbane have shown the fastest rates of densification in the last three years.

What about smaller Australian cities? (120,000+ residents in 2014):

Darwin comes out as the third most dense city in Australia on this measure, with Brisbane rising quickly in recent years into fourth place. Most cities have shown densification in recent times, with the main exception being Townsville. On an SA2 level, population weighted density in Perth hardly rose at all in 2015-16 (a year when 92% of population growth was in the outer suburbs)

However, we need to sanity test these values. Old-school suburban areas of Australian cities typically have a density of around 15 persons per hectare, so the values for Geelong, Newcastle, Darwin, Townsville, and Hobart all seem a bit too low for anyone who has visited them. I’d suggest the results may well be an artefact of the arbitrary geographic boundaries used – and this effect would be greater for smaller cities because they would have more SA2s on the interface between urban and rural areas (indeed all of those cities are less than 210,000 in population).

For reference, here are the June 2014 populations of all the above cities:

Australian cities population 2014

The following map shows Hobart, with meshblock boundaries in black (very small blocks indicate urban areas), SA2s in pink, and the Significant Urban Area (SUA) boundary in green.  You can see that many of the SA2s within the Hobart SUA have pockets of dense urban settlement, together with large areas that are non-urban – ie SA2s on the urban/rural interface. The density of these pockets will be washed out because of the size of the SA2s.

Hobart SUA image

Reducing the impact of arbitrary geographic boundaries

As we saw above, the population-weighted density results for smaller cities were very low, and probably not reflective of the actual typical densities, which might be caused by arbitrary geographic boundaries.

Thankfully ABS have followed Europe and released of a square kilometre grid density for Australia which ensures that geographic zones are all the same size. While it is still somewhat arbitrary where exactly this grid falls on any given city, it is arguably less arbitrary than geographic zones that follow traditional notions of area boundaries.

Using that data, I’ve been able to calculate population weighted density for the larger cities of Australia. The following chart shows those values compared to values calculated on SA2 geography:

pop weighted density 2011 grid and SA2 australian cities

You’ll see that the five smaller cities (Newcastle, Hobart, Geelong, Townsville and Cairns) that had very low results at SA2 level get more realistic values on the kilometre grid.

You’ll notice that most cities (except big Melbourne and Sydney) are in the 15 to 18 persons per hectare range, which is around typical Australian suburban density.

While the Hobart figure is higher using the grid geography, it’s still quite low (indeed the lowest of all the cities). You’ll notice on the map above that urban Hobart hugs the quite wide and windy Derwent River, and as such a larger portion of Hobart’s grid squares are likely to contain both urban and water portions – with the water portions washing out the density (pardon the pun!). While most other cities also have some coastline, much more of Hobart’s urban settlement is near to a coastline.

But stepping back, every city has urban/rural and/or urban/water boundaries and the boundary has to be drawn somewhere. So smaller cities are always going to have a higher proportion of their land parcels being on the interface – and this is even more the case if you are using larger parcel sizes. There is also the issue of what “satellite” urban settlements to include within a city which ultimately becomes arbitrary at some point. Perhaps there is some way of adjusting for this interface effect depending on the size of the city, but I’m not going to attempt to resolve it in this post.

International comparisons of population-weighted density

See another post for some international comparisons using square km grids.

Changes in density of larger Australian cities since 1981

We can also calculate population-weighted density back to 1981 using the larger SA3 geography. An SA3 is roughly similar to a local government area (in Melbourne at least), so getting quite large and including more non-urban land. Also, as Significant Urban Areas are defined only at the SA2 level, I need to resort to Greater Capital City Statistical Areas for the next chart:

This shows that most cities were getting less dense in the 1980s (Melbourne quite dramatically), with the notable exception of Perth. I expect these trends could be related to changes in housing/planning policy over time. This calculation has Adelaide ahead of the other smaller cities – which is different ordering to the SA2 calculations above.

On the SA3 level, Perth declined in population-weighted density in 2015-16.

When measured at SA2 level, the four smaller cities had almost the same density in 2011, but at SA3 level, there is more separating them. My guess is that the arbitrary nature of geographic boundaries is having an impact here. Also, the share of SA3s in a city that are on the urban/rural interface is likely to be higher, which again will have more impact for smaller cities. Indeed the trend for the ACT at SA3 level is very different to Canberra at SA2 level.

Melbourne’s population-weighted density over time

I’ve taken a more detailed look at my home city Melbourne, using all available ABS population figures for the geographic units ranging from mesh blocks to SA3s inside “Greater Melbourne” (as defined in 2011) or inside the Melbourne Significant Urban Area (SUA, where marked), to produce the following chart:

Note: I’ve calculated population-weighted density at the SA2 level for both the Greater Capital City Statistical Area (ie “Greater Melbourne”, which includes Bacchus Marsh, Gisborne and Wallan) and the Melbourne Significant Urban Area (slightly smaller), which yield slightly different values.

All of the time series data suggests 1994 was the turning point in Melbourne where the population-weighted density started increasing (not that 1994 was a particularly momentous year – the population-weighted density increased by a whopping 0.0559 persons per hectare in the year to June 1995 (measured at SA2 level for Greater Melbourne)).

You’ll also note that the density values are very different when measured on different geographic units. That’s because larger units include more of a mix of residential and non-residential land. The highest density values are calculated using mesh blocks (MB), which often separate out even small pockets of non-residential land (eg local parks). Indeed 25% of mesh blocks in Australia had zero population, while only 2% of SA1s had zero population (at the 2011 census). At the other end of the scale, SA3s are roughly the size of local councils and include parklands, employment land, rural land, airports, freeways, etc which dilutes their average density.

In the case of SA2 and SA3 units, the same geographic areas have been used in the data for all years. On the other hand, Census Collector Districts (CD) often changed between each five-yearly census, but I am assuming the guidelines for their creation would not have changed significantly.

Now why is a transport blog so interested in density again? There is a suggested relationship between (potential) public transport efficiency and urban density – ie there will be more potential customers per route kilometre in a denser area. In reality longer distance public transport services are going to be mostly serving the larger urban blob that is a city – and these vehicles need to pass large parklands, industrial areas, water bodies, etc to connect urban origins and destinations. The relevant density measure to consider for such services might best be based on larger geographic areas – eg SA3. Buses are more likely to be serving only urbanised areas, and so are perhaps more dependent on residential density – best calculated on a smaller geographic scale, probably km grid (somewhere between SA1 and SA2).

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A detailed look at changes in Melbourne residential density 2006-2011

Mon 8 July, 2013

Since my first post looking at 2011 Melbourne residential density, there’s been a heap of new 2011 census data released. This post includes new maps showing Melbourne’s population density in maximum detail, as well as some more calculations of Melbourne’s urban/residential density for the density nerds.

Melbourne’s residential density in extremely high resolution

2011 population figures are now available for mesh blocks – the smallest ABS geographic unit. This allows a fine-grained look at 2011 residential density, and comparisons with 2006 as we now have a time series.

Here’s a very large animated map (4.7MB, 6825 x 4799 pixels) showing residential density at mesh block level for 2006 and 2011. You’ll need to click on it to download and see the animation (I’d suggest a new tab or window). Use your browser to zoom in and scroll around to areas of interest.

Melbourne mesh block density

 

[update 10 July: It has been brought to my attention that some people are unable to view this map because they are restricted to using certain versions of Internet Explorer. If you cannot see the large map above, I have also created a smaller animated map showing only the inner areas of Melbourne]

You can see that new growth areas on the fringe actually have relatively high densities, contrary to conventional wisdom. I also note a relatively high and increasing density in the Springvale/Keysborough/Noble Park area, quite some distance from the CBD. If you look carefully you will also spot infill developments like Waverley Park, Parkville (ex-Commonwealth Games village), Gresswell Hill in Macleod, Docklands, Maidstone, Edgewater estate in Maribyrnong, along St Kilda Road, Waterways, and no doubt many more.

More values for the urban/residential density of Melbourne

Okay, you might want to stop reading here unless you have a deep interest in density calculation methodology.

Along with mesh blocks, the recently released census data provides boundaries for urban centres and localities, which each representing a relatively continuous urban area (including residential and non-residential land). There is an urban centre of “Melbourne” defined, which excludes the satellite urban centres of Pakenham, Melton, Sunbury, Healesville and towns along the Warburton Highway, but includes the major urban regions along the Mornington Peninsula to Portsea and Hastings.

All this new data enables calculation of yet more values of the urban/residential density of Melbourne, adding to my previous list (some of which I have repeated for comparison purposes). The areas covered by each calculation are shown on the map below.

Geography Area 
(km2)
Population Average density 
(pop/ha)
Areas on map below
“Greater Melbourne” Greater Capital City Statistical Area 9990.5 3,999,982 4.0 white + yellow + green
SA1s within Greater Melbourne with population density > 1 person/ha 2211.4 3,903,450 17.7  (not shown exactly, slightly less than yellow + green)
Mesh blocks within Greater Melbourne, with population density > 1 person/ha 1713.1 3,913,215 22.8  yellow + green
Mesh blocks within Greater Melbourne, with population density > 5 person/ha 1348.5 3,824,999 28.4 green
Melbourne urban centre 2543.2 3,707,530 14.6 all within blue boundary
Mesh blocks within Melbourne urban centre, with population density > 1 person/ha 1443.8 3,696,316 25.6 yellow + green within blue boundary
Mesh blocks within Melbourne urban centre, with population density > 5 person/ha 1238.3 3,642,685 29.4 green within blue boundary

I note that the Melbourne urban centre is approximately a quarter of the area of “Greater Melbourne”.

Here’s a reference map of Melbourne showing the Greater Capital City Statistical Area, Statistical Division and Urban Centre boundaries of “Melbourne”, together with mesh blocks of above 1 and 5 persons/ha.

Density area scope map mesh blocks2

Finally, for the density nerds who are still reading this post, I have calculated the 2011 population-weighted density of Greater Melbourne using mesh blocks to be 42.8 persons/ha, which is much higher than the population-weighted density using SA1 geography of 31.8 persons/ha. It’s higher because more non-residential land parcels have been excluded from the overall calculation. If I restrict myself to mesh blocks within the Melbourne urban centre, the population-weighted density is only slightly higher at 45.1 persons/ha.

So if you want to compare population-weighted densities of different cities, you’ll need to make sure you are using equivalent geographic units, which I suspect would be very difficult for international comparisons. An attempt at Australian and Canadian city comparisons was made in the comments section of a previous post.

There you go. Next time someone claims to know the urban density of Melbourne, you can now argue with them for hours about whether you agree with their number and how it should be measured.