Where is population growth happening in Australia?

Tue 8 January, 2019

The location of population growth has a big impact on transport outcomes. It’s also interesting in its own right. So where is Australia’s population growing?

This post primarily uses the ABS’s Regional Population Growth data set, which is the highest resolution geography level for which per-year population estimates are published and the data series goes back to 1991.

Population growth by part of Australia

At the top level I’ve divided Australia’s population into those living within:

  • Capital cities – defined by Greater Capital City Statistical Areas (GCCSA)
  • Large regional cities – defined as Significant Urban Areas (SUA) (2011 boundaries) with more than 100,000 population in 2011 – the smallest city qualifying being Toowoomba, the largest city not qualifying being Ballarat
  • Small regional cities – all other Significant Urban Areas with at least 10,000 population (in 2011)
  • Elsewhere – ie smaller towns and rural areas

Here’s the history of Australia’s population and growth since 1991, by these four categories:

While the capital cities have seen the largest absolute growth, the large regional cities have seen the highest percentage growth.

Here is the annual population growth by each category:

The capital cities have dominated the quantity of population growth, particularly since around 2007, with “elsewhere” having very small net growth in recent years. But as the first chart showed, large regional cities have had the fastest percentage growth – so it all depends on how you want to think about “growth”!

The distribution of total population across the four categories has very slowly shifted towards capital cities:

So what proportion of Australians live in urban areas?

Here’s a breakdown of Australia’s population from the 2016 census by size of city/town and rural areas (using urban centre and locality boundaries – different to the above analysis):

The United Nations cannot land on a single definition of urban (is a locality of 100 people urban?) so it’s hard to perfectly answer the question. But I can say: well over 90% of Australians live in urban areas.

Dominance of capital cities within states and territories

In all states, capital cities have been increasing their share of the population:

The blip in the Northern Territory represents a temporary exodus of population after Cyclone Tracy devastated much of Darwin on Christmas Day 1974.

Population growth of cities

The following chart shows the population of capital cities and large regional cities. Note I’ve again used a log scale on the Y-axis to separate the cities.

You can see the Gold Coast and Sunshine Coasts have overtaken several other cities.

Here’s a longer time series history of the capital cities (this time not a log scale):

Technical note: Historical population estimates on Greater Capital City Statistical Area boundaries are only available back to 1971, and for Significant Urban Areas boundaries back to 1991. Estimates for earlier years are on inconsistent boundaries.

Perth overtook Adelaide in 1984, and Canberra overtook Hobart in 1972.

Here is the percentage population growth since 1971 for capitals:

And for more recent history, here is the percentage population growth since 2001 for capital and large regional cities:

The Gold and Sunshine Coasts are the fastest growing cities by far, followed by Cairns, Brisbane and Perth. Hobart and Adelaide are the slowest growing capital cities.

Another view is annual growth rates:

In 2017, Melbourne had the fastest population growth rate, and Adelaide the slowest. The Gold and Sunshine Coasts have had relatively high growth since 1991. All cities have fluctuated a fair bit over time.

Here’s the annual population change for each city – again on a log scale Y-axis:

Technical note: because of the log scale, negative values are omitted from the chart.

Melbourne has been adding more people than Sydney every year since 2002 (hence predictions it will become Australia’s largest city), while Perth’s recent strong growth spurt ran between 2006 and 2013.

Here’s a simple map of Australian cities and towns by size (based on 2016 GCCSA and SUA boundaries, which is different to the time series data shown above):

Explore this data in Tableau Public.

Note: the intervals are arbitrary and it’s hard to get them perfect. For example, Ballarat had 103,581 residents and Bendigo 97,470 (in 2017), so they are coloured differently. Note: Ballarat had less than 100,000 residents in 2011 so was not included in the earlier charts for regional cities.

Also many of these SUAs include a lot of hinterland – eg Geelong includes Torquay

Here is a similar map, but colours now indicate percentage population change 2001 to 2017:

Explore this data in Tableau Public.

The city or town with the highest percentage growth is Bussleton in WA (+66%), followed by Hervey Bay in Queensland (+58%). Broken Hill (NSW) has seen the biggest population decline (-15%), followed by Mount Isa in Queensland (-7%).

Where is population growing within larger cities?

Melbourne

Firstly, my home town Melbourne. Here’s the population growth in the five years to 2017:

Technical note: I’ve used point circles for each SA2, rather than fill colour (which should never be used for non-ratio data because the size of the zone can too easily distort the message!). Alternatives are to show population density, population growth density, or growth rate percentages. However some metro fringe SA2s include a relatively small urban area coupled with a large rural area, so the density gets washed out by the rural area. Growth rate percentages also depend a lot on the population in the base year. If an SA2 goes from 2000 residents to 8000 residents the growth rate is 300%, but that’s the same increase as a SA2 that goes from 30,000 to 36,000 (20%).

Melbourne’s SA2s (on 2016 boundaries) with the largest population growth were in the outer west, outer north, outer south-east, and central city. SA2s with population slight decline were Rowville South, Upwey – Tecoma, Endeavour Hills South, Keilor Downs, Taylors Lakes and Mill Park.

I think it’s also important to note that SA2 boundaries are somewhat arbitrary and they only change every five years.

In fact, South Morang was reported by the ABS (and media) as the fastest growing SA2 in Australia in 2015-16 (on 2011 boundaries) in terms of absolute growth, but by then it had 64,354 residents and was by far the largest SA2 in Australia (the next largest, Point Cook, had 52,253). It was time to split into smaller SA2s – which indeed happened shortly thereafter with the new 2016 boundaries (ditto Point Cook). So it was probably the fastest growing SA2 more because the ABS had not yet split it into smaller SA2s. Unfortunately this issue isn’t always picked up by the ABS and the media.

How has population growth changed over the years? That is a four-dimensional question, so my answer will be a four-dimensional visualisation. Here’s an animated map showing the annual growth for each SA2 for each year 1992 to 2017 (you might need to click to enlarge to see it clearly):

Technical note: until 2001 the maps shows SA2s on 2011 boundaries and then from 2002 onwards the map shows 2016 boundaries. There were several SA2s that split with the 2016 boundaries, mostly in the northern suburbs.

While there has been fairly consistent growth on the fringe in all years, the amount of growth in established areas has fluctuated over time. Here’s a summarised view of the same data, but simplifying the geographic element to distance from the CBD:

You can see many of Melbourne’s middle suburbs (particularly 10-15 km) saw population decline around 1992 to 1995 while Victoria was under economic stress (but also Australia’s total population growth rate fell below 1% during this period).

Most of Melbourne’s outer growth areas are 20+ km from the CBD, and you can see reasonably steady growth in bands that far out and beyond. But within 20 km there was a big population growth slow-down in 2010 and 2011.

Sydney

Here are the same two charts for Sydney:

Sydney’s population growth has also varied considerably between years, but the most consistent band for population growth is within 5 km of the CBD. Population growth in the inner and middle suburbs has been strong since 2007.

Brisbane

Brisbane seems to have been a mixed bag. There’s been growth on the fringe to the north and south-west. From around 2002 there was an increase in central city population growth, with a particularly strong surge in 2003 and 2017.

Perth

 

Perth is an interesting story. Apart from the mining boom years 2007 to 2013, most of the population growth has been through urban sprawl. During the mining boom the central and inner suburbs saw substantial population growth (along with the fringe), but since 2014 that’s crashed and there was substantial population decline in the inner and middle suburbs, particularly 10-15 km out from the CBD in 2016.

Adelaide

Adelaide saw substantial population decline in the inner suburbs in the early 1990s, with instead sprawl to the south and north. Things were quieter around the turn of the century before population growth rose around 2005, with quite significant inner suburban population growth, but still plenty of sprawl on the fringe.

Canberra

In the early 1990s, population growth was mostly in the far north and south. Then at the turn the century the south quietened down and Queanbeyan West – Jerrabomberra had a growth spurt. Growth in the outer north took off around 1995. Infill growth took off around 2007, particularly in Belconnen, Bruce, Civic and Kingston – Barton. And then from around 2014 a brand new growth front opened in the west (Wright and Coombs).

Hobart

Note: I’ve used a different scale for the bubbles. because of the smaller changes and smaller geography.

Hobart had net population decline in the late 1990s but then grew quickly from 2003 onwards, with particularly strong growth in 2009 and 2017. The majority of population growth in recent years has been within 10km of the CBD.

Population growth in regional areas

Here is a map showing population growth percentage from 2001 to 2017 for all SA2s in Australia:

No, a new gigantic dense rectangular city has not emerged in the north-west of Western Australia. That’s an artefact of coloured maps and large geographic zones. The “East Pilbara” SA2 population simply grew from 2441 to 6789, which is 178% growth. But the 2017 average density was 0.00017 persons per hectare.

Otherwise places of higher percentage growth are mostly around the major cities. Population decline is common in most inland/outback areas.

I hope this has provided you some new insights on population growth around Australia.

My next post will look at the urban growth areas of large cities in more detail.


Update on Australian transport trends (December 2018)

Fri 28 December, 2018

For more recent trend information – skip to the December 2019 update on Australian transport trends.

Each year, just in time for Christmas, the good folks at the Australian Bureau of Infrastructure, Transport, and Regional Economics (BITRE) publish a mountain of data in their Yearbook. This post aims to turn those numbers (and some other data sources) into useful knowledge – with a focus on vehicle kilometres travelled, passenger kilometres travelled, mode shares, car ownership, driver’s licence ownership, greenhouse gas emissions, and transport costs.

Vehicle kilometres travelled

Road transport volumes are rising, and most of the traffic is of course cars:

Here’s the growth by vehicle type since 1971:

Light commercial vehicle kilometres have grown the fastest, curiously followed by buses (although much of that growth was in the 1980s).

Car kilometre growth has slowed significantly since 2004.

In fact, on a per capita basis car use peaked in 2004 and then declined until 2014, with a little growth since. Here’s the Australian trend (in grey) as well as city level estimates to 2015 (from BITRE Information Sheet 74):

Technical note: “Australia” lines in these charts represent data points for the entire country (including areas outside capital cities).

Darwin has the lowest average which might reflect the small size of the city. The blip in 1975 is related to a significant population exodus after Cyclone Tracey caused significant destruction in late 2014 (the vehicle km estimate might be on the high side).

Canberra, the most car dependent capital city, has had the highest average car kilometres per person (but it might also reflect kilometres driven by people from across the NSW border in Queanbeyan).

The Australia-wide average is higher than most cities, with areas outside capital cities probably involving longer average car journeys and certainly a higher car mode share.

Passenger kilometres travelled

It’s also possible to look at car passenger kilometres per capita, which takes into account car occupancy – and also includes more recent estimates up until 2017:

While car passenger kilometres per capita also peaked in 2004, they have increased slightly in recent years in Perth, Adelaide, Brisbane, and Sydney.

BITRE also produce estimates of passenger kilometres for other modes (data available up to 2017 at the time of writing).

Rail use is highest in Sydney followed by Melbourne. You can see two big jumps in Perth following the opening of the Joondalup line in 1992 and the Mandurah line in 2007.

(note: this includes both public and private bus travel)

Australia-wide bus usage is surprisingly high. While public transport bus service levels and patronage would certainly be on average low outside capital cities, buses do play a large role in carrying children to school – particularly over longer distances in rural areas. The peak for bus usage in 1990 may be related to deregulation of domestic aviation, which reduced air fares by around 20%.

Darwin saw a massive increase in bus use in 2014 thanks to a new nearby LNG project running staff services, while investments in increased bus services in Melbourne and Brisbane in the first decade of this century led to significant patronage growth.

We can sum all of the mass transit modes (I use the term “mass transit” to account for both public and private bus services):

We can also calculate mass transit mode share of motorised passenger kilometres (walking and cycling kilometres are unfortunately not estimated):

Sydney has maintained the highest mass transit mode share, while Melbourne made significant gains between 2005 and 2009, and Brisbane also grew strongly 2007 to 2013.

Here’s how car and mass transit passenger kilometres have grown since car used peaked in 2004:

Mass transit use has grown much faster than car use in Australia’s three largest cities. In Sydney and Melbourne it has exceeded population growth also.

Mass transit has also outpaced car use in Perth, Adelaide, and Hobart:

In Canberra, both car and mass transit use has grown much slower than population, and it is the only city where car growth exceeded public transport growth between 2004 and 2017.

Car ownership

The ABS regularly conduct a Motor Vehicle Census, and the following chart includes data up until January 2018.

Technical note: Motor Vehicle Census data (currently conducted in January each year) has been interpolated to produce June estimates for each year.

Car ownership has continued to rise slowly in all states – except Victoria, which is consistent with a finding of declining motor vehicle ownership in Melbourne from census data (see also an older post on car ownership).

Driver’s licence ownership

Thanks to BITRE Information Sheet 84, here is motor vehicle licence ownership per 100 persons (of any age) going back to 1971:

Technical note: the ownership rate is calculated as the sum of car, motorbike and truck licenses – including learner and probationary licences, divided by population. Some people have more than one driver’s licence so it’s likely to be an over-estimate of the proportion of the population with a licence.

There’s been slowing growth over time, but Victoria has seen slow decline since 2011.

Here’s a breakdown by age bands (note each chart has a different Y-axis scale):

Motor vehicle licence ownership rates have increased for people over 70 (presumably due to a healthier ageing population), and declined for people under 30.

Licencing rates for teenagers have been trending down in South Australia and Victoria recently, but not in other states:

The trends are mixed for 20-24 year-olds:

New South Wales and Victoria are seeing downward trends in the 25-29 age bracket:

Licencing rates for people in their 70s are rising in all states (I suspect a data error for South Australia in 2016):

A similar trend is clear for people aged 80-89 (Victoria was an anomaly before 2015):

(see also an older post on driver’s licence ownership for more detailed analysis)

Transport greenhouse gas emissions

Australia’s domestic non-electric transport emissions have increased steadily since 1990 and show no signs of slowing down, let alone declining (latest data at the time of writing is up to June 2018):

Depending on how you disaggregate total emissions, transport is the second largest sector and the fastest growing.

Here’s breakdown of transport emissions (detailed data only available to 2016 at time of writing):

And the growth in each sector since 1990:

Domestic aviation has had the fastest growth, followed by buses. In more recent years rail emissions have grown strongly (note: most of this is rail freight as the vast majority of passenger train movements are electric). Car emissions have grown 27%, but make up the largest share of transport emissions.

Here are per capita transport emissions for each state:

The data is a bit noisy (largely due to fluctuations in aviation emissions). Here are road emissions per capita:

In 2016 there were sharp increases in Western Australia, Queensland and the Northern Territory, while most other states appear to be on a downward trend.

Car emissions per capita have been generally trending downwards in most states, again except Queensland, Western Australia, and the Northern Territory:

Of course if we are to avoid dangerous climate change, total emissions need to reduce substantially, not just per capita emissions!

It’s possible to combine data sets to estimate average emissions per vehicle kilometre for different vehicle types:

It’s difficult to see any significant reductions in emissions intensity, while average bus emissions intensity has increased recently (not sure why). Average car emissions have fallen slightly from 281 g/km in 1990 to 244 g/km in 2016.

However, the above figures don’t take into account the average passenger occupancy of vehicles. To get around that we can calculate average emissions per passenger kilometre for the high person-capacity modes:

Of course the emissions per passenger kilometres of a bus or plane will depend on occupancy – a full aeroplane or bus will have likely have significantly lower emissions per passenger km. Indeed, the BITRE figures imply an average bus occupancy of around 9 people (typical bus capacity is around 60) – so a well loaded bus should have much lower emissions per passenger km. The operating environment (city v country) might also impact car and bus emissions. On the aviation side, BITRE report a domestic aviation average load factor of 78% in 2016-17.

Cost of transport

The final topic for this post is the real cost of transport. Here are headline real costs (relative to CPI) for Australia:

Technical note: Private motoring is a combination of factors, including motor vehicle retail prices and automotive fuel. Urban transport fares include public transport as well as taxi/ride-share.

The cost of private motoring has tracked relatively close to CPI, although has been trending down since around 2008. The real cost of motor vehicles has plummeted since 1996. Urban transport fares have been increasing faster than CPI since the late 1970s.

Here’s a breakdown of the real cost of private motoring and urban transport fares by city (note different Y-axis scales):

Urban transport fares have grown the most in Brisbane, Perth and Canberra – relative to 1973.

However if you choose a different base year you get a different chart:

What’s most relevant is the relative change between years – eg. you can see Brisbane’s experiment with high urban transport fare growth between 2009 and 2017 in both charts.

To illustrate the data visualisation problem of choosing a base year – here is the same data for every base year between 1973 and 2018:

Hopefully this post has provided some useful insights into transport trends in Australia. A future post might examine the relationships between the data sets further.


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.


How did the journey to work change in Sydney between 2011 and 2016?

Wed 17 October, 2018

Over a quarter of Sydney commuters (26.3%) went to work by public transport in 2016, the highest rate of Australian cities, and an increase of 3.0% on 2011. This post provides an overview of mode shares and mode shifts across Sydney from 2006 to 2016 (following on from my previous analysis of Melbourne and Brisbane).

I’m going to mostly look at trends in private motorised transport mode shares, as it is generally the least space-efficient and most polluting method of travel on a per person basis, and many cities aim to shift people away from private transport to active or public transport.

Firstly, here are private transport mode shares by home location (click to enlarge or explore in Tableau Public but be patient):

You can see lower private mode shares in the inner city and around train lines, as you might expect. In many places private transport accounts for a minority of commuters.

Here are the private transport mode shifts by home location (also in Tableau):

There were significant mode shifts away from private transport almost all over Sydney, but particularly strong in the inner south, inner west, north shore and hills area, including many areas served only by buses for public transport.

You can see the mode split of net new commuter origins on the next chart, with public transport dominating new trips from many areas on the north shore, eastern suburbs, and inner west and south-west (also in Tableau):

Private transport dominated new commuters in the outer western suburbs. Compared to other cities, a smaller proportion of new commutes came from the outer fringe, which may partly explain why Sydney had the strongest mode shift to public transport.

Here’s another look at that data, with the private transport mode share of net new journeys to work:

In many parts of Sydney there was an absolute reduction in the number of private transport journeys to  work (pink areas), and many where it represented a small minority. Private transport did however dominate new commutes from most outer western suburbs and the northern beaches.

Summarising the above, Sydney saw public transport journeys grow faster than private transport journeys across all but the outer suburbs:

Here are the private transport mode shares by work location (also in Tableau):

Sydney is distinctly different to the other cities in that there are many major employment centres outside the CBD with quite low private mode shares. The lowest 2016 private transport mode share destination zone in Macquarie Park was 59%, in Strathfield was 53%, in Manly was 55%, in Parramatta was 40%, in Chatswood was 40%, in St Leonards was 43%, in Bondi Beach was 43%, in Burwood was 46%, in Kensington was 45%, in Bondi Junction was 35%, and in North Sydney was 22%. Refer to my recent post about suburban employment clusters for more on this.

The Sydney CBD itself has a destination zone with only 6% private mode share in 2016. Sub-50% private mode shares stretch out from the CBD as far as Newtown south-west of the CBD.

Here are private transport mode shifts by work location:

There were significant mode shifts away from private transport across much of Sydney, with the largest in Mascot (-9%, noting that train fares were reduced at stations in Mascot in March 2011), and 7% declines in Sydney Airport, Kogarah, Waterloo – Beaconsfield, Newtown – Camperdown – Darlington, Redfern – Chippendale, Chatswood (East) – Artarmon. There was a 6% mode shift away from private transport in both North Ryde and Macquarie Park, where new train stations opened in 2009.

Here is a map showing the volume and mode split of new commuter destinations in Sydney:

The Sydney CBD is such a big pie chart it swamps all others with 63,732 new commuters, 86% of which were accounted for by public transport. Public transport also dominated in North Sydney – Lavender Bay (which actually had a net reduction in private transport trips), Surrey Hills (88% by public transport) and Pyrmont – Ultimo (84% by public transport).

It’s also notable that Sydney’s major regional centres had a significant share of their jobs growth accounted for by public transport trips, as explored in my earlier post on employment clusters.

Here’s a map of private transport mode share of net new trips by workplace:

There was a net reduction in private transport journeys to many SA2s, including North Sydney, Homebush, Epping – North Epping, and Mascot – Eastlakes (note: some others might be artifacts of boundary changes between 2011 and 2016). Private transport again dominated new journeys to the outer west and northern beaches.

You can see on the following chart that the central city accounted for a significant portion of the jobs growth and public transport accounted for almost all of those new trips, which helps explain the overall shift to public transport. Private transport only significantly dominated new jobs more than 10 km from the city centre.

For more on the journey to work, you might like another post about likely factors explaining city-wide mode shifts across Australia’s larger cities.

About the data

The mode share maps are filtered for residential areas (CD or SA1) with at least 5 persons/hectare or destination zones (DZs) with at least 4 jobs/hectare (as appropriate). Mode shifts, mode splits, and mode shares of net new commutes are calculated and shown on 2016 SA2 boundaries, with 2006 and 2011 CDs, SA1s and DZs mapped to 2016 SA2 boundaries on a majority overlap basis (mostly a perfect alignment, but sometimes not). I’ve only counted people who travelled on census day and stated what mode(s) they used, and – for work destinations – where the work SA2 is known. See my Brisbane post for a longer explanation.