What does the census tell us about motor vehicle ownership in Australian cities? (2006-2016)

Sun 30 July, 2017

With the latest release of census data it’s possible to take a detailed look at motor vehicle ownership in Australian cities.  This post will look at ownership rates across time and space, and compare trends between car ownership, population growth, and population density. And this time I will cover 16 large Australian cities (but with a more detailed look at Melbourne).

I’ve measured motor vehicle ownership as motor vehicles per 100 persons in private occupied dwellings. If you want the boring but important details about how I’ve analysed the data, see the appendix at the end of this post.

I’ve used Tableau Public for this post, so all the charts and maps can be explored, and they cover all sixteen cities.

Is motor vehicle ownership increasing in all cities?

Elsewhere on this blog I’ve shown that motor vehicle ownership is increasing in all Australian states, but what about the cities? Here are the overall results for Australia’s larger cities, on motor vehicles per 100 persons basis. Note that the Y-axis only goes from 54 to 70, so the rate of change looks steeper than it really is.

(you can explore this data in Tableau)

Sydney unsurprisingly has the lowest average motor vehicle ownership, followed by Melbourne, Brisbane (Australia’s third biggest city), and then Cairns and Darwin. Perth was well on top, with Sunshine Coach rapidly increasing to claim second place. Most of the rest were around 66-68 motor vehicles per 100 persons in 2016.

But Melbourne is showing a very different trend to most other cities, with hardly any increase in ownership rate across the ten years (also, Canberra-Queanbeyan saw very little growth between 2011 and 2016).

At first I wondered whether Melbourne was a data error. However, I did the one data extract for all cities for both population and motor vehicle responses, and I’ve also checked for any potential duplicate SA1s. So I’m confident something very different is happening in Melbourne.

So let’s have a look at Melbourne in more spatial detail, starting with maximum detail over time:

(you can zoom in and explore this data in Tableau).

You can see lower ownership in the inner city, inner north, inner west, and the more socio-economically disadvantaged suburbs in the north and south-east. You can also see lower motor vehicle ownership around train lines in many middle suburbs. Other pockets of low motor vehicle ownership are in Clayton (presumably associated with university students) and Box Hill, and curiously some of the growth areas in the west and north. Very high motor vehicle ownership can be seen in wealthier areas and the outer east.

It’s a bit hard to see the trends with such a detailed map, so here’s a view aggregated at SA2 level (SA2s are roughly suburb-sized).

No doubt you are probably distracted by the changes in the legend. That’s because in 2006 there were no SA2s in the <20 and 30-40 ranges at all, and the 30-40 range is only present in 2016. That is, the legend has to expand over time to take into account SA2s with lower motor vehicle ownership rates.

You’ll notice a lot more light blue and green SA2s around the city centre, plus Clayton in the middle south-east switches to green in 2016.

Looking at it spatially, more areas appear to have increasing rather than decreasing motor vehicle ownership. But not all SA2s have the same population – or more particularly – the same population growth. So we need to look at the data in a non-spatial way.

Here’s a plot of population and motor vehicle ownership for all Melbourne SA2s, with the thin end of each “worm” being 2006 and the thick end being 2016.

Okay yes that does looks like a lot of scribbles (and you can explore the data in Tableau to find out what is what), but take a look at the patterns. There are lots of short worms heading to the right – these have very little population growth but some growth in motor vehicle ownership. Then there are lots of long worms that are heading up and to the left – which means large population growth and mostly declining motor vehicle ownership.

Here’s a similar view, but with a Y-axis of change in population since 2006:

(explore in Tableau)

The worms heading up and to the left include both inner city areas and outer growth areas. These areas seem to balance out the rest of Melbourne resulting in a stable ownership rate overall.

Some SA2s that are moving up and to the right more than others include Sunbury – South, Langwarrin, and Mount Martha. And there are a few in population decline like Endeavour Hills – South, Mill Park – South, and Keilor Downs.

The inner city results are not surprising, but declining ownership in outer growth areas is a little more surprising.

Is this to do with growth areas being popular with young families, and therefore containing proportionately more children?

Here’s a map of the percent of the population in each CD/SA1 that is aged 18-84 (ie approximately of “driving age”):

(view in Tableau)

The rates are highest in the central city and lowest in urban growth areas. And if you watch the animation closely, you’ll see areas that were “fringe growth” in 2006 have since had increasing portions of population aged 18-84, presumably as the children of the first residents have reached driving age (and/or moved out).

So what is happening with motor vehicles per 100 persons aged 18-84? Is there high motor vehicle ownership amongst driving aged people in growth areas?

Yes, a lot of growth areas are in the 80-85 range, similar to many middle suburban areas (view in Tableau)

Here’s the same thing but aggregated to SA2 level (explore in Tableau):

Motor vehicle ownership rates in most growth areas are similar to many established middle suburbs, but lower than non-growth fringe areas which show “saturated” levels of ownership (where there is roughly a one motor vehicle per person aged 18-84), particularly the outer east.

However in the outer growth areas of Sunbury (north-west) and Doreen (north-north-east), ownership rates are close to saturation in 2016.

But is the rate of motor vehicle ownership still declining amongst persons aged 18-84 in the outer growth areas? Here’s a similar chart to the previous one, but with ownership by persons aged 18-84 (explore in Tableau):

You can see most of the outer growth areas still have declining ownership rates. You can also see some established suburbs with strong population growth and increased ownership, including Dandenong and Braybrook (which includes the rapidly densifying suburbs of Maidstone and Maribyrnong).

Here’s a spatial view of the changes in ownership rates (area shading), as well as total changes in the household motor vehicle fleet (dots ). (I’ve assumed non-reporting private dwellings have the same average motor vehicle ownership as reporting dwellings in each area).

(explore in Tableau)

You can see outer growth areas shaded green (declining ownership), but also with large dots (large fleet growth).

But also you can see some declines in ownership in the middle eastern and north-eastern suburbs, and some non-growth outer suburbs, which is quite surprising. I’m not quite sure what might explain that.

You’ll also notice the scale for the dots starts at -830, which accommodates Wheelers Hill (in the middle south-east) where there has been a 2% decline in population, and 6% decline in motor vehicle fleet.

Okay, so that’s Melbourne, what about ownership rates amongst “driving aged” people in other cities?

Trends in motor vehicles per persons aged 18-84

(explore in Tableau)

The trends are similar, but Melbourne is even more interesting on this measure. It has declined from 81.3 to 80.7, bucking the trend of all other cities (although Canberra only grew from 88.4 in 2011 to 88.5 in 2016).

How does motor vehicle ownership relate to density?

Here’s a chart showing population weighted density and motor vehicle ownership for persons aged 18-84 for SA2s across all the big cities in 2016 (explore in Tableau):

Some dots (central Melbourne and Sydney) are off the chart so you can see patterns in the rest. I’ve labelled some of the outliers. The general pattern shows higher density areas generally having lower motor vehicle ownership.

Is densification related to lower motor vehicle ownership?

Here’s a chart showing how each city has moved in terms of population-weighted density (measured at CD or SA1 level) and ownership for persons aged 18-84, with the thick end of each worm 2016, and the thin end 2006.

(Note that the 2006 population weighted density figures are not perfectly comparable with 2011 and 2016 because they are measured at CD level rather than SA1 level, and CDs are slightly larger on average than SA1s)

(explore in Tableau)

You can see Sydney is a completely different city on these measures, and also that Melbourne is the only city heading to the left of the chart. Canberra is also bucking the trend between 2011 and 2016.

We can look at this within cities too. Here’s all the Local Government Areas (LGAs) for all the cities (note: City of Sydney and City of Melbourne are off the top-left of the chart)

(explore in Tableau)

Many Melbourne and Sydney LGAs are rising sharply with mostly declining motor vehicle ownership. But then there are Sydney LGAs like Woollahra, Mosman and Northern Beaches in Sydney that are showing increasing motor vehicle ownership while they densify (probably not great for traffic congestion!).

And we can then look inside cities. Here is Melbourne (again, several inner city SA2s are off the chart):

Some interesting outliers include:

  • The relatively dense Port Melbourne, Albert Park, Elwood with relatively high motor vehicle ownership.
  • The land-locked suburb of Gowanbrae with medium density but rapidly increasing car ownership (which has a limited Monday to Saturday bus service).
  • The growth area of Cranbourne South with reasonable density but more than saturated car ownership.
  • Relatively medium dense but low motor vehicle ownership of Clayton and Footscray.

Explore your own city in Tableau. You know you want to.

What are the spatial patterns of motor vehicle ownership in other cities?

The detail above has focussed on Melbourne, so here are some maps for others cities. You can explore any of the cities by zooming in from this Tableau map (be warned: it may take some time to load as I’ve ignored Tableau’s recommendations about how many showing more than 10,000 data points!). In fact for any of the maps you’ve seen on this blog, you can pan and zoom to see other cities.

To help see the changes in motor vehicle ownership between censuses more easily, I’ve prepared the following detailed animations.

Sydney

 

Brisbane

 

Adelaide

Perth

(Find Mandurah in Tableau)

Canberra

Hobart

Darwin

Cairns

Townsville

Sunshine Coast

Geelong

Central Coast (NSW)

Newcastle – Maitland

This post has only looked at spatial trends and the relationship with population density. There’s plenty more to explore about car ownership with census data, which I aim to cover in future posts.

I hope you’ve enjoyed this post, and found the interactive data at least half as fascinating as I have.

Oh, and sorry about some of the maps showing defunct train lines. I’m using what I can get from the WMS feed from Geoscience Australia.

Appendix – About the data

The Australian census includes the following question about how many registered motor vehicles were present at each occupied private dwelling on census night. This excludes motorcycles but includes some vehicles other than cars (probably mostly light vehicles).

96% of people counted in the 2016 census were in a private dwelling on census night, and 93.6% of occupied dwellings filled in the census and gave an answer to the motor vehicle question. So the data can give a very detailed – and hopefully quite accurate – picture.

I’ve used two measures of motor vehicle ownership:

  • Motor vehicles per 100 population (often referred to as “motorisation” in Europe), and
  • Motor vehicles per 100 persons aged 18-84

The first is easy to measure and easily comparable with other jurisdictions, but the second gives a better feel for what proportion of the “driving aged” population own a car. In an area with good alternatives to private transport, you might expect lower ownership rates.

Setting the lower age threshold at 18 works well for Victoria (imperfectly for other states with a lower licensing age), and 84 is an arbitrary threshold during the general decline in drivers license ownership by older people. So it’s not perfect, but is indicative, and certainly takes most children out of the equation.

As the motor vehicle question is based on what was parked at the dwelling on census night, I’ve used population present on census night (place of enumeration). That works well if someone was absent on census night and took their car with them, but not so well if they were absent and left their car behind (e.g. they took a taxi to the airport). You cannot win with that, but the census is timed in August during school and university term to try to minimise absences.

When calculating ownership rates, I’ve excluded people in dwellings that did not answer the motor vehicle question, and people in non-private dwellings. This is more robust than assumptions I made in previous posts on this topic so results will vary a little.

For 2011 and 2016, the census data provides counts of the number of dwellings with 0, 1, 2, 3, .. , 29 motor vehicles, and then bundles the rest as “30 of more”. For want of a better assumption, I’ve assumed dwellings with 30 or more motor vehicles have an average of 31 motor vehicles, which is probably conservative. But these are so rare they shouldn’t make any noticeable difference on the overall results.

As shorthand, I’ve referred to “motor vehicle ownership” rates, but you’ll note the census question includes company vehicles kept at home, so it’s not a perfect term to use, but then company vehicles are often available for general use.

I’ve used the 2011 boundaries of Significant Urban Areas (SUA) for each city, which are made up of SA2s and leave a good amount of room for urban fringe growth in 2016. However they do exclude some satellite towns (such as Melton, west of Melbourne).

I’ve extracted data at SA1 level geography for 2011 and 2016, and Collector District (CD) geography for 2006. In urban areas, SA1s average around 400 people while the older Collector Districts of 2006 averaged around 550 people. These are the smallest geographies for which motor vehicle and age data is available in each census. ABS do introduce some small data randomisation to protect privacy so there will be a little error well summing up lots of parcels.

I’ve generally excluded parcels with less than 5 people per hectare as an (arbitrary) threshold for “urban” residential areas. I’ve mapped all parcels to the 2016 boundaries of Local Government Areas and SA2s, and the 2011 boundaries of SUAs (2016 boundaries have not yet been released). Where boundaries do not line up perfectly, I’ve included a parcel in an SAU, LGA, or SA2 if more than 51% of the parcel’s area is within that boundary. The mapping isn’t perfect in all cases, particularly for growth area SA2s and 2006 CDs. See the alignments for SA2s, LGAs in Tableau.

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Comparing the densities of Australian, European, Canadian, and New Zealand cities

Thu 26 November, 2015

[updated March 2016 to add Canadian and New Zealand cities]

Just how much denser are European cities compared to Australian cities? What about Canadian and New Zealand cities? And does Australian style suburbia exist in European cities?

This post calculates the population-weighted density of 53 Australian, European, and Canadian cities with a population over 1 million, plus the three largest New Zealand cities (only Auckland is over 1 million population). It also shows a breakdown of the densities at which these cities’ residents live, and includes a set of density maps with identical scale and density shading.

Why Population Weighted Density?

As discussed in previous posts, population-weighted density attempts to measure the density at which the average city resident lives. Rather than divide the total population of a city by the entire city area (which usually includes large amounts of sparsely populated land), population weighted density is a weighted average of population density of all the parcels that make up the city. As I’ve shown previously, the size of the parcels used makes a big difference in the calculation of population-weighted density, which makes comparing cities difficult internationally.

To overcome the issue of different parcel sizes, I’ve used kilometre grid population data that is now available for both Europe and Australia. I’ve also generated my own kilometre population grids for Canadian and New Zealand cities by proportionally summing populations of the smallest census parcels available.

Some measures of density exclude all non-residential land, but the square kilometre grid approach means that partially populated grid parcels are counted, and many of these parcels will include non-residential land, and possibly even large amounts of water. It’s not perfect, particularly for cities with small footprints. For example, here is a density map around Sydney harbour (where light green is lower density, dark green is medium density and red is higher density):

Sydney harbour

You can see that many of the grid cells that include significant amounts of water show a lower density, when it fact the population of those cells are contained within the non-water parts of the grid cell. The more watery cells, the lower the calculated density. This is could count against a city like Sydney with a large harbour.

Defining cities

The second challenge with these calculations is a definition of the city limits. For Australia I’ve used Urban Centre boundaries, which attempt to include contiguous urbanised areas (read the full definition). For Europe I’ve used 2011 Morphological Urban Areas, which have fairly similar rules for boundaries. For Canada I’ve used Population Centre, and for New Zealand I’ve used Urban Areas.

These methodologies tend to exclude satellite towns of cities (less so in New Zealand and Canada). While these boundaries are not determined in the exactly the same way, one good thing about population-weighted density is that parcels of land that have very little population don’t have much impact on the overall result (because their low population has little weighting).

For each city, I’ve included every grid cell where the centroid of that cell is within the defined boundaries of the city. Yes that’s slightly arbitrary and not ideal for cities with dense cores on coastlines, but at least I’ve been consistent. It also means some of the cells around the boundary are excluded from the calculation, which to some extent offsets the coastline issues. It also means the values for Australian cities are slightly different to a previous post.

All source data is dated 2011, except for France which is 2010, and New Zealand which is 2013.

Comparing population-weighted density of Australian, European, Canadian and New Zealand cities

AU EU CA NZ Population Weighted Density

You can see the five Australian cities are all at the bottom, most UK cities are in the bottom third, and the four large Spanish cities are within the top seven.

Sydney is not far below Glasgow and Helsinki. Adelaide, Perth and Brisbane are nothing like the European cities when it comes to (average) population-weighted density.

Three Canadian cities (Vancouver, Toronto and Montreal) are mid-range, while the other three are more comparable with Australia. Of the New Zealand cities, Auckland is surprisingly more dense than Melbourne. Wellington is more dense that Vancouver (both topographically constrained cities).

But these figures are only averages, which makes we wonder…

How much diversity is there in urban density?

The following chart shows the proportion of each city’s population that lives at various urban density ranges:

AU EU CA NZ urban density distribution

Because of the massive variations in density, I had to break the scale interval sizes at 100 persons per hectare, and even then, the low density Australian cities are almost entirely composed of the bottom two intervals. You can see a lot of density diversity across European cities, and very little in Australian cities, except perhaps for Sydney.

You can also see that only 10% of Barcelona has an urban density similar to Perth or Adelaide. Which makes me wonder…

Do many people in European cities live at typical Australian suburban densities?

Do many Europeans living in cities live in detached dwellings with backyards, as is so common in Australian cities?

To try to answer this question, I’ve calculated the percentage of the population of each city that lives at between 10 and 30 people per hectare, which is a generous interpretation of typical Australian “suburbia”.

AU EU CA NZ cities percent at 10 to 30 per hectare

It’s a minority of the population in all European cities (and even for Sydney). But it does exist. Here are examples of Australian-style suburbia in outer Hamburg, Berlin, LondonMilan, and even Barcelona (though I hate to think what some of the property prices might be!)

How different is population-weighted density from regular density?

Now that I’ve got a large sample of cities, I can compare regular density with population weighted densities (PWD):

PWD v regular density 2

The correlation is relatively high, but there are plenty of outliers, and rankings are very different. Rome has a regular density of 18, but a PWD of 89, while London has a regular density of 41 and PWD of 80. Dublin’s regular density of 31 is relatively close to its PWD of 47.

Wellington’s regular density is 17, but its PWD is 49 (though the New Zealand cities regular density values are impacted by larger inclusions of non-urbanised land within definitions of Urban Areas).

So what does the density of these cities look like on a map?

The following maps are all at the same scale both geographically and for density shading. The blue outlines are urban area boundaries, and the black lines represent rail lines (passenger or otherwise, and including some tramways). The density values are in persons per square kilometre (1000 persons per square kilometre = 10 persons per hectare). (Apologies for not having coastlines and for some of the blue labels being difficult to read).

Here’s Barcelona (and several neighbouring towns), Europe’s densest large city, hemmed in by hills and a coastline:

Barcelona

At the other extreme, here is Perth, a sea of low density and the only city that doesn’t fit on one tile at the same scale as the other cities (Mandurah is cut off in the south):

 

Perth

Here is Paris, where you can see the small high density inner core matches the high density Metro railway area:

Paris

Similarly the dense inner core of London correlates with the inner area covered by a mesh of radial and orbital railways, with relatively lower density outer London more dominated by radial railways:

London

There are many more interesting patterns in other cities.

What does this mean for transport?

Few people would disagree that higher population densities increase the viability of high frequency public transport services, and enable higher non-car mode shares – all other things being equal. But many (notably including the late Paul Mees) would argue that “density is not destiny” – and that careful design of public and active transport systems is critical to transport outcomes.

Zurich is a city often lauded for the high quality of its public transport system, and its population weighted density is 51 persons/ha (calculated on the kilometre grid data for a population of 768,000 people) – which is quite low relative to larger European cities.

In a future post I’ll look at the relationship between population-weighted density and transport mode shares in European cities.

All the density maps

Finally, here is a gallery of grid density maps of all the cities for your perusing pleasure (plus Zurich, plus many smaller neighbouring cities that fit onto the maps). All maps have the same scale and density shading colours.

Please note that the New Zealand and Canada maps do not include all nearby urbanised areas. Apologies that the formats are not all identical.


Are Australian cities becoming denser?

Tue 5 November, 2013

[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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How commuters got to workplaces in Brisbane, 2006 and 2011

Sat 17 November, 2012

My last post about Brisbane journey to work focussed on where people live. This post focuses on where people work and what modes of transport they use to get there. It covers employment density, mode shares by work locations, and mode shares for people travelling to the CBD.

ABS data about mode shares at work place locations is available for Statistical Local Areas (SLA) in 2006, and for Statistical Area Level 2 (SA2) geography in 2011. These are the smallest available areas in each year, and unfortunately SLA level data was not available at the time of posting for 2011 (to enable a direct comparison on the same areas).

Fortunately for Brisbane, there is a lot of similarity between the two sets of boundaries (some SLAs split, some combined, some restructured).

The following maps alternate between 2006 and 2011 using the slightly different boundaries. You will need to click on them to enlarge and see the animation.

Caution is needed when making inferences when the geographies change as different areas will have different numbers of employees. For example: If two SLAs with 2% and 10% mode shares (in 2006) were combined into a new (2011) SA2 area with 11% mode share (in 2011), it doesn’t mean that mode share actually changed from 2% to 11% in the first of the SLAs. It may be that many more people were employed in the SLA with 10% mode share and actually very little changed overall.

Employment density

Firstly, what does the employment density of Brisbane look like? If I had the travel zone data available (as per Sydney), I’d be able to draw a much higher resolution picture, but for now I will have to suffice with SLA/SA2 employment density:

A lot of the differences you can see between 2006 and 2011 are to do with the change in boundaries, not necessarily changes on the ground. For example, there are many more SA2s than SLAs in the Ipswich area, which has meant the 2011 data shows a slightly dense area in the centre of Ipswich.

Some places where the SLA and SA2s are the same and a change in employment density is evident include reductions in New Farm, West End, Mitchelton, Wynnum, and Chermside West, and an increase in Enoggara.

Mode share by workplace location

I’ve zoomed in on the inner parts of Brisbane so you can see the inner city details for mode shares (apologies for the lack of place names – I figured the numbers showing the mode shares might be more interesting).

First up, public transport mode share:

Public transport mode share was highest in the CBD, then for areas around the CBD and stretching to a little more to the inner south-west. Curiously, public transport mode share was relatively high in suburban Carindale (the patch of yellow turned green in the “middle” eastern suburbs) and Nundah in the middle northern suburbs.

Significant rises in PT mode share were evident in the following places:

  • Fairfield/Dutton Park – which went from 7%/9% to 23%, which is probably related to the Boggo Road busway and green bridge and route 196 BUZ route.
  • Chelmer (6% to 12%) – perhaps related to train frequency upgrades on the line to Darra
  • Teneriffe (10% to 20%) – although it was absorbed into Newstead-Bowen Hills in 2011 the two SLAs combined into one SA2 had a similar number of employees in 2006. In 2011 Teneriffe was served by a new CityCat ferry terminal, and bus services were upgraded (including the CityGlider bus).
  • Kelvin Road – Herston, which went from 14%/16% to 21% (including the growing Kelvin Grove Urban Village and bolstered by the northern busway)

Next is active transport:

There was very little change in active transport mode share by destination. The exceptions were St Lucia (including University of Queensland) which increased from 13% to 16%, and Highgate Hill which went from 9% to 13%. These areas are connected by the new green bridge (buses, walkers and cyclists only) which would have made it easier to reach these places by active transport.

Enoggera records 13% in both 2006 and 2011, which is explained by the existence of a major army barracks there. I’m not sure why the Anstead area had a 15% mode share in 2006 (it was blended out in 2011 with the change of geography).

Finally, here is sustainable transport mode share (public transport + active only transport):

Suburban destinations with high sustainable transport mode share include:

  • Robertson (which includes Griffith University went from 13% to 17%)
  • Carindale (eastern suburbs, 14% to 17%)
  • Taigum/Fitzgibbon (north suburbs, steady 12%)
  • Mount Ommaney (south-western suburbs, 13% in 2006 but unclear in 2011 due to larger SA2)

The significant rises are covered by the discussion above.

Commuting to the CBD

The Central Business District (CBD) is an important destination as it has the highest employment density, and public transport is probably best placed to compete against the car. For this analysis I am defining the “CBD” as the Brisbane City SA2, which is bounded by Hale Street in the west, Wickham Terrace in the north, Boundary Street in the north-east, and the Brisbane River (here is a map). That’s probably bigger than what you might call the core CBD, but unfortunately I cannot obtain 2011 data at a smaller geography.

Brisbane’s CBD accounted for 15.5% of Greater Brisbane journey to work destinations in 2011, and 14.1% of Brisbane Statistical Division destinations in 2006 (Greater Brisbane is slightly larger than the Brisbane Statistical Division). There were 9.5% more journey to work destinations in the CBD in 2011 compared to 2006.

Here’s a map showing the proportion of commuters who had a destination of the Brisbane CBD in 2011 (by home location at SA1 geography):

The prevalence of the CBD as a work destination is almost directly proportional to the distance people live from the CBD, with the notable exception of Springfield in the southern suburbs.

The next map shows the portion of CBD commuters who used public transport in their journey to work (by home location). I’ve only shaded SA1s with 20 or more CBD commuters, which is quite small for calculating mode shares.

Note: I have not filtered SA1s by density on these maps (unlike others), so some low density SA1s to the south-west of the CBD are included in the following maps.

Public transport mode share was particularly high for those further from the CBD (where such a long drive would probably not be fun or cheap). It was lowest around the CBD itself (presumably the locals just walked to work), a few scattered suburban locations, and around the wealthy and low density Pullenvale area to the south-west (served only infrequently by public transport but not that far from the CBD).

Here’s the share of people who only used private motorised transport to commute to the CBD:

Pockets of high private motorised transport mode share include:

  • Hamilton/Albion
  • Bardon
  • Kenmore
  • Fig Tree Pocket
  • Capalaba
  • Gumdale
  • Tingalpa
  • Yeronga
  • Indooroopilly
  • Pullenvale

I understand that many of these are relatively wealthy areas.

Mode shift in journeys to the CBD

How have mode shares changed for journeys to work in the CBD?

Public and active transport increased their mode shares considerably over the 10 years. In fact, the Brisbane CBD had the second highest mode shift to public transport (in percentage terms) of major Australian CBDs (behind Perth, more on that in a future post).

The absolute number of car driver trips fell from 26,397 in 2001 to 23,244 in 2011, while the number of public transport trips shot up from 47,208 in 2001 to 65,570 in 2011 – a 39% increase (a very similar increase to Melbourne and Adelaide). In the same time, South East Queensland public transport patronage grew by 59%.

The vast majority of people who used public transport to commute to the CBD only used one mode of public transport. However, the percentage of people using multiple public transport modes rose from 2.7% in 2001 to 2.9% in 2006 and 3.6% in 2011, suggesting integrated ticketing may be influencing public transport travel behaviour. That said, Brisbane’s CBD still had the lowest rate of multiple public transport mode journeys to work of the CBDs of Australia’s five biggest cities (more on that soon).

 

I’d like to acknowledge Jane Hornibrook for assistance with this post.


Spatial changes in Brisbane journey to work 2006-2011

Sun 4 November, 2012

How have mode shares of journeys to work from different home locations changed in Brisbane? What impact have recent bus service level improvements had?

In my post on city level mode share changes we saw that Brisbane had a 1.2% mode shift to public transport between 2006 and 2011. This post will uncover which areas shifted the most.

The following animations show various mode shares for journeys to work from census collection districts for 2006 and Statistical Area Level 1 (SA1) for 2011. These are the smallest geographies available for each census. All the data is by place of usual residence.

I’ve animated each image to alternate between 2006 and 2011, so you can gaze at them and spot the changes. You’ll need to click on them to enlarge and see the animation.

Public transport

You can mode shift in the inner suburbs, The Gap, the Albany Creek area, around Shorncliffe, the middle southern suburbs (between Yeerongpilly and Woodridge), and the strip towards Shailer Park. Much less mode shift is evident in the outer suburbs, particularly Ipswitch, Victoria Point, Cleveland, and Redcliffe. The Springfield growth area shows higher mode shares than average for urban fringe areas without heavy rail.

Sustainable transport (only)

This map excludes those who used private transport to reach public transport. In most outer suburbs of Brisbane, it seems the vast majority of people are using private motorised transport as part of their journey to work, including to get to train or busway stations.

Train

Significant mode shift can be seen along the Ferny Grove line, the Shorncliffe line, and the line towards Darra. I can see little mode shift on other lines.

There was modest mode shift towards train in the Inala area (near the Richlands rail line that opened in early 2011). Perhaps it will take some time for commuting patterns to change to take advantage of the rail line?

Note that a significant share of people in Springfield used trains. They will be getting a train closer to home when the rail line extension from Richlands to Springfield opens in 2014. It appears that only a few of them got to the train by feeder bus, as the next map shows.

Bus

There was significant shift to bus use in the southern suburbs, particularly around the South East Busway (shown in purple). This busway opened in 2001, but it seems mode shift has continued. There was also strong shift in South Brisbane and the West End (where the high frequency CityGlider bus was introduced), out to The Gap, to the inner south-west, the inner northern suburbs between the train lines, and south through Calamvale (north of Browns Plains, now served by high service “BUZ” bus routes using the South East Busway). There was little shift to using buses in the outer suburbs, other than in the Browns Plains area which is now serviced by BUZ routes.

Ferry

There are some significant changes, particularly around the West End (south-west of the CBD) where ferry mode share collapsed (perhaps due to increased bus service levels and disruptions to ferries following the 2011 floods). Ferry mode share also dropped in the St Lucia area, and for students on the University of Queensland campus. I suspect this might be to do with increased bus service levels.

There was strong growth in ferry mode share in Bulimba (north-east of the CBD), following the reopening of the Apollo Road Ferry Wharf in 2008 (which on these maps seems to have been a success) (Apollo Road wharf is the furthest downstream ferry wharf on the south bank).

Train and bus

Train and bus journeys increased share in many areas around Brisbane (note the different scale). Notable areas include around Ferny Grove, North Lakes, along the Beenleigh rail line, along the rail line to Darra, and in Springfield. However these are all very small mode shares.

Multiple public transport modes

Multiple public transport mode journey origins tend to be fairly scattered, so here is a summary over the Greater Brisbane area (using place of enumeration data and thus losing journeys with ferry + non PT modes):

Integrated fares were introduced in 2004/05 eliminating the fare penalty for changing modes. There was a slight drop in multi-modal public transport mode share in 2006 (compared to 2001), but then a substantial rise by 2011 (faster than growth in single mode journeys). I want to explore multi-modality in journey to work data some more soon. Stay tuned.

Mode shift to public transport overall

Here’s a map showing the overall mode share to public transport in Statistical Local Areas (SLAs), the smallest geography where data is available for both 2006 and 2011 (you’ll need to click to enlarge, and unfortunately my GIS software doesn’t give every SLA a label ).

The biggest mode shifts to public transport on this map are in Pallara – Heathwood – Larapinta (mostly sparsely populated), around Darra-Richlands (where the new train line opened), Calamvale (new BUZ routes presumably), and around the end of the South East Busway.

Pinjarra Hills has a shift but only 139 people travelled to work from this SLA in 2011, so it only takes a few people to register a larger mode shift. And before you get excited about the airport area (Pinenba-Eagle Farm), only 144 people travelled from there to work in 2011. I’ll look at mode share by work location in a later post.

The biggest shift away from public transport was in Yeerongpilly, whilst other SLAs with significant drops include Fairfield, Geebung, Holland Park, and Highgate Hill. Not sure what the reasons might be in those places.

Walking only

There was a slight shift to walking in the inner city areas, notably around Woolloongabba, Paddington, and Wilston. Walking mode share was highest around the CBD, Fortitude Valley, and around St Lucia/University of Queensland (UQ).

Cycling

Cycling has grown rapidly (off a small base), particularly in the inner suburbs include around St Lucia/UQ and West End.

I’m sure other people will find more patterns – please comment on any interesting finds.


Traffic volumes on Australian toll roads

Sat 3 March, 2012

[Last updated September 2016]

What are the trends in traffic volumes on major toll roads in Australian cities? How sensitive are motorists to toll prices? How accurate have forecasts been on some recent toll roads? This post aims to shed some light on these questions.

Average daily volumes

Firstly, here is a chart comparing the most recent available figures for average daily traffic volumes (at the time of last updating this post):

Citylink, which is effectively made up of two mostly radial motorways in Melbourne, has by far the greatest traffic volume of any of the roads. In comparing these values, be aware that some toll roads are very short (eg just one bridge or tunnel), and others are over 20 km in length with many exit and entry points along the way.

For reference, the proposed east-west link toll road between Melbourne’s Eastern Freeway and Citylink was forecast to carry 100-120 thousand vehicles per day.

Traffic growth on roads with regular data

The next chart shows the relative growth in traffic volumes on several toll roads in Melbourne, Sydney and Brisbane (where regular data is published) since 2006, or whenever data became available:

You might want to click to zoom in and see all the detail. Another way of looking at this data is to consider rolling year on year traffic growth (ie 12 months versus the previous 12 months):

(click here for an experimental interactive version of this chart in Tableau)

Some observations:

  • Most roads show a cyclical trend, with weak growth in 2008-09 (possibly GFC related) and 2012, and strong growth in 2013-14 and again in 2015.
  • Growth has been much faster on non-radial roads. This might reflect the creation of new demand corridors as these roads provided significantly better links than the established road networks. But it also might reflect the low base from which the traffic volumes grow on these road. The high growth roads are:
    • Melbourne’s Eastlink, which runs north-south in the outer Eastern suburbs.
    • Sydney’s Westlink M7, which mostly runs north-south in the western suburbs.
    • Brisbane’s Gateway Bridge, which provides a north-south link east of the city centre.
  • Melbourne’s CityLink has shown a fairly steady growth trend of around 3%, except for a decline in 2009 (probably related to roadworks, but traffic soon recovered to trend once these works were complete). The road upgrade appears to possibly have had an impact on train patronage – refer another post.
  • Traffic volumes on Sydney’s M2 declined between late 2011 and mid 2013 due to major road upgrade works, but have since rebounded quite spectacularly.

An important note on growth rate precision: Transurban report daily traffic volumes rounded to the nearest thousand. For roads with relatively small volumes (eg Clem7), the growth rates will be more impacted by rounding errors. For example, the traffic volumes on Clem7 went from 27+26+27+27=107 thousand in 2014/15 to 27+26+26+27=106 thousand in 2015/16, which is notional growth of -0.9%. But actual values for each quarter will be within +/-500, and the rounding errors will add up over the eight quarters making up the calculation. The actual growth could be anywhere between -4.6% and 2.9%, but is more likely to be in the middle of that range.

Unfortunately data isn’t always readily available:

  • The Brisbane Gateway Bridge and Logan/Gateway Motorway extension data is only available for financial years in annual reports up until 2010. Transurban took over these roads and have reported traffic volumes since 2013 but they do not appear to be the same measures so I have listed them separately.
  • In October 2011, Horizon Roads purchased Melbourne’s Eastlink, and they do not seem to be publishing traffic volumes.
  • I haven’t been able to source Clem7 data for 2012 and the first half of 2013.

Traffic growth on other toll roads

Sydney Harbour Bridge and Tunnel

Calum Hutcheson from Hyder Consulting has generously compiled and shared time-series data with me on traffic volumes going back to 1971 for these two toll roads. He has sourced data from several available sources but has had to estimate some figures where data is missing.

Sydney Harbour Traffic 2

Traffic volumes levelled off on the bridge around 1988 and on the combined bridge and tunnel around 2005. It would appear the tunnel brought additional vehicle capacity good for around 17 years’ growth but that has now been exhausted (although I’m far from an expert in Sydney traffic).

In 1992 one lane was converted to a southbound bus lane (presumably related to the capacity freed up by the tunnel). The bridge’s vehicular traffic levels have not returned to 1988 levels, but I suspect the number of people moved in (road-based) vehicles has increased significantly (not to mention the train line across the bridge).

Sydney Cross City Tunnel

Transurban now own this asset and reported an average 33,057 daily transactions in the June quarter of 2014 – which is below the figure for late 2006.

I have not been able to source much data pre-2013, but a 2006 NSW Auditor General’s report contains some traffic volume data for 2005 and 2006, reproduced here (from page 32 of the report).

The tunnel is now carrying around 39,000 daily trips – not a large increase since 2006.

It would appear that motorists are highly sensitive to toll pricing, and the forecast volumes were not achieved even when tolls were removed.

Brisbane’s Clem7 cross-city tunnel

Brisbane’s first new road tunnel, the Clem7, opened in March 2010. During the first three weeks of toll-free operation, there was an average of 59,109 vehicles per day. During the first week of tolling, this fell to 20,602. The forecast was for initial traffic of around 60,000 vehicles per day, rising to 100,000 within 18 months. Owners at the time, Rivercity Motorways, went to the extraordinary step of publishing daily traffic data, as can be seen in the following chart showing traffic volumes since tolling commenced:

You can see an up-tick from the beginning of July 2010, when toll prices were cut. Tolls were raised in November 2010 and again in April 2011 and you can see corresponding drops in traffic volumes. Average daily traffic in calendar 2011 was 10% lower than for the first 12 months of operation (includes one overlapping quarter).

During the 2011 flood crisis tolls were waived for one week, and at the end of that period on Monday 17 January 2011, 40,566 vehicles were recorded, the highest since tolling commenced. This may or may not have also reflected closures to other roads making Clem7 more attractive. (footnote: actual weekend volumes have not been published for April 2010, so I have substituted the average non-workday figures, that have been published).

More recently, this road is carrying an average of 26,000 vehicles per day, around a quarter of the forecast.

Brisbane’s Airportlink

This toll road was forecast to attract 135,000 vehicles per day one month into operations, and have 165,000 vehicles per day after the ramp up period.

AirportLink traffic

The traffic volumes declined as tolls were progressively introduced to all traffic. BrisConnections, the owner of the road, went into voluntary administration in February 2013.

The Clem7 and Airportlink roads are the first two major tollways as part of the TransApex plan for adding major road capacity to Brisbane. The third piece of this puzzle is the Go Between Bridge, now owned by Transurban and they report 12,000 vehicles per day as of late 2015 (see some data on the Wikipedia page for what it’s worth). The forecast was for 17,500 by 2011 and 21,000 by 2021. Current patronage is around two-thirds of that forecast.

I’m guessing it may be a very long time before these TransApex roads reach capacity.

According to Wikipedia, this covers all major toll roads in Australia in operation at the time of writing. I’ll try to update these figures periodically.

Eastlink volumes compared to forecast

The following chart shows that Eastlink actual traffic volumes have been fairly consistently around 60-65% of original (2004) forecast since tolling began. It suggests the forecasts were good at estimating the ramp-up shape, but not so much the overall traffic volumes.

Note: ConnectEast issued revised forecasts in August 2009, including that (steady state annual) average daily trips in 2011 would be 209,900. That forecast doesn’t appear to have been realised either. Unfortunately data reporting stopped in October 2011 following the sale to Horizon Roads.

Maps of Australian Toll Roads

Here are some rough Google maps: Melbourne Sydney Brisbane
Maps and more information about many of the roads is also available on the Transurban website.

Other sources of traffic volume data

See another post on Melbourne traffic volumes. Some interesting recent data on Brisbane traffic volumes is in this report prepared for RiverCity Motorways (who operated the Clem7). It shows many major roads in Brisbane with stable or declining traffic volumes (possibly because they are at capacity, or possibly because of a mode shift to public transport).