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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Spatial changes in Sydney journey to work 2006-2011

Sun 25 November, 2012

How have mode shares of journeys to work from different home locations in Sydney changed between 2006 and 2011? What has the impact been of the new T-Ways and the Epping-Chatswood railway?

In my recent post on city level mode share changes we saw that Sydney had a 2.1% mode shift to public transport between 2006 and 2011. This post will uncover which areas shifted the most. For more analysis of patterns in the 2006 journey to work, see an earlier post.

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, with a minimum density of 3 workers travelled per hectare. 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

A shift to public transport is particularly evident in the north-western suburbs between Blacktown, Castle Hill and Epping. This is like to be a result of the new T-Ways (busways) between Parramatta, Blacktown and Rouse Hill, and express bus services from the area to the city along bus lanes on the M2 motorway.

There is also some evidence of mode shift along the Cronulla rail line.

Many new patches of green appear in the 2011 map which were blank in the 2006 map. I’m not sure if these are a result of the changed ABS geography (CD to SA1), or new transit orientated developments (I suspect mostly the former).

Sustainable transport (only)

This map excludes those who used private transport to reach public transport.

As well as the above public transport shifts, shifts to sustainable transport are evident around Turramurra and Forestville in the northern suburbs.

Train

Areas with a noticeable shift to train include Hornsby, Quakers Hill and Epping.

There is little change evident around the new Epping-Chatswood rail line, other than for a small residential pocket near Macquarie University station. Most of the stations on the new line are surrounded by non-residential land uses and show up as white. There has been quite a substantial impact on the public transport share of journeys to workplaces along the new line, which you’ll see in an upcoming post.

Bus

A shift to bus is most evident in the region between Parramatta and Castle Hill (as mentioned above).

Ferry

(ferry wharves are shown as blue dots)

Shifts to ferry are most evident around Manly, Balmain, and Watsons Bay (which is a little odd as it does not have peak period services).

Train and bus

43,815 people in Greater Sydney travelled to work by train and bus (and no other modes except walking) in 2011, up from 34,377 in 2006.

Journeys involving train and bus remain most heavily concentrated around Bondi Beach, where special cheap integrated train/bus link tickets are available. Areas with some shift to train and bus travel include Epping, south of Blacktown, Bossley and St Johns Park (served by the Liverpool-Parramatta T-way), and North Parramatta.

Multiple public transport modes

Here is a summary over the Greater Sydney area of journeys using single and multiple public transport modes (using place of enumeration data and thus losing journeys with ferry + non PT modes):

Sydney’s public transport mode share went backwards between 2001 and 2006, particularly for multi-modal public transport trips. There was a strong shift towards public transport between 2006 and 2011, with roughly equal growth in single mode and multi-mode public transport journeys. The data doesn’t tell us whether this represents a shift from single mode to multi-modal journeys (following the change to the fare system in April 2010).

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).

The biggest mode shifts are in different locations when aggregated at the SLA level. The biggest shifts were in Hornsby south, Concord, Manly, Parramatta north west and Baulkham Hills. I suspect the large mode shift in Hornsby south is a result of the new train line connecting this area to the major employment areas around Macquarie Park.

Campbelltown south was the only SLA to record a mode shift away from public transport.

Walking only

I cannot spot any significant shifts between 2006 and 2011.

Cycling

There were quite noticeable shifts to cycling in the inner south and around Manly. The total number of people cycling as part of their journey to workplaces in Sydney went from 12,128 in 2006 to 17,838 in 2011.

Here is an enlargement of the inner suburban areas:

 

Cycling’s mode share peaked at 21% in a pocket of Redfern between Telopea Street and Phillip Street, closely followed by a pocket of Dulwich Hill around Kintore Street at 20%.

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


Trends in journey to work mode shares in Australian cities to 2011

Tue 30 October, 2012

[updated December 2012 with more Canberra and Hobart data, and removing ‘method of travel not stated’ from all mode share calculations]

The ABS has just released census data for the 2011 journey to work (amongst other things). This post takes a city-level view of mode share trends.

Public transport

The following chart shows the public transport share for journeys to work for people within Statistical Divisions (up to 2006) and Greater Capital City Statistical Areas (for 2011) for each of the Australian major capital cities.

PT mode share trend

You can see 2011 increases in public transport more share in all cities except Adelaide, Hobart and Canberra. Melbourne grew by 2.2%, Perth by 2.1%, Sydney by 2.0%, Brisbane by 1.1% while Adelaide, Canberra and Hobart dropped by 0.1%.

But there are limitations of this data:

  • Census data is usually available by place of enumeration (where you actually were on census night) and/or place of usual residence. In the above chart the following years are by place of enumeration: 1991,  2001, 2006, 2011. I am just not sure whether the other years are place of enumeration or place of usual residence (ABS were unfortunately not as rigorous with their labelling of data tables in the past). There may be small differences in the results for place of usual residence.
  • The data available to me has been summarised in a “lossy” fashion when it comes to public transport mode share. It means that a journey involving tram or ferry and one or more non-PT modes is not counted as public transport in any of the results (it falls under “other two modes” or “other three modes” which includes PT and non PT journeys). For example, car + ferry or bicycle + tram. That means the true share of trips involving public transport will be slightly higher than the charts above, particularly for Melbourne and Sydney.
  • The 2011 figures relate to Greater Capital City Statistical Areas. For Perth, Melbourne, Adelaide, Brisbane and Hobart these are larger than the statistical divisions used for 2006 and early data. This means people on the fringe are now included, and they are likely to have lower rates of public transport use. So the underlying trends are likely to be higher growth in public transport mode share.

The limitations in counting of tram and ferry trips can be overcome by measuring mode share by workplace location, although I can only get such data for 2001, 2006 and 2011:

PT mode share by workplace trend

These figures are all higher because they include people travelling to work in the metropolitan areas from outside (where PT might have a higher mode share via rail networks for example) and they count all journeys involving ferry and tram. Between 2006 and 2011, Melbourne grew the fastest – by 2.4%, Sydney and Perth were up 2.0%, Brisbane up 1.2% and very little change in Adelaide, Canberra and Hobart.

Cycling

The following chart shows cycling only journey to work mode share:

cycling only mode share trend

(Adelaide and Perth are both on 1.3% in 2011)

Canberra is the stand-out city, owing to a good network of off-road bicycle paths through the city. But Melbourne has shown the fastest increase, going from 1.o% in 2001 to 1.6% in 2011.

Adelaide, Perth, Brisbane and Melbourne had a significant drop between 1991 and 1996, but this did not occur in Hobart, Canberra or Sydney.

Canberra, Melbourne and Sydney have shown the most growth in recent times. Adelaide and Hobart unfortunately went backwards in 2011. I’m not sure why Adelaide dropped so much, maybe it was a product of weather on the two census days?

Here’s another view that includes journeys with bicycle and other modes (by work location, not home location):

Bicycle any mode share

Perth and Canberra had the largest growth in journeys involving cycling and other modes.

Walking only

 

 

walking only mode share trend

Walking only rose in all cities 2001 to 2006, but then fell in most cities between 2006 and 2011 (Perth and Brisbane the exceptions). Perhaps surprisingly, Hobart had a higher rates of walking to work than all other cities.

Car

The following chart shows the proportion of journeys to work made by car only (either as driver or passenger):

car only mode share

(both Adelaide and Hobart were on 82.7% in 2011)

You can see car mode share peaked in 1996 in all cities except Canberra where it peaked in 2001, and Hobart where the 2011 result was just under the 1996 result.

Hobart, Adelaide and Canberra had small rises in 2011 (1.0%, 0.4% and 0.1% respectively) while Perth had the biggest drop in car mode share (down 2.6%), followed by Melbourne (down 2.0%), Sydney (down 1.8%) and Brisbane (down 0.9%).

Vehicle passenger

Vehicle passenger by work location

Travel as a vehicle passenger has declined in all cities, suggesting we are doing a lot less car pooling and commuter vehicle occupancy is continuing to decline in line with increasing car ownership. Curiously Hobart and Canberra topped the cities for vehicle passenger mode share.

Overall mode split

Because of the issue of under-counting of tram and ferry data for place of enumeration, I’ve constructed the following chart using place of work and a “main mode” summary:

 

work dest mode split 2001-2011

I assigned a ‘main mode’ based on a hierarchy as follows:

  • Any journey involving train is counted with the main mode as train
  • Any other journey involving bus is counted with the main mode as bus
  • Any other journey involving tram and/or ferry is counted as “PT Other”
  • Any other journey involving car as driver, truck or motorbike/scooter is counted as “vehicle driver”
  • Any other journey involving car as passenger or taxi is counted as “vehicle passenger

In future posts I plan to look at the change in spatial distribution of journey to work mode share (by home and work location).

I’d like to acknowledge Dr John Stone for assistance with historical journey to work data.


How did Sydney get to work in 2006?

Fri 26 October, 2012

With the imminent release of 2011 census journey to work data (30 October 2012), I thought it would be worth completing a look at 2006 data for Sydney and other cities. This post will take a more detailed look at Sydney, thanks to the free data provided by ABS and the Bureau of Transport Statistics New South Wales (BTS NSW).

There are five parts to this post:

  1. Mode share by home location
  2. Mode share by work location
  3. Mode share for Sydney CBD workers
  4. An employment density map of Sydney
  5. The relationship between employment density and mode share

(get ready for 25 charts!)

In future posts I hope to look at Adelaide, Perth and Brisbane in more detail, and also compare 2006 and 2011 results.

Firstly a few definitions for mode shares:

  • Public transport: Any journey involving any public transport mode (private transport might also have been involved – eg park and ride).
  • Active transport: A journey that only involved only walking and/or cycling.
  • Sustainable transport: Public transport + Active transport (note: this includes private+public journeys, but not private+cycling journeys).

Also, I have included railway lines on the following maps, however the data I have is unfortunately quite old and doesn’t show the CBD area rail network or the airport line (the Epping-Chatswood line was not operational in 2006).

Method of journey to work by home location

Data is readily available on journey to work by home census collection district, however this is by place of usual residence. Ideally mode shares should be measured using place of enumeration (where people actually were on census night), but I haven’t forked out the $750 required to get access to ABS TableBuilder Pro which would provide that data. So the data I’m presenting is not ideal as some people would have been away from home on census morning and their modes of travel will be associated with their usual residence.

But the data still provides a fairly good feel for what happened as most people were probably at their usual residence, and hopefully most people filled out their forms accurately.

Public transport mode share

Sydney is a sea of green on this map (other cities will have the same colour scale, stay tuned!). Public transport use in journey to work was highest in the inner city area and along the train lines. It was lowest in the outer suburbs beyond the rail lines.

Train

There are three large and stark areas of red near the CBD and close to train lines. Most of these areas are served by direct and frequent bus services to the CBD, and while for some it might be quicker to change onto a train, this would probably be more expensive. Also, the area around Castle Hill has very low train mode share, although we will see shortly that of the small number who do commute to the CBD about three-quarters use public transport.

I note that the airport rail line (not drawn on the map) resulted in a high train mode share at Mascot but not at Green Square.

Bus

Bus mode share was high in the suburbs close to the Sydney CBD, but very low in the outer suburbs (with exceptions around Palm Beach in the north, Castle Hill (served by freeway buses), and seemingly random pockets north of Mount Druitt).

Train and bus

The following map shows people who used both train and bus in their journey to work:

I’ve used the same colour scale as other maps, and so most of the city is red indicating very few bus-train transfers. The curious exception is around Bondi Beach/Bronte. This is probably all to do with the special Link Tickets that allow bus and train travel on the one ticket in this area only. They are designed for people visiting these areas, but they seem to be very popular with locals travelling to work.

I do wonder what would happen if there were valuable integrated tickets for more places (perhaps we’ll see some differences for 2011 thanks to MyZone).

Ferry

I’ve zoomed into the harbour for this map, and included the ferry wharves (some receiving a much more frequent peak period service than others).

You can see high mode shares on the north shore, to the inner east, and around Manly (wharves which probably have fairly direct services to the CBD). This includes some areas a fair walk from the ferry terminals – with some people probably using connecting buses. In fact, here is a map showing bus and ferry commuters mostly on the north shore (note different colour scale):

Public and Private transport combined

The following map shows the percentage of people who used public transport as well as car, motorcycle and/or truck to get to work (again using a different colour scale):

Use of both public and private modes is most common in the northern suburbs around Hornsby (areas away from the train line), around Macquarie Park (now served by rail), north of Blacktown (now serviced by bus rapid transit), and west of Sutherland.

Cycling

The following map also uses the different scale, and I have zoomed into the areas with significant bicycle mode share.

The cycling mode share peaks at 11% from a pocket of Enmore, and seems to be the domain of the inner southern suburbs.

Active transport (only)

The following map shows people who only used walking and/or cycling to get to work:

You can see the walking/cycling hot spots are around the CBD, North Sydney, Parramatta, Chatswood, Liverpool, Penrith, and around Randwick/UNSW.

Method of journey to work by work location

Here is a map showing the public transport mode share of journeys to travel zones in Sydney in 2006 (where 200 or more journeys were made):

It’s not just the Sydney CBD that had reasonably high public transport mode share. Public transport mode share peaked in the centre of the following regional hubs:

  • North Sydney 53%
  • Bondi Junction: 41%
  • Parramatta: 38%
  • Chatswood: 35%
  • St Leonards: 34%

(these are the highest value recorded by any travel zone in each centre).

By contrast, analysis of destination mode share for Melbourne showed all major suburban centres to have well less than 15% public transport mode share (most less than 10%).

Public transport mode share was also quite clearly higher along the train lines – particularly in the middle and outer suburbs.

Here are enlargements of inner Sydney and the Sydney CBD area:

 

Here’s a map showing active transport mode share for greater Sydney workplace destinations:

Active transport was most commonly used to inner city areas including Newtown, Camperdown, Bondi Beach, Randwick, Paddington and Potts Point.  However it was low in the Sydney CBD. The Holsworthy Military Camp as a large green area in the south with high active transport mode share – probably because the military staff live on site. People more familiar with Sydney might be able to comment further.

Here is sustainable transport mode share (public transport and active transport combined, everything else being private motorised transport). You can see that private transport was by far the dominant for western Sydney jobs.

Journeys to work in the Sydney CBD

Here’s a map showing the public transport mode share by home location of journeys to work in the Sydney CBD (defined as the Sydney – inner SLA, the only red SLA on the map):

Public transport had a mode share around 70-80% for large areas of Sydney (in contrast to Melbourne where 60-70% was more common). However there was a much lower share from the CBD itself and areas adjacent.

Were they walking or cycling instead?

Well, yes for the City of Sydney areas, but not for Woollahra to the east. On the following sustainable transport mode share map, you can see that around 35% of workers from Woollahra commuted to the CBD by private transport (note I have used a different scale for this map):

Sustainable mode share is highest from the western and south-western suburbs, whereas many people chose to drive from the northern suburbs, the southern coastal areas, and even the inner eastern suburbs.

But what proportion of the working population commuted to the CBD?

Compared to the Melbourne CBD, the Sydney CBD seems to have a stronger role, even though Sydney has major employment centres outside the central CBD.

For anyone interested, here are similar maps for North Sydney and Parramatta as work destinations:

Sydney’s employment density

The BTS data also allows the construction of an employment density map. I’ve drawn this map based on people who travelled to each destination zone on census day.

And a zoom in on the inner city:

Employment density and mode share

Finally. here is a look at the relationship between employment density and public, active and private transport mode share (by workplace zone).

I must stress that these results will strongly reflect the design of public transport – which is heavily geared towards places with high employment density (such as the Sydney CBD) as that is where public transport can generally complete strongest with private transport (the cost of parking and traffic congestion etc). By increasing employment density in any parcel of land you won’t automatically get high public transport mode share – you have to provide high quality public transport to that destination first!

No surprises there!

Was that what you expected? Active transport actually had the highest mode share in areas with the lower employment densities. These are likely to be mixed residential/employment areas where employees can live close by, military camps, and farms.

Finally, it will be little surprise that the lower employment densities had the highest private transport mode shares. These areas are likely to have ample room for free employee parking, and public transport is likely to struggle to efficiently deliver a small number of employees over a large area.


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).


Public transport mode share – according to household travel surveys

Sat 10 April, 2010

[post revised and updated October 2012 with new data from Sydney, Brisbane, and New Zealand]

Arguably the best source of public transport mode share statistics is from household travel surveys that are conducted in most large Australia cities and all of New Zealand (unfortunately some surveys more regularly than others). A common measure is public transport’s share of motorised trips (although public transport will also be competing with unmotorised transport modes).

In household travel survey speak, a linked trip is a journey between two distinct non-travel activities, and may involve several trip legs or unlinked trips. For example, if you walk to a bus stop, catch a bus to the train station, then catch a train to the city, then walk to your workplace, that is one linked trip made up of 4 unlinked trips (walk, bus, train, walk). Similarly if you drive from your home to your workplace, that’s one linked trip made up of one unlinked trip (unless you decide to count walking to and from the car). Hence mode share figures that relate to unlinked motorised trips will always be higher than mode share figures that relate to linked trips.

The data I have been able to obtain for cities is sometimes linked trips, sometimes unlinked trips, and sometimes both. It should be possible to get figures for both for any city, and I hope to obtain such data from state transport agencies in the future.

Here is the data I have for linked trips:

And here are the results for unlinked trips:

The Melbourne and Sydney measures are for weekdays only, whereas the New Zealand data appears to be for all days of the year.

In 2008, Melbourne appeared on track to overtake Sydney on unlinked trip public transport mode share, however the 2009-10 result for Melbourne was lower than predicted. Note that the error bars on the 2007-08 and 2009-10 VISTA survey results for Melbourne indicate the actual mode share might not have actually gone down significantly (similar error bars would apply to the linked trip data points). Over the same period public transport patronage grew by 11% and arterial road traffic grew by around 1.2%.

How reliable is this data?

Given that most household travel surveys interview thousands of households in any one year, the results should be pretty accurate for a high level reported figure such as mode share of trips. Household travel survey techniques have matured over the years, so it is likely they are reasonably reliable (particularly more recent results in larger cities).

The Perth survey data for 2003 to 2006 does not correlate with public transport patronage figures, that show a 12% growth over the same period.

For Brisbane 2003-04 I had to add whole number shares for each mode and divide by the sum of motorised mode shares. So there is some uncertainty about the precise motorised mode share.

The Melbourne official estimates for 2002-2007 were calculated using VicRoads traffic data, and public transport patronage figures.

(For more detail see the end of this post).

Linked or unlinked trips?

Calculating mode share based on linked trips removes the impact of public transport transfers. Cities where the public transport network is structured around feeder services with free transfers (eg bus to train) may have more public transport boardings (unlinked trips) than cities where transfers are “less encouraged” by the network design and fare systems (eg Wellington, Auckland, Sydney).

In fact, here is a chart showing the ratio of unlinked to linked public transport trips for four cities where I have data:

The Perth and Adelaide data is based on patronage figures that are reported as ‘initial boardings’ and ‘all boardings’. Annual reports comment that recent through-routing of bus services through the Adelaide CBD may have reduced the number of transfer boardings. You can see the transfer rate for Perth jumped after the southern suburbs railway opened at the end of 2007 (replacing many CBD bus routes with train feeder bus routes).

The Perth, Adelaide and Melbourne public transport fare systems are dominated by products that allow unlimited transfers within a time window (anywhere from 2 hours to 365 days). So while there may be a time and convenience penalty for transferring between two services, there is no financial penalty. Sydney’s public transport fare system has largely involved tickets for a single trip and/or one mode, such that another fare must be paid to transfer. Sydney’s CBD is also served by seemingly hundreds of bus routes – many of which parallel train lines – which enable people to travel to the city without having to transfer onto trains and pay a higher fare (even if that could provide a faster over journey).

The lower Sydney transfer rate partly explains why Melbourne and Sydney are much closer on mode share of unlinked trips, compared to mode share of linked trips. Network design will probably also have an impact.

There was a slight dip in the trend for Sydney around 2007-08 followed by a rise. I’m not sure what might explain that trend – the revamp of the fare system in April 2010 (introducing more multi-modal and multi-operator tickets) may have had a small impact on the 2009-10 figure.

The difference in these rates suggests that there could be quite substantial change in Sydney public transport use patterns should the fare system be revised to make free transfers the norm. Perhaps this might help ease the bus congestion issues in the CBD and allow higher bus frequencies in the suburbs? (assuming there is capacity to transfer bus passengers onto trains in the suburbs). There is one small area of Sydney where train+bus link tickets are available (no fare penalty for transferring), and the census data reveals a very significant rate of bus+train journeys to work in the Bondi Beach area, much higher than anywhere else in Sydney.

Other measures of public transport mode share

In another post, I looked at BITRE data on estimated passenger kms per mode in Australian cities (presumably calculated using patronage figures and average trip lengths from household travel survey data or elsewhere). That enabled calculation of estimated public transport mode share of motorised passenger kilometres, with continuous time series available for all Australia cities. However there will be many assumptions involved in these estimates.

Another measure is boardings per capita (covered here), although this also has the problem of different transfer rates in different cities.

The quest for a fair measure of public transport use continues!

Household travel survey sources:

Melbourne: Victorian Department of Transport (personal communications), but also available in the Growing Victoria Together Progress Report (page 387), in the 2009-10 Victorian State Budget Papers. Figures until 2001 were from the VATS survey, while the 2008 result is from the VISTA survey.

Sydney Household Travel Survey: Data was supplied by NSW Transport Data Centre by email. Public transport trips are inclusive of trains, buses, ferries, monorail and light rail.

Adelaide Household Travel Survey (AHTS): Adelaide Travel Patterns: an overview (if anyone can tell me about whether more recent surveys have been conducted I would be very appreciative, better still if I can get results data!).

South East Queensland Travel Survey: Brisbane Fast Facts Brochure (unclear dating, but PDF was created in 2006 so I assume the results are for 2003-04. The report does not mention whether these are mode shares for trips or kms, however it seems highly likely they are for trips as the walking mode share was 10% and we know walking trips are generally shorter than motorised trips). I also have results for 2008-09 courtesy of Ian Wallis and Associates. I unfortunately do not yet have results for the 2006-2008 survey.

Perth and Regions Travel Survey (PARTS): Data is from the PARTS Key Findings Report (by Data Analysis Australia). The  2003-2006 results are from PARTS, the 2000 figure is a TravelSmart estimate, and 2001 and 2008 estimates are from unspecified sources.

The New Zealand Household Travel Survey: Because of sample sizes, the figures for the New Zealand cities are two years combined (ie the “2010” figure is for 2008/09 and 2009/10). The Canterbury region includes Christchurch as well as a not insignificant surrounding population. The Auckland region is more similar to the Australian cities statistical divisions. The Wellington figures are for the Wellington Region, but are dominated by metropolitan Wellington.