I’ve looked at Melbourne residential density in detail, so what about other Australian cities?  Is population weighted density a useful measure? Does population weighted density help explain differences in public transport mode shares?

For this exercise, I’ve looked at 2011 census data at the Statistical Area Level 1 (SA1) geography (currently the smallest geography for which population data is available) for Greater Capital City Statistical Areas (which include large tracts of rural hinterland). I’ve sometimes applied an arbitrary threshold of 3 persons per hectare to define urban residential areas.

Measures of overall density

Population weighted density is a weighted average of the density of all the parcels of land in the city, with the population of each parcel of land providing the weighting. This provides a figure indicative of the residential density of the “average person”, although that’s still a little abstract. A city where a large proportion of people live in dense areas will have a much higher weighted population density than average population density.

Average density is simply the total population divided by the area of the city (or if you like, the average density weighted by the areas of each parcel of land). In calculating average residential density (which I’m doing in this post), the area would only include residential areas (I’ve arbitrarily used a threshold of SA1s with at least 3 persons per hectare).

Another measure is urban density, which considers all the land that makes up the urban city, including non-residential areas, but excluding the rural land that makes up large parts of most metropolitan areas when defined by administrative boundaries. I have not attempted to measure ‘urban’ density in this post.

Firstly here’s a table of data for the six largest Australian cities with three different measures of residential density:

You’ll notice that Melbourne has a lower population than Sydney, but the total land area above 3 persons/ha is much larger.

Here are those densities in chart form:

You can see Sydney has around double the population weighted density of most other cities, but its average density is only about 60% higher. These figures show Sydney has a very different density pattern compared other Australian cities.

You can also see very little difference in weighted density whether you exclude low density land parcels or not (the blue and red bars). The density is brought down only slightly by the relatively small number of people living in very low density areas (below 3 persons/ha) within the statistical geography. Thus weighted average density is a good way to get around arguments about the boundary of the “urban” area. But then we are only measuring residential density here – and the large unoccupied spaces between residents of a city are very important when it comes to transport issues.

Can you compare population weighted density of Australian cities with international cities? Yes, but only if the parcels of land used are of a similar size and created in a similar fashion. The more fine-grained the geography (ie smaller the parcels of land), the more non-residential pockets of land will be excluded from the calculation. Anyone doing an international comparison should compare how the ABS create their geography at SA1 level with approaches of other statistical agencies. And please comment below if you get a set of comparable figures.

Density by distance from the CBD

The differences in density can be seen a little more clearly when you look at weighted average density by distance from the city centre:

(note: I’ve chopped the vertical scale at 100 persons/ha so parts of central Sydney, Melbourne and Brisbane are off the scale).

For Perth, Adelaide, Brisbane and Canberra (ACT) you can see a weighted average density in the mid to low 20s for large areas of the city, indicating large tracts of what you might describe as traditional Australian suburbia. In Canberra this kicks in at just 2 km from the CBD, and in Adelaide it kicks in 3 km from the city.

In Melbourne the weighted average density doesn’t get below 30 until 9 kms from the CBD indicating a larger denser inner area, and in Sydney it doesn’t drop below 30 until you are 39 km from the CBD!

Distribution of population at different densities

Here’s a frequency distribution of densities in the cities:

I’m using an interval of 1 person/ha, and the figures are rounded down to form the values on the X axis (ie: the value you see at 20 persons/ha is the proportion of the population living between 20 and 21 persons/ha).

You can see Sydney has the flattest distribution of all – indicating it has the widest range of densities of any city. Melbourne is not far behind, whereas Canberra has a lot of people living in areas between 12 and 24 persons/ha.

Note that many cities have a significant proportion of the population living at rural densities (0 to 1 person per hectare), particularly Greater Brisbane.

Another way to look at this data is a cumulative frequency distribution:

You can read off the median densities for the cities: Sydney 33, Melbourne 28, Brisbane 22, Perth 22, Adelaide 22, Canberra 19.

You can also see that 30% of people in Sydney live in densities of 44 persons/ha or more – compared to only 12% of Melburnians, 5% of Brisbanites, and less than 2% of people in the other cities.

If 15-30 persons per hectare is what you define as suburbia, then that’s 26% of Sydney, 37% of Melbourne, 44% of Brisbane, 55% of Perth, 57% of Canberra and 62% of Adelaide.

Spatial distribution of density

For the purest view of density you cannot get past a map. The following maps show a simple density calculation at the SA1 geography.

Update 22 Oct 2012: maps now include railway lines using OpenStreetMap data provided by Maps Without Borders. The data is licensed under Creative Commons Attribution-ShareAlike 2.0, copyright OpenStreetMap and contributors.

Sydney

You can see vast areas of darker green (40+/ha), particularly between Sydney Harbour and Botany Bay. There are also quite a few green areas in the western suburbs, while the northern north shore has the lowest density. There are many concentrations of density around the passenger rail lines.

Melbourne (and Geelong)

You can see areas of dark green around the inner city, with large tracts of yellow and green in the suburbs (25-35 persons/ha). There are however areas of moderate green (30-40) in some of the newer outer growth areas to the west and north, reflecting recent planning. There’s a not a strong relationship to train lines, but this might reflect higher densities equally attracted to tram lines (not shown on the map).

Note this map is slightly different to that in a recent post where I masked out non-residential mesh blocks.

Brisbane

You can see dark green patches around the river/CBD, but then mostly medium to low densities in the suburbs. There’s very little evidence of higher densities in fringe growth areas. There are some denser areas around railway lines (note the map does not show Brisbane’s busway network).

Perth

You can see green patches around the city, but also in some fringe growth areas where new planning controls are presumably forcing up densities. There are however vast tracts of orange (15-25 persons/ha), and little evidence of higher density around the rail lines (note: a lot of the lines are freight only and the north-south passenger line has very broad station spacing and limited walking catchment as most of it is within a freeway median).

Adelaide

Adelaide some inner city blocks of high density, but once you get outside the green belt surrounding the city blocks, you fairly quickly head into suburban densities. There are only a few pockets of high density in the middle and outer suburbs, and very little relationship evident between density and the rail lines.

Canberra (and Queanbeyan)

Canberra has vast areas at low density, and only a few pockets with dark green. There are however green patches on the fringes (particularly in the far north and far south), perhaps again reflecting planning policies forcing up densities.

Sydney is really quite a different city compared to the rest of Australia, with a much larger share of the population living in high density residential areas (more than I had expected). Melbourne has a much lower population weighted density (still quite a few people living in high density areas, but much less so than Sydney), followed by four cities that aren’t that different when it comes to density: Brisbane, Perth, Adelaide and Canberra.

What about density and public transport use?

Here’s a comparison of density (measured as both average and population weighted) and the most recent estimate of public transport mode share of motorised passenger kms for Australian cities:

Population weighted density certainly shows a stronger relationship with public transport use than average density (r-squared of 0.89 versus 0.82 on a linear regression).

If you believe that higher population density will lead to higher public transport use (for a given level of public transport service), then you would expect Sydney to be well placed to have a higher public transport mode share. Which indeed it does, but does it have the same level of public transport supply as other cities, and are all other factors equal? That’s a very difficult question to answer.

You could measure public transport service kilometres per capita, but different modes have different speeds, stopping frequencies and capacities, public transport supply will vary greatly across the city, and some cities might have more effective service network designs that others.

If all cities had the same levels of public transport supply and all other things were equal, you might expect a straight line relationship (or perhaps an exponential relationship). But Brisbane and Melbourne (and to a small extent Perth) seem to be bucking what otherwise might be a linear pattern. Are these cities doing much better with quality and quantity of public transport supply? Or is it something else about those cities?

Car ownership rates do vary between Australian cities, but this might be more a product of public transport viability for particular residents:

Also, we know that car ownership doesn’t have a strong relationship with car use.

When working population census data comes out I would like to look at the distribution of employment within cities. We know that public transport use is highest for journeys to work in the CBD (as it usually competes strongly against the car), so the proportion of a city’s jobs that are in the CBD is likely to impact the public transport mode share (at least for journeys to work). Moreover, a higher average employment density in general might be easier to serve with competitive public transport, and thus lead to a higher public transport mode share. It will hopefully also be possible to calculate weighted density of employment (at least at the SA2 level).

Finally, I’d like thank Alan Davies (The Urbanist) for inspiring this post.

Other posts about density:

• A first look at 2011 Melbourne residential density, and how it has changed
• Visualising the changing density of Australian cities
• What does Melbourne’s urban density look like? (2006)
• Urban density and public transport mode share

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.

[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.

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:

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:

(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):

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

Walking only

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):

(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

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:

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 have the mode shares of journeys to work changed by different home locations in Melbourne?

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

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

Public transport

Public transport mode share is mostly up across the board. Some exceptions include:

• Langwarrin (east of Frankston)
• Dingley
• Greenvale
• Hillside
• Eastern parts of Rowville

Sustainable transport (only)

This map excludes those who used private transport to reach public transport. It shows that on the suburban fringe, the vast majority of people are still using private motorised transport to get to work. Areas without significant growth include Sunbury, South Morang, Greenvale, Rowville, Berwick north, Skye/Carrum Downs, Mt Eliza, Dingley, areas around the Ringwood-Lilydale rail line, and Westmeadows.

[minor corrections to map made 5 Nov 2012]

Train

There is growth across mode areas of Melbourne. You can see a massive difference in Roxburgh Park Craigieburn area following the extension of suburban electric services to Craigieburn.

Bus

You can see a substantial increases:

• in Doncaster area following the introduction of 7 SmartBus routes (including 4 to the CBD).
• in pockets between the Ringwood and Dandenong rail lines in the middle eastern suburbs. These areas had SmartBus routes introduced in 2002/2005, and perhaps it is taking a while to translate to bus in journey to work.
• Around Abbotsford/Collingwood, perhaps reflecting increased train crowding and introduction of four SmartBus routes along Hoddle Street creating an extremely frequent service to the city.

Tram

You can see increased mode share across the network, particularly around the outer end of the tram route to Bundoora (zone 2 only in 2006, included in zone 1 in 2011) (but less so in Vermont South).

Active transport (only)

You can see gains in the Brunswick, Northcote, Kew and Foostcray areas.

Walking only

I can see little change between 2006 and 2011, which is in line with little change in the overall share for Melbourne.

Cycling

Cycling continues to grow rapidly in the inner northern suburbs, but also a little to the inner east and inner south.

Train and Bicycle

With the introduction of Parkiteer cages at train stations, was there any increase in the number of people riding to train stations?

The numbers are so small, it is difficult to see spatially, but there was a substantial increase in overall numbers from around 1200 to 1800.

Train and bus

You can see increases around the Dandenong rail line, between the Glen Waverley and Ringwood rail lines, around Werribee/Tarneit, and around Sydenham.

Public transport mode shift by SLA

Here’s a map showing the mode shift towards public transport by Statistical Local Area (SLA), the smallest geography for which results are available for both the 2006 and 2011 censuses.

The biggest mode shifts were in the City of Melbourne, followed by Wyndham – south (Point Cook), South Yarra/Prahran, and Moreland – north. Nowhere in Melbourne did public transport mode share reduce.

I’m sure other people will find more patterns in the maps than I have been able to today. Please comment on any interesting finds. I might come back later and update this post when I have more time.

I will aim to do a similar exercise for other cities soon.

How have mode shares of journeys to work from different home locations changed in Perth? What impact has the new Mandurah rail line had?

In my post on city level mode share changes we saw that Perth had a 2.1% mode shift to public transport between 2006 and 2011. This post will uncover which areas shifted the most.

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

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

(I’ve used a slightly faster flip speed compared to my equivalent Melbourne post. Is this better? Please let me know).

Public transport

You can see dramatic increases in public transport mode share in the southern suburbs, most strikingly around Kwinana, Rockingham, and Atwell/Success/Hammond Park/Aubin Grove (south of Cockburn Central). You would have to say the new Mandurah rail line is fairly transformational public transport infrastructure.

You can also see people moved in near Clarkson train station (south-east corner of the urban block labelled “Clarkson” in the far north) and 29% of commuters nearest the station caught public transport to work (most on the fast train service to the Perth CBD). If Clarkson is supposed to be a transit orientated development with high public transport use, it seems to have been successful. The public transport mode share is extraordinarily high for such an outer suburban area. Note that Clarkson station opened in 2004.

Areas of Perth with little discernible shift to public transport include Ellenbrook, the Forrestfield/Kalamunda area to the east, and Ballajura (north-east of Mirrabooka). These outer suburbs do have bus routes linking them to the centre of Perth, but they don’t exactly get a high-speed run into the city.

Sustainable transport (only)

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

[minor corrections to map made 5 Nov 2012]

Train

As you would expect, there is a huge change in the southern suburbs around the new Mandurah rail line.

It is also interesting to see that train mode share was much higher north of Warwick than it is south of Warwick. In fact for the inner suburbs significant train mode shares only showed up in the immediate area around stations. Those further from the train line were a little less likely to use public transport, and were more likely to use buses, as the next map shows.

Bus

There’s not a lot of change across Perth. In particular, there isn’t much change in the middle southern suburbs (between Fremantle and Cannington). That might suggest the net increase in public transport mode share in this area came from people getting to train stations by modes other than feeder bus.

Ferry

I’ve added ferries for completeness. I’m not sure what conclusions you can draw, especially with the change in geographies between 2006 and 2011. Certainly ferries did get used by a group of commuters in the South Perth area to get across to the Perth CBD (note there is no train station in South Perth).

Train and bus

You can see the middle southern suburbs used feeder bus services in significant numbers, though not as strongly around Kwinana and Rockingham (perhaps parking at the station is easier?). Train + bus commuting also grew somewhat in the northern suburbs between Warwick and Joondalup, and west of Stirling.

Mode shift to public transport overall

Here’s a map showing the mode shift towards public transport by Statistical Local Area (SLA), the smallest geography for which results are available for both the 2006 and 2011 censuses.

The biggest mode shift was in Kwinana, followed by Perth – remainder (areas of the City of Perth excluding the CBD core), Cockburn, Canning and Melville – all around the new Mandurah rail line. Just off the map is the City of Mandurah area, which had a 5.7% mode shift to public transport (from 3.2% to 8.9%). Nowhere in Perth did public transport mode share go down, although in Kalamunda it was stagnant at 6.7%.

And before you get excited about Rottnest Island showing a mode shift to public transport, it is simply part of the Cockburn SLA. For the record, only 73 people on Rottnest travelled to work in 2011, 21% by bicycle and 64% by walking only (none by ferry or other public transport).

Walking only

The biggest change was in the CBD, where there is now a significant density of workers living (and thus making it onto the map). Walking to work was largely confined to the Perth CBD, around the University of Western Australia (UWA, east of Claremont), Fremantle, Joondalup, and Claremont

Cycling

Cycling has grown rapidly (off a small base), particularly in the inner northern and western suburbs, south of Fremantle, and around UWA.

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

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

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

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

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

Public transport

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

Sustainable transport (only)

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

Train

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

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

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

Bus

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

Ferry

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

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

Train and bus

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

Multiple public transport modes

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

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

Mode shift to public transport overall

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

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

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

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

Walking only

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

Cycling

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

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

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

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

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

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

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

Employment density

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

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

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

Mode share by workplace location

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

First up, public transport mode share:

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

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

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

Next is active transport:

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

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

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

Suburban destinations with high sustainable transport mode share include:

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

The significant rises are covered by the discussion above.

Commuting to the CBD

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

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

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

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

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

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

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

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

Pockets of high private motorised transport mode share include:

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

I understand that many of these are relatively wealthy areas.

Mode shift in journeys to the CBD

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

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

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

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

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

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.

The city centre is a traditional market for public transport, and certainly where public transport mode shares are the highest. Recent strong growth in city centre employment is likely to be the cause of public transport patronage growth in some cities. So I thought it would be interesting to look at public transport mode shares and mode shifts to workplaces within and outside Australian city centres.

Definition of city centres

First up, its important to understand what data I’m analysing. In 2011 the ABS restructured their geography for census and other data. While this change brings many benefits, it creates some challenges when comparing data from previous years. In the analysis I generally compare Statistical Local Areas (SLAs) with Statistical Area Level 2 (SA2) geography, but sometimes I’m just comparing Local Government Areas (LGAs).

Here are the areas I have used as the “central city” for each of the five large Australian cities:

Sydney

The “Sydney – Haymarket – The Rocks” SA2 which is very similar (but not entirely identical) to the “Sydney (C) – inner” SLA. There are only minor variations on the fringe of this area. On the following maps, the dark green area is included in all years, the red areas are only included in 2011, and the blue areas are only included in 2001 and 2006.

Melbourne

The “Melbourne” SA2 and the “Melbourne (C) – Inner” SLA, the former being larger as it includes a triangle of land between Peel/William Street, Victoria Street and Latrobe Street. City of Melbourne CLUE data from 2010 suggests 7.6% of jobs in the SA2 are in this triangle (and not included in the SLA). A previous post found that 2006 journey to work public transport mode shares in this triangle were around 56-61% whereas most of the CBD was around 60-70%. So this study is likely to understate increases in public transport mode share for central Melbourne.

Melbourne+

As Southbank and Docklands include significant employment density, I have created a second definition of central Melbourne that includes these areas, and labelled it “Melbourne+”. Note this area also gains the triangle north of the CBD for 2011 due to boundary changes. While arguably I should also include East Melbourne, data is not available at that resolution for 2001 and 2006, which would mean I would need to expand to include all of the City of Melbourne which is starting to be a lot more than the central city core.

The following map shows the Melbourne and Melbourne+ areas: the green area is included for all years, the red area is only included in 2011, and the yellow area is Southbank/Docklands, that is included in all years for Melbourne+ only.

Brisbane

The “Brisbane City” SA2, which precisely covers the “City – inner” and “City – remainder” SLAs combined. In 2006, “City – inner” accounted for 62% of the entire SA2 employment population, but the public transport mode share of the overall combined area was only about 1% lower than “City – inner”.

This Brisbane SA2 area is shown in green on the following map (the area in yellow represents Fortitude Valley and South Brisbane, referred to later in this post).

Adelaide

The City of Adelaide LGA (which includes North Adelaide). The new SA2 geography splits central Adelaide and North Adelaide, but historical data is not available at smaller resolution than the entire LGA. This area is shown in green in the following map:

Perth

The City of Perth LGA. While there are smaller SLAs and SA2s, there is weak correspondence between the old and new geographies so I had to use local government boundaries instead. This area is shown in green on the following map:

Mode shares for journeys to work in city centres

Previous posts have looked at public transport mode share overall for cities, and journey to work by work location for some cities (Brisbane 2006 and 2011, Sydney 2006, Melbourne 2006 with more to come). Here’s a look at the mode split for city centre areas (as defined above).

Note:

• as discussed above the central areas for Melbourne and Melbourne+ in 2011 are larger that for in 2001 and 2006
• Adelaide “2011i” refers to central Adelaide excluding North Adelaide.

The chart shows public and active transport mode share increasing in all cities, with the exception of Sydney where there was an increase in private transport use between 2001 and 2006. Public transport dominates in Sydney, Melbourne and Brisbane, with Perth now roughly evenly split between private and public transport, and private transport still being in the majority in central Adelaide. Active transport (walk/cycle) has posted significant gains in all city centres, with Melbourne having the highest share (9.0% in 2011) followed by Sydney (7.9%) and Brisbane (7.8%), with Perth the lowest (6.4%).

The above chart shows central Perth has having the strongest mode shift to public transport (in no small part due to the opening of the Mandurah rail line in late 2007), followed by Brisbane, and (perhaps surprisingly) then Melbourne (although Melbourne’s poorer performance may be related to the change in geographic boundaries as discussed above). Adelaide and Sydney were the laggards of public transport mode shift between 2006 and 2011.

Again, Perth is the stand-out in mode shift away from private transport in 2011.

Here is another look on the above mode split data with a little more detail, assigning each journey a “main mode” (precedence given to train, bus, any other public transport, vehicle driver, vehicle passengers, bicycle, in that order).

This chart shows trains accounting for around half of all journeys to work in central Sydney and Melbourne and buses being a significant mode in all cities except Melbourne where trams have a significant share. Notably Melbourne’s tram mode share is smaller than all the other cities’ bus mode shares. I note that Sydney is now moving to light rail to try to alleviate CBD bus congestion. Trains delivered less than 10% of central Adelaide commuters to work.

Vehicle passenger journeys are much more common in Adelaide (8.2%) and least common in Sydney, but are in decline in all cities, suggesting a move away from car pooling.

Central Melbourne is the leader in cycling with 3.3% of journeys primarily by bicycle, with Sydney the lowest bicycle share (1.4%).

Number of car journeys to city centres

The following chart shows the absolute change in the number of people whose primary method of journey to work was vehicle driver.

*Caution should be applied for Melbourne, as the 2011 geographic area included additional area that in 2006 (and that areas had a lower public transport mode share in 2006).

The stand-out result is Melbourne+, which indicates a lot more vehicle driver commuter trips generated as Docklands and Southbank employment centres expand. Public transport’s mode share for Southbank and Docklands combined increased from 39.4% in 2006 to 46.8% in 2011, but this was not enough to stop an increase in the overall number of vehicle driver trips. My understanding is that parking costs are generally cheaper in Southbank and Docklands compared to the CBD core.

There was a decline in city centre commuter car parking requirements in Sydney, Brisbane and Perth between 2006 and 2011, while central Adelaide had a substantial increase in vehicle driver commuters (despite some mode shift to public transport), no doubt putting pressure on traffic congestion.

Share of jobs in city centres

Are jobs within metropolitan areas concentrating within city centres? The following chart shows the percentage of metropolitan jobs located within the city centre areas defined above, as well as a wider city centre definition for Brisbane.

Comparing cities is dangerous as there is not a consistent definition of city centre. What the data does show is that central Perth is reducing its share of metropolitan jobs, central Adelaide’s share seems relatively static, central Sydney’s share is growing, and for Melbourne and Brisbane, the central city share is growing but only if you also include nearby employment-focussed areas (Southbank and Docklands for Melbourne, South Brisbane and Fortitude Valley for Brisbane).

In the above analysis I have used my own definitions for metropolitan areas, as ABS have changed from using Statistical Divisions to sometimes larger Greater Capital City Statistical Areas for metropolitan areas. See the appendix at the end of this post for how I have defined metropolitan regions.

Comparing journeys to work inside and outside city centres

Here is a chart comparing 2011 public transport mode shares for journeys to work inside city centres, outside city centres, and for each city overall:

The differences are very stark, but as you might expect as it is generally easier to drive and cheaper to park at workplaces outside the city centre (plus public transport service quality is often lower). Note that many city fringe areas are included in the “outside city centre” figures, and public transport mode shares are generally higher in these areas, and lower further out. You can see the mode share for trips to workplaces outside “Melbourne+” (Melbourne + Southbank + Docklands) is only 9%.

Here’s the trend for public transport mode share to destinations outside city centres, showing increases between 2006 and 2011 for all cities except Adelaide.

The following chart shows that mode shifts to public transport have been much higher in central city areas for Brisbane, Perth and Adelaide, but not Sydney (low mode shift to both city centre and elsewhere) and Melbourne. Mode shift to public transport outside the “Melbourne+” city centre was just over 1%.

Growth in public transport for journeys to work versus all purposes

The following chart compares the growth in the absolute number of people choosing public transport to get to work (between census 2006 and 2011), versus overall growth in public transport patronage (comparing financial years 2010-11 to 2005-06).

Note: For Brisbane, the overall patronage growth figure refers to all of South East Queensland (SEQ).

In all cities except Melbourne, the number of public transport journeys to work increased faster than overall patronage, suggesting growth in public transport use for other trip purposes was weaker.

Do city centres dominate journeys to work by public transport?

We think of city centres as the main workplace location where people would use public transport to get to work. But is this accurate?

The answer is yes in the smaller cities, no in Sydney, and in Melbourne it depends on whether you include Southbank and Docklands.

Conclusions

We have seen that:

• Public transport is the dominant mode of journeys to work in city centres in the larger cities, but a minority mode in central Adelaide
• Perth has shown the greatest shift to public transport for travel to the central city
• Melbourne has shown the greatest shift to public transport for journeys to work overall
• Melbourne has the highest active transport (and bicycle-only) mode share for journeys to city centres
• In Brisbane, Perth and probably the Melbourne CBD, there was a net decline in private vehicles being driven to city centres for work between 2001 and 2011
• Public transport’s share of journeys to workplaces outside city centres is much lower in all cities
• Mode shift to public transport for journeys to work was higher for city centres except Sydney and Melbourne
• Growth in public transport use for journeys to work was higher than overall public transport patronage growth in all cities except Melbourne
• The central city share of all metropolitan jobs is increasing in Sydney, Melbourne (when Southbank and Docklands are included), and to a lessor extent Adelaide. Central Perth and Brisbane are declining in their share of metropolitan jobs.
• Most public transport journeys to work in the smaller cities are to the city centre, but this is not the case for Sydney and Melbourne (without Southbank and Docklands)

Appendix: Common definitions of city metropolitan regions 2001-2011

The change in ABS geography makes it difficult to have a fair time series estimate of the total number of jobs in each metropolitan area. To try for maximum consistency across the change, I have calculated the number of jobs in each city as follows:

Melbourne: Melbourne Statistical Division, plus Shire of Yarra Ranges – Part B (ie includes all of the Shire of Yarra Ranges)

Perth: Perth Statistical Division plus the City of Mandurah (which was incorporated into the Greater Perth definition in 2011)

Brisbane: The Greater Brisbane Capital City Geographic Area, which for 2006 was approximated by the Brisbane Statistical Division plus the SLAs of Beaudesert Part C, Beenleigh, Bethania-Waterford, Boonah, Eagleby, Edens Landing-Holmview, Esk, Kilcoy, Laidley, Mt Warren Park and Wolfdene-Bahrs Scrub.

Sydney: there are very few differences between the Sydney Statistical Division and Greater Sydney, so I assumed equivalence.

Adelaide: All LGAs in the Adelaide Statistical Division, including all parts of the Adelaide Hills Council.

My earlier post about Melbourne journey to work 2011 focussed on where people live. This post focuses on where people work and what modes of transport they used to get there in 2006 and 2011. It also covers employment density and the home locations and associated mode shares for people travelling to the central city.

As per other posts, you will need to click on maps to see the detail/animation.

Note: I have mode share data at work place locations at destination zone level for 2006 (smallest resolution available) but only at SA2 level for 2011. For the purposes of direct comparison, I have mapped 2006 destination zones to SA2s based on the centroid of each 2006 destination zone (so not a perfect mapping – see here for a comparison map).

See also an earlier similar post covering 2006 journey to work data for Melbourne, and a similar post covering journeys to workplaces in Brisbane.

Employment density

Firstly, what does the employment density of Melbourne look like? If I had travel zone data for both years I’d be able to draw a much higher resolution picture, but for now I will have to suffice with SLA/SA2 employment density. Note that 2011 SA2s are generally smaller than 2006 SLAs so this isn’t a direct comparison.

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

I do note the absence of many relatively dense employment areas on the western side of Melbourne.

Mode share by workplace location

Public transport

Public transport mode share was highest in the CBD, then for areas around the CBD and stretching a little more to the inner east. Box Hill stands out as a suburban location with a relatively high mode share (13% in 2011).

Here is a map that shows the mode shift for each SA2 (bearing in mind that there isn’t a perfect mapping from 2006 destination zones to 2011 SA2s):

The biggest mode shifts to public transport were:

Most of the above are in the inner city, but there are exceptions of Watsonia, Mount Evelyn and Springvale South (all off a very small base in 2006).

Some interesting rises in the suburbs include:

• Doncaster 5.5% to 8.3%, probably related to the introduction of several SmartBus services
• Frankston North 2.6% to 5.0%, again probably influenced by the introduction of SmartBus services
• Forest Hill 5.2% to 7.8% (not sure why)
• Mill Park North 1.7% to 4.2% (note the South Morang rail extension was not open in 2011, but SmartBus services had been introduced by the 2011 census)
• Box Hill 10.2% to 12.7%, possibly related to upgraded SmartBus services
• Noble Park 3.0% to 5.4% (not sure why)

Some interesting declines include:

• Montrose – there are boundary differences between 2006 and 2011 with many more jobs counted in 2011.
• Cairnlea 6.6% to 2.4% (probably because Victoria University St Albans Campus is mapped to this SA2 in 2006 but not 2011)
• Carlton North – Princes Hill 13.1% to 10.4% (which also had an increase in walking and cycling)
• Port Melbourne 14.7% to 12.6% (not sure why, perhaps more people walked to work from the increasingly dense local residential area)

As an aside, here are 2011 public transport mode share for journeys to work at major Australian airports (where there is an “Airport” named SA2):

• Sydney 13.9%
• Melbourne 3.8% (up from 2.5% in 2006)
• Brisbane 3.1%
• Adelaide 2.6%
• Perth 1.7%
• Darwin 1.7%

Train

Train mode share was highest in the CBD and surrounding inner city areas. Notably, mode shares were relatively higher in the inner east and south-east (particularly Caulfield, Camberwell and Hawthorn) compared to other axes.

Here is the mode shift to trains between 2006 and 2011:

The biggest rises were in Docklands (up 9.2%), South Yarra (up 5.6%) and then a few other inner suburban destinations.

In 2011, 47% of journeys to work in Greater Melbourne involving train were to the Melbourne CBD. This rises to 59% when adding Southbank and Docklands.

Tram

Unfortunately I do not have 2006 data for “any journey involving tram” below the SLA level, so here is the 2011 picture at SA2 level, with the tram network shown as green lines:

I must say I was surprised by the CBD figure of only 14.9% (and I did double-check the data).

Tram mode share was highest in the SA2s of Albert Park and South Yarra West (which straddle the St Kilda Road office precinct which has very high tram frequencies). Other work destinations with higher tram mode shares included Parkville, Carlton, Fitzroy and South Melbourne.

Perhaps there was some under-reporting of tram journeys as a “secondary” mode in people’s journey to work? In Parkville (which includes the main University of Melbourne campus, the hospitals precinct and Royal Park), there were more people reporting only train (934) than train+tram (772) and train+bus (275). I would expect most of those jobs to be remote from Royal Park station, and the southern section of the SA2 is at least a 1 km walk from Melbourne Central train station. Another example is South Melbourne – all of which is more than 1.2 km from a train station, yet 1240 people reported only train in their journey to work, while 894 reported train+tram. While of course some people will walk longer distances from train stations to work, the numbers seem a little high to me.

37% of journeys to work in Greater Melbourne involving tram were to a destination in the Melbourne CBD. If you add in Southbank, Docklands, Parkville and South Melbourne the share goes to 56%.

Bus

Again, I do not have comparable data for 2006, so here is a 2011 map:

Bus mode share was highest in Malvern East (which includes Chadstone Shopping Centre), followed by Doncaster, Maribyrnong (which includes Highpoint Shopping Centre), Carlton and the Melbourne CBD. Mount Evelyn is curiously high at 5.8%, with 45 people travelling by bus to workplaces there.

Only 21% (9905) of journeys to Greater Melbourne workplaces involving bus were to the CBD, with the next highest SA2 counts in Docklands (1175), Clayton (1160), Dandenong (1157), Southbank (1071) and Parkville (1046). This would suggest that growth in CBD employment is unlikely to be one of the major factors in bus patronage growth in Melbourne (unlike train and tram).

Cycling

Due to the nature of the data I have for 2006, this analysis excludes journeys also involving public transport or trucks (yes, there were 39 people who said they travelled to work by truck and bicycle in Australia in 2011!):

Cycling to work boomed in inner Melbourne between 2006 and 2011, particularly to workplaces in the inner north, with the Parkville SA2 recording the highest bicycle share.

Here’s a view of the mode shift to bicycle:

The biggest mode shifts towards bicycle were for workplaces in the inner northern suburbs, while relatively small mode shifts away from bicycle were observed in the outer eastern suburbs and around Aspendale to Carrum.

I should point out that the census is conducted in winter (August), and warmer weather bicycle mode shares of journeys to work are likely to be higher.

Walking (only)

Walking mode share is a mixed bag across the city. High walking mode shares are evident in Parkville, Carlton North/Princes Hill, around St Kilda, the Simpson Army Barracks (in Yallambie), but also some rural areas. In the Koo Wee Rup SA2, 8.7% of employees walked to work, 41% of whom were in the “Agriculture, Forestry and Fishing” industry.

The lowest walking only mode shares were at the major airports (Melbourne, Essendon and Moorabbin), some industrial areas and generally in the outer suburbs of Melbourne.

Here is mode shift to walking:

Mode shift to walking was more common in the northern suburbs and some outer eastern suburbs, but not so much in the inner city. Mode shift away from walking only to work was observed in many outer eastern and north-eastern suburbs.

Note: the neighbouring SA2s of Wheelers Hill and Glen Waverly East each showed mode shifts in opposite directions. This is almost certainly to do with the Police Academy being mapped into a different SA2 in 2006 due to the imperfect mapping between 2006 destination zones and 2011 SA2s.

Sustainable transport

I’ve defined sustainable transport here as any journey involving public transport, plus any journey that only involved walking and/or cycling.

Sustainable transport mode share was highest in the CBD and immediate surrounding areas. Sustainable transport was relatively higher for workplaces in the inner north, east and south-east compared to the inner west.

Mode shift to sustainable transport was most prevalent in the inner north and inner south.

Some interesting suburban mode shifts to sustainable transport include:

• Upwey - Tecoma (mainly walking)
• Dandenong North (mostly a mix of walking and public transport)
• Gladstone Park - Westmeadows 3.1% (most of which was public transport mode shift, possibly relating to the introduction of SmartBus services),
• Altona Meadows (mostly public transport, perhaps relating to the City West waste purification plant being mapped into this SA2 only in 2006 but this is not clear)
• Watsonia (possibly a result of destination zone to SA2 mapping issues )

Commuting to the central city, 2011

The central city is an important destination as it has the highest employment density and public transport is best-placed to compete against the car. For analysis in this section I am using the combination of the Melbourne CBD, Southbank, Docklands, Carlton, North Melbourne and East Melbourne SA2s as my definition of the “central city” (which is different to other posts on this blog – I am deliberately choosing a larger area to get a better sense of origins and mode shares).

Here’s a map showing the proportion (%) of commuters who had a destination of central Melbourne in 2011 (by place of usual residence at SA1 geography):

The prevalence of the CBD as a work destination is almost directly proportional to the distance people live from the CBD, although rates are relatively higher around train lines.

Notable outliers include:

• Point Cook, Tarneit, Caroline Springs in the western suburbs with a higher central city share, possibly reflecting a workers-to-jobs imbalance in the outer western suburbs, particularly for white-collar workers (I might explore that more in a future post)
• East Doncaster, which has a relatively high central city share, possibly as a result of frequent express bus services to the city
• A pocket of St Kilda East and Caulfield North between the Sandringham and Caulfield rail lines that has a low share despite being relatively close to the city (not sure why that might be)

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

Note: I have not filtered SA1s by density on the following maps (unlike others), so some low density SA1s are included.

Public transport mode share was particularly high for those in middle to outer suburbs (where such a long drive would probably not be fun or cheap).

It was lowest around:

• the city centre itself (more on that in a moment)
• Western Kew in the inner east (a relatively wealthy area)
• Sanctuary Lakes in the south-western suburbs (largely remote from public transport in 2011)
• Pockets of Caroline Springs
• Areas of Templestowe, Donvale, Research and North Warrandyte in the east-north-eastern suburbs
• Areas north of Sunbury
• Areas around Keilor East and Avondale Heights (like Kew, close to the CBD but remote from train lines)
• Greenvale (a relatively wealthy area)
• Brighton and Toorak (very wealthy areas)

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

This map is largely the inverse of the previous map, except for areas near the inner city, suggesting active transport is being used by residents of the central city to get to work in the central city, as you might expect.

Finally, here is a map showing the density of people who work in the central city:

This map effectively combines population density with the proportion of workers travelling to the central city. The density falls away with distance from the city (quite markedly south of Elwood), but there are outliers in pockets of Carnegie, Point Cook, East Doncaster, Deer Park, Mitcham, Bundoora, and Heatherton (not all of which are connected to the city by high quality public transport).

A similar analysis could be conducted to other employment centres, although numbers per SA1 will be much smaller, and it would be time-consuming.

If you spot any other interesting changes and/or have explanations for them, I would welcome comments.

It seems public transport intermodal integration is a frequent topic of conversation in Australia’s larger cities. So how multi-modal is public transport travel in our cities?

In this post I’ll look at journeys to work from the 2011 census for the five larger Australian cities with multi-modal public transport networks. The results might not be quite what you expect.

Before looking at the data, I think it is important to think about the factors that might influence the degree of multi-modal public transport commuter trip-making, particularly with regard to radial trips towards city centres:

• Commuters from the middle and outer suburbs are more likely to require a rapid transit component to their commute to ensure an attractive travel time.
  • Cities with CBD-orientated busways (primarily Brisbane, Adelaide and to a lesser extent Perth) are perhaps less likely to see multi-modal journeys as buses provide both the local pick up and the rapid transit component of the journey.
  • Cities with more extensive train networks are also perhaps less likely to see multi-modal journeys because a greater share of the population will be within walking distance of a train station and not require a feeder mode (eg bus).
• In cities where transfers are a fundamental part of the network design, there might be higher transfer rates. For example, very few middle and outer suburban bus routes in the larger cities service the CBD, rather they run to train stations where passengers generally transfer to trains to access inner city areas. This is particularly the case in Melbourne and Perth.
• The same issue applies for people arriving in city centres. For example, Sydney ferry commuters travelling to areas of the CBD not within easy walking distance of a ferry terminal would need to transfers to buses or trains. Adelaide only has one train station which is on the edge of the CBD, effectively forcing transfers onto buses or the tram for most CBD destinations. Perth has two main CBD train stations, although the core employment areas are within reasonable walking distance of these stations. That said, one might argue that an ideal integrated public transport network would encourage people to use local modes (bus or tram) to travel between destinations and major transport nodes within city centres (in all cities except Sydney, such transfers are almost always free). All cities do offer street-based public transport to help circulate commuters within city centres. I also wonder whether these short trips within city centres might be under-reported in census data (perhaps something to explore another time).

Journeys to work in city centres

So, what percentage of all journeys to work in city centres involve multiple public transport modes? (see note at the end of this post about estimation for 2001 figures)

Note the definitions of city centres aren’t perfectly comparable (see earlier post for maps):

• Melbourne is primarily the CBD (excluding Southbank and Docklands)
• Perth includes all of the City of Perth
• Adelaide includes North Adelaide (entire of City of Adelaide)
• Brisbane is the “Brisbane City” SA2

The first thing to note is that the share of commuters who use multiple public transport modes is very low (considering public transport mode share to city centres is generally very high).

The following chart shows the proportion of public transport journeys to work in city centres that involved multiple modes of public transport:

The vast majority of people who use public transport to access jobs in city centres only use one mode. Given that most city centre workers don’t actually live all that far from the CBD, it’s not too surprising as an overall pattern.

Perth is the stand-out for highest multi-modal public transport travel, and largest increase in this type of journey between 2006 and 2011. A few things might explain this:

• Perth’s rapid transit network is relatively sparse (five train lines and one busway), meaning fewer people can walk to a rapid transit station.
• Indeed, most train stations on the northern and southern lines have very limited walking catchments, but relatively strong bus feeder services and excellent interchange layouts that make transferring easy.
• The increase between 2006 and 2011 is no doubt related to the Mandurah line where many previously bus-only journeys have been replaced by bus-train journeys, but it might also relate to improved feeder bus services on other lines.
• Perth’s high multi-modal share may also reflect a strong focus on timetable coordination. My understanding is that Transperth don’t try to “optimise” train-bus connection times, they force bus timetables to have ideal bus-train connection times, with high vehicle utilisation a secondary priority.

Melbourne comes in second (if Southbank and Docklands were included, the 2011 figure would be 10.3%). Interestingly, there were more train+bus journeys to the city centre, than train+tram journeys.

Sydney is third, despite having four modes of public transport. This perhaps reflects the lack of a fully integrated fare system (ie multi-modal tickets are usually more expensive that single-mode tickets) and the fact many bus routes run parallel to train lines (and it is usually cheaper to stay on the bus rather than transfer onto the train). It’s not clear to me why Sydney would have had a reduction in multi-modality between 2001 and 2006.

Brisbane had a much lower multi-modal share, probably related to a high bus mode share, the presence of busways providing efficient single-mode (often single-seat) travel for a large number of commuters to the central city, many bus routes running parallel to train lines, and the only relatively recent introduction of full multi-modal fare integration in 2004-05.

Adelaide also rates lowly and has been in decline, perhaps relating to the low-frequency train system (that is now receiving an upgrade including electrification). The extension of the Adelaide tram route from Victoria Square to the Entertainment Centre may have reduced the need for existing tram passengers to transfer, but on the other hand may be helping to circulate people arriving in the city on buses and trains.

Outside city centres

The following chart shows how multi-modality compares for public transport journeys to work in city centres and elsewhere:

Public transport journeys to work in locations outside city centres were much more likely to involve multiple modes, which makes sense as direct rapid services are probably less likely to be available to reach such workplaces. Keep in mind also that public transport mode share of journeys to workplaces outside the city centre are much lower.

Here are the trends over time for multi-modality of public transport journeys to workplaces outside city centres. It shows increases in Perth and Brisbane, declines in Adelaide and Sydney, and little recent change in Melbourne:

Perhaps the increase in Brisbane might be attributed to full multi-modal fare integration introduced in 2004/05, providing free transfers between modes. The increase in Perth is no doubt related to the Mandurah rail line opening.

So is the city centre the main destination for multi-modal public transport journeys to work?

In the larger cities the answer is no. In Adelaide and Perth – where over 60% of PT journeys to work are to the CBD – only around half of the multi-modal PT trips are to the city centre.

While a large proportion of multi-modal public transport journeys to work are not to the city centre, I would expect most would still be radial in nature (as jobs are on average closer to the city centre than homes). This is perhaps something to explore in a future post (my guess would be concentrations of multi-modal public transport travel to workplaces surrounding the city centre).

Finally, I’ve had a look at the home origins for multi-modal public transport journeys to work for Melbourne and Perth in 2011. Click to enlarge maps, and note the colour scale is for mode shares 1 to 10%.

In Melbourne the highest concentrations are north of Footscray, where several frequent tram and bus routes feed Footscray station. There are also concentrations in the middle-eastern and middle-northern suburbs, particularly around SmartBus routes.

In Perth the highest concentrations are in the northern and southern suburbs, where frequent bus routes connect people’s homes to high-speed train services in peak periods.

My next post will continue the multi-modal theme and look at what modes were used in conjunction with trains in the journey to work.

Footnote regarding 2001 estimates

Available data for 2001 only shows mode share in an aggregated summary, including figures for “train and two other modes” and “bus and two other modes”. Not all of these journeys involved multiple public transport modes, and I don’t know exactly how many did.

To estimate 2001 figures of total multi-modal PT journeys, for each city I have calculated the proportion of 2006 journeys that would come under these headings that actually involved multiple PT modes (as detailed data is available for 2006), and then applied these percentages to the 2001 figures for “train and two other modes” and “bus and two other modes” figures.

The result is that around 20% of the total 2001 multi-modal PT journeys are estimated.

I also checked these percentages in the 2011 data, and they were very similar to 2006. For example, 89% of journeys that could be described as “train and two other modes” in 2006 for Melbourne involved multiple PT modes, and in 2011 that figure was 88%. The similarities were weaker for “bus and two other modes”, but the numbers for this category were very small (less than 65 journeys in all cities except Sydney at 145).

Who is cycling to work? Where do they live? Where do they work? How old are they? What work do they do? Do men commute by bicycle more than women? How far are cyclists commuting? What other modes are cyclists using?

The census provides some answer to these questions for the entire Australian working population, albeit for one winter’s day every five years.

This post builds on material I presented at the Bike Futures 2013 conference, using census data from across Australian with a little more detail on capital cities and my home city Melbourne.

It’s not a short post, so settle in for 13 charts and 17 maps of data analysis.

How has cycling mode share changed over time?

The first chart shows the proportion of journeys to work by bicycle (only) in Australia’s capital cities.

Darwin appears to the capital of cycling to work, although it is quickly losing ground to Canberra (unfortunately I don’t have figures for Darwin pre-1996).  The census is conducted in Darwin’s dry season, but other data suggests there is little difference in bicycle activity between the wet and dry seasons.

Melbourne has shown very strong growth since 2001 and Sydney showed strong growth between 2006 and 2011. Cycling mode share has grown in all cities since 1996.

Mode shares collapsed in Adelaide, Sydney, Brisbane, and Melbourne between 1991 and 1996, which many people have attributed to the introduction of mandatory helmet laws (Alan Davies has a good discussion about this issue on his blog).

But as I pointed out at the start, census data is only good for one winter’s day every five years. Does the weather on these days impact the results?

Here is a chart roughly summarising the weather in (most of) the capital cities for 2001, 2006 and 2011 in terms of minimum temperature, maximum temperature and rainfall. It doesn’t cover wind, nor what time of day it rained (although perhaps some fair-weather cyclists might avoid riding on any forecast rain). It also fails to show the sub-zero minimums in Canberra (involves asking too much from Excel).

You can see that 2011 was wetter in Adelaide and Hobart than previous years, and this coincides with lower cycling mode shares in these cities in 2011. So census data is quite problematic from a weather point of view. That said, most cities had very little or no rain on the last three census days.

Where were the commuter cyclists living and working?

Other posts on this blog have also covered some of these maps, but not for all cities.

Some of the following maps are animated to show both 2006 and 2011 results, and note that the colour scales are not the same for all maps. I’ve sometimes zoomed into inner city areas when these are the only places with significant cycling mode share. White sections on maps represent areas with low density, or where the number of overall commuters was very small (sorry I haven’t gone to the effort of making every map 100% consistent, but rest assured the areas in white are less interesting). Click on the maps to see more detail.

Canberra

Firstly home locations:

The cycling commuters mostly appear to be coming from the inner northern suburbs. I don’t know Canberra intimately, but Google maps doesn’t show a higher concentration of cycling infrastructure in this area compared to the rest of Canberra.

Secondly, bicycle mode share by work destination (at the larger SA2 geography):

The highest mode share was 12% in the SA2 of Acton, which is dominated by the Australian National University. Perhaps a lot of the university staff live in the inner northern suburbs of Canberra?

Melbourne

By home location:

Cycling mode share is highest for origins in the inner northern suburbs and has grown strongly since 2006. There’s also been some growth in the Maribyrnong  and Port Phillip council areas off a lower base.

By work location (note: this data is at the smaller destination zone geography):

Cycling to work boomed in inner Melbourne between 2006 and 2011, particularly to workplaces in the inner north. Princess Hill had the highest bike share of 14% in 2011 (possibly dominated by Princess Hill Secondary College employees), followed by a pocket of south-west Carlton that jumped from around 5% to 13%. Apart from the inner north, there were notable increases in Richmond, Balaclava, Yarraville and Southbank. Cycling rates within the CBD are relatively low, perhaps reflecting limited cycling infrastructure on CBD most streets in 2006 and 2011.

Adelaide

Firstly, by home:

Adelaide appears to lack any major concentrations of cycling, although slightly higher levels are found just outside the parkland surrounding the CBD.

Secondly, bicycle mode share by work destination at the (larger) SA2 geography:

The numbers are all small, with 3% in the (large) Adelaide CBD. I imagine a map based on destination zones might show some pockets with higher mode share, but that data isn’t freely available unfortunately.

Perth

By home location:

The inner northern and western suburbs, and south of Fremantle seem to be the main areas of cycling growth.

For workplaces at the larger SA2 geography:

The highest mode share was in ‘Swanbourne – Mount Claremont’, only slightly ahead of ‘Nedlands – Dalkeith – Crawley’ – which contains the University of Western Australia. The Fremantle SA2 (with 3% bicycle mode share by destination) includes of Rottnest Island where around 20% of the 73 resident commuters cycled to work, but the result will be easily dominated by the mainland Fremantle section.

Again, I suspect some smaller pockets would have had higher mode shares if I had access to destination zone data.

Brisbane

By home location:

There was significant growth in cycling from the West End, and around the University of Queensland/St Lucia – which may be related to the opening of the Eleanor Schonell Bridge (after the 2006 census) which only carries pedestrians, cyclists and buses.

By work location (at larger SA2 geography):

The highest share was in St Lucia – which is probably dominated by the University of Queensland. Neighbouring Fairfield – Dutton Park came in second. These two areas are directly joined by the Eleanor Schonell Bridge which provides cycling a major advantage over private transport. It seems to have been quite successful at promoting cycling in these areas.

Sydney

First by home location:

There were quite noticeable shifts to cycling in the inner south and around Manly.

By work location (by smaller destination zone geography):

There was strong growth, again in the inner southern suburbs. In 2011 bicycle mode share was highest in Everleigh (11.5%) following by the University of NSW (Paddington) at 7.9% (excluding travel zones with less than 200 employees who travelled).

Rural Australia

Here’s a map showing bicycle share by SA2 workplace location for all of Australia, which gives a sense of bicycle mode shares in rural areas.

Higher regional/rural bicycle mode shares are evident in southern Northern Territory (Petermann – Simpson), Katherine (NT), the Exmouth region, the Otway SA2 on the Great Ocean Road in western Victoria, and Longford – Loch Sport in eastern Victoria. I’ll let other people explain those.

The SA2s in Australia with the highest cycling mode shares in 2011 (by home location) were:

• Lord Howe Island, NSW: 21%
• Acton, ACT (covering Australian National University): 12%
• Port Douglas, Queensland: 10%
• Parkville, Victoria (covering the University of Melbourne main campus): 8%
• East Side, Northern Territory (Alice Springs): 8%
• St Lucia, Queensland (covering the University of Queensland): 8%

How far did people cycle to work? (in Melbourne)

It is difficult to get precise distances for journeys to work, but approximations are possible. I’ve calculated the approximate distance for each journey to work by measuring the straight line distance between the centroid of the home and work SA2s and then rounded to the nearest whole km. To give a feel for how this looks, here is a map showing inner Melbourne SA2s and the approximate distances between selected SA2s:

This distance measure generally works well in inner city areas. However in the outer suburbs SA2s are often much larger in size, and sometimes only partially urbanised. However as we’ve seen above the volumes of cycling journeys to work are very low in these places, so that hopefully won’t skew the results signficantly.

Two-thirds of cycling journeys to work in Melbourne were approximately 5km or less, with 80% less than 7 km, and 30% were 2 km or less.

The longest commute recorded within Greater Melbourne was approximately 44km.

Was cycling combined with other modes?

The following chart shows that bicycles were seldom combined with other modes:

Around 16-17% of cycling commuters in the four largest cities in 2011 involved another mode. Use of other modes with cycling grew in all cities between 2006 and 2011

The next chart shows what these other modes were:

Sydney, Melbourne, Brisbane and Perth had high rates of bicycle use with trains, while combining car and bicycle was more common in the smaller cities.

The next chart shows the number of trips involving bicycle and trains in 2006 and 2011:

The chart shows the relative success of Melbourne Parkiteer program of introducing high quality bicycle cages at train stations, which has helped boost the number of people access the train network by bicycle by around 600 between 2006 and 2011. I understand a similar project has been undertaken in Perth which saw growth of around 250.

In Melbourne, the home locations for people using bicycle and train are extremely scattered – the following map shows a seemingly random smattering:

How does commuter cycling vary by age and sex?

This chart shows remarkably clear patterns. Males were much more likely to cycle to work. Teenage boys (particularly those under driving age) had the highest cycling mode shares (with teenage girls much less likely to cycle). The next peak for men was around the mid thirties, and women’s mode share peaked around ages 28-32.

Where are women more likely to cycle to work?

Women are sometimes talked about as the “indicator species” for cycling – ie if you have large numbers of women cycling compared to men then maybe you have good cycling infrastructure that attracts a broader range of people.

The census data can shed some light on this. For each SA2 in Melbourne, I have calculated the male and female cycling mode shares both as a home origin, and as a work destination (this analysis looks at people who only used bicycle (and walking) in their journey to work). I’ve then calculated the ratio of male mode share to female mode for each area (SA2).

I’ve used the ratio of mode shares in preference to the straight gender split of cycling commuters – as female workforce participation is generally lower and there can be spatial variations in the gender split of the workforce. 46% of all journeys within Greater Melbourne in the 2011 census were by females, but only 28% of cycling journeys to work were by females.

The following map shows the ratio of male to female cycling mode shares by home location for SA2s (with more than 50 commuter cyclists, and where the bicycle mode share is above 1%):

Areas attracting comparable female and male bicycle shares include the inner northern suburbs and – curiously – Toorak (probably many using the off-road Gardiners Creek and Yarra Trails to access the city centre).

Here’s a similar map, but by workplace areas:

The patterns are much more pronounced. Six SA2s had higher female mode shares than male: Yarraville, Fitzroy North, Brunswick East, Ascot Vale, Carlton North – Princes Hill, and Elsternwick.

The areas with near-1 ratios of male to female mode shares were similar to the areas with higher total cycling mode shares. The following chart confirms this relationship (note areas with cycling mode shares below 1% not shown):

What this also shows is that home-area mode shares reach much higher values than workplace-area mode shares. Perhaps the secret is in the home-area cycling infrastructure? Or perhaps it’s more to do with the residential demographics?

See the Bicycle Network Victoria website for more data about female cycling rates in Melbourne.

Do women cycle the same distances as men?

Again using the approximate straight line commuting distances (as explained above) the following chart shows that women’s cycling commutes are a little shorter than men’s, but not by much:

The median female cycling commute was approximately 1.8 km shorter than for males.

What types of workers are more likely to cycle to work?

Firstly, I’ve looked at the differences between public and private sector employees.

Before I dive into the data, it’s important to recognise that different types of workers are not evenly spread across Australia. Some types of jobs concentrate in city centres while others might be more likely to be found in the suburbs or the country. Therefore many of the following charts show results for Australia as a whole, but also for people working in central Melbourne (the SA2s of Melbourne, Carlton, Docklands, East Melbourne, North Melbourne and Southbank), which has a relatively high rate of cycling to work.

The data suggests public servants were much more likely to cycle to work:

The local government result has prompted me to calculate the cycling mode shares for local government workers across Australia (assuming workers work within the council for which they work). Here are bicycle mode shares for the top 20 councils for employee cycling mode share in the census:

Most of the top 20 are non-metropolitan councils. Melbourne’s City of Yarra is the top metropolitan city council (within Greater Melbourne the next highest councils are Moreland 6.1%, Port Phillip 5.6%, Melbourne 5.6% and then Stonnington 4.9%).

National government employees had the highest bicycle mode share of all of Australia. I suspect this relates to university staff, as many of the earlier maps showed university campuses often had relatively high rates of employees cycling (85% of “higher education” employees count as “national government” employees).

The census data can also be disaggregated by income:

Cycling mode shares were highest for people on high incomes. Initially I thought this might reflect the fact that high income jobs are often in city centres were cycling is relatively competitive with private and public transport. However, even within central Melbourne workers, cycling rates are higher for those on high incomes (curiously with a second peak for those on incomes between $300 and $399 per week).

Does cycling to work make you healthier and therefore more likely to get promoted and earn a higher income? Or are employers offering workplace cycling facilities to attract highly paid staff? I haven’t got data that answer those questions.

Consistent with higher rates of cycling for higher income earners, those in more highly skilled occupations were more likely to cycle to work:

I suspect this might reflect the presence/absence of workplace cycling facilities (perhaps office workplaces are more likely to provide cycling facilities than retailers for example) and/or the ability to afford to live close to work (which makes cycling easier).

Are recent immigrants more likely to ride to work?

This one really surprised me and I only investigated it because it was possible to do. The census asks what year people migrated to Australia (if not born here), and it turns out that recent immigrants were much more likely to cycle to work:

This might be explained by the demographics of recent immigrants (eg car ownership, home location, income levels, occupation and age).

I’d welcome comments on any other trends people might spot in the data.

This post charts some key Australian transport trends based on the latest available official data estimates as at January 2017 (including the Bureau of Infrastructure, Transport, and Regional Economics 2016 Yearbook).

Car use per capita has continued to decline in most Australian cities (the exceptions being Adelaide and Brisbane, but still well down on the peak of 2004):

Mass transit’s share of motorised passenger kms was very slightly in decline in most cities in 2014-15 (the exceptions being Sydney and Adelaide)

(note: “mass transit” includes trains, trams, ferries, and both public and private buses)

At the same time, estimated total vehicle kilometres in Australian cities has been increasing:

However, mass transit use has outpaced growth in car usage since 2003-04 across the five big cities:

In terms of percentage annual growth, car use growth only exceeded mass transit in 2009-10, and 2012-13.

Car ownership has still been slowly increasing (note the Y axis scale):

Australia’s domestic transport greenhouse gas emissions actually ever-so-slightly declined in 2015-16:

Here is driver licence ownership by age group for Australia:

(note: the 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 not a perfect measure)

From June 2014 to June 2015, license ownership rates increased in all age groups except 30-39, 60-69 and 80+.

2015 saw a change in the trend on licence ownership rates for teenagers, with a slight increase after four years of decline. However the trends are quite different in each state:

(note: in most states 16 is the age where people are able to obtain a learner’s permit)

I’m really not sure why Western Australia has such a low licence ownership rate compared to the other states (maybe the data doesn’t actually include learner permits).

And finally, here are licence ownership rates for people aged 20-24, showing quite different trends in different states:

I’ll aim to elaborate more on these trends in updates to subject-specific posts when I get time.

[Updated 1 December 2017 with reissued Place of Work data]

The ABS has now released all census data for the 2016 journey to work. This post takes a city-level view of mode share trends. It has been expanded and updated from a first edition that only looked at place of work data.

My preferred measure of mode share is by place of enumeration – ie how did you travel to work based on where you were on census night (see appendix for discussion on other measures).

I’m using Greater Capital City Statistical Areas (GCCSA) geography for 2011 and 2016 and Statistical Divisions for earlier years. For Perth, Melbourne, Adelaide, Brisbane and Hobart the GCCSAs are larger than the Statistical Divisions used for earlier years, but then those cities have also grown over time. See appendix 1 for more discussion.

Some of my data goes back to 1976 – I’ll show as much history as I have for each mode/modal combination.

Public transport mode share

Sydney continues to have the largest public transport mode share, and the largest shift of the big cities. Melbourne also saw significant positive mode shift, but Perth and particularly Brisbane had mode shift away from public transport.

There’s so much to unpack behind these trends, particularly around the changing distribution of jobs in cities that I’m going to save that lengthy discussion for another blog post.

But what about the…

Massive mode shift to “public transport” in Darwin?!?

[this section updated 26 Oct 2017]

Yes, I have triple-checked I downloaded the right data. “Public transport” mode share increased from 4.3% to 10.9%. The number of people reporting bus-only journeys went from 1648 in 2011 to 5661 in 2016, which is growth of 244%. There has also been a spike in the total number of journeys to work in 2011, 30% higher than in 2011, while population growth was 13%.

Initially I thought this might have been a data error, but I’ve since learnt that there is a large LNG gas project just outside Darwin, and up to 180 privately operated buses are being used to transport up to 4700 workers to the site. This massive commuter task is swamping the usage of public buses.

Here’s the percentage growth in selected journey types between 2011 and 2016:

Bus + car as driver grew from 74 to 866 journeys, which reflects the establishment of park and ride sites around Darwin for the special commuter buses. Bus only journeys increased from 1953 to 5744. So it looks like most workers are getting the bus from home and/or forgot to mention the car part of their journey (in previous censuses I’ve seen many people living kilometres from a train station saying they got to work by train and walking only).

So this new project has swamped organic trends, although it is quite plausible that some people have shifted from cycling/walking to local jobs to using buses to commute to the LNG project (which is outside urban Darwin). When I look at workplaces within the Darwin Significant Urban Area (2011 boundary), public transport mode share is 6.0%, in 2016, still an increase from 4.4% in 2011. More on that in a future post.

Train

Sydney saw the fastest train mode share growth, followed by Melbourne, while Brisbane and Perth went backwards.

Bus

Darwin just overtook Sydney for top spot thanks to the LNG project. Otherwise only Sydney, Canberra and Melbourne saw growth in bus mode share. Melbourne’s figure remains very low, however it is important to keep in mind that trams provide most of the on-street inner suburban radial public transport function in Melbourne.

Train and bus

Sydney comes out on top, with a large increase in 2016 (although much of this is still concentrated around Bondi where there are high bus frequencies and no fare penalties for transfers – more on that in an upcoming post). Melbourne is seeing substantial growth (perhaps due to improvements in modal coordination), while Perth, Adelaide and Brisbane had declines in terms of mode share (Brisbane and Adelaide were also declines on raw counts, not just mode share). I’m sure some people will want to comment about degrees of modal integration in different cities.

Train and bicycle

Some cities are also trying to promote the bicycle and train combination as an efficient way to get around (they are the fastest motorised and (mostly)non-motorised surface modes because they can generally sail past congested traffic). The mode shares are still tiny however:

Sydney and Melbourne are growing but the other cities are in decline in terms of mode share.

As this modal combination is coming off an almost zero base, it’s also probably worth looking at the raw counts:

The downturns in Brisbane and Perth are not huge in raw numbers, and probably reflect the general mode shift away from public transport (which is probably more to do with changing job distributions than bicycle facilities at train stations).

Cycling

I have a longer time-series of bicycle-only mode share, compared to “involving bicycle”, so two charts here:

Observations:

• Darwin lost top placing for cycling to work with a large decline in mode share (refer discussion above about the massive shift to bus).
• Canberra took the lead with more strong growth.
• Melbourne increased slightly between 2011 and 2016 (note: rain was forecast on census day which may have suppressed growth, more on that in a moment).
• Hobart had a big increase in 2016, following rain in 2011.
• Sydney remains at the bottom of the pack and declined in 2016.

Walking and cycling mode share is likely to be impacted by weather. Here’s a summary of recent census weather conditions for most cities (note: Canberra minimums were -3 in 2001, -7 in 2006, 0 in 2011 and -1 in 2016):

Perth had rain on all of the last four census days, while Adelaide had significant rain only in 2001 and 2011 (and indeed 2006 shows up with higher active transport mode share). Hobart had significant rain in 2011, which appears to have suppressed active transport mode share that year.

But perhaps equally important is the forecast weather as that could set people’s plans the night before. Here was the forecast for the 2016 census day,  from the BOM website the night before:

Note that it didn’t end up raining in Melbourne, Adelaide, or Hobart.

The census is conducted in winter – which is the best time to cycle in Darwin (dry season) and not a great time to cycle in other cities. However the icy weather in Canberra clearly hasn’t stopped it getting the highest and fastest growing cycling mode share of all cities!

Indeed here is a chart from VicRoads showing the seasonality of cycling in Melbourne at their bicycle counters:

And in case you are interested, here are the (small) mode shares of journeys involving bicycle and some other modes (other than walking):

Walking only

Canberra was the only city to have a big increase, while there were declines in Darwin, Perth, Adelaide, Brisbane, and Sydney.

The smaller cities had the highest walking share, perhaps as people are – on average – closer to their workplace, followed by Sydney – the densest city. But city size doesn’t seem to explain cycling mode shares.

Car

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

Sydney has the lowest car only mode share and it declined again in 2016. It was followed by Melbourne in 2016. Brisbane and Perth had large increases in car mode share in 2016 (in line with the PT decline mentioned above). Darwin also shows a big shift away from the car to public transport (although the total number of car trips still increased by 24%). Adelaide hit top spot, followed by Hobart and Perth.

Here is car as driver only:

And here is car as passenger only:

Car as passenger declined in all cities again in 2016, but was more common in the smaller cities, and least common in the bigger cities. I’m not sure why car as passenger declines paused for Perth and Sydney in 2006.

We can calculate an implied notional journey to work car occupancy by comparing car driver only and car passenger only journeys. This is not actual car occupancy, because it excludes people not travelling to work and excludes journeys that involved cars and other modes. However it does provide an indication of trends in car pooling for journeys to work.

There were further significant decreases in car commuter occupancy, in line with increasing car ownership and affordability.

Private transport

Here is a chart summing all modal combinations involving cars (driver or passenger), motorcycle/scooter, taxis, and trucks, but excluding any journeys that also include public transport.

The trends mirror what we have seen above, and are very similar to car-only travel.

Overall mode split

Here’s an overall split of journeys to work by “main mode” (click to enlarge):

Note: the 2001 data includes estimated splits of aggregated modes based on 2006 data.

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 “tram/ferry”
• 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”
• Any other journey involving walking or cycling only as “active”

How different are “place of work” and “place of enumeration” mode shares?

[this section updated 1 December 2017 with re-issued Place of Work data. See new Appendix 3 below for analysis of the changes]

The first edition of this post reported only “place of work” data, as place of enumeration data wasn’t released until 11 November 2017. This second edition now focuses on place of enumeration – where people were on census night.

The differences are not huge, as most people who live in a city also work in that city, but there are still a number of people who leave or enter cities’ statistical boundaries to go to work. Here’s an animation showing the main mode split by place of work and enumeration so you can compare the differences (you’ll need to click to enlarge). The animation dwells longer on place of work data.

Public + active transport main mode shares are generally higher for larger cities with place of work data, and smaller for smaller cities.

Here’s a closer look at the 2016 public transport mode shares by the two measures:

See also a detailed comparison in Appendix 1 below for 2011 Melbourne data.

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

Appendix 1 – How to measure journey to work mode share

Firstly, I exclude people who did not work, worked at home, or did not state how they worked. The first two categories generate no transport activity, and if the actual results for “not stated” were biased in any way we would have no way of knowing how.

I prefer to use “place of enumeration” data (ie where people were on census night). “Place of usual residence” data is also available, but is unfortunately contaminated by people who were away from home on census day. The other data source is “Place of work”.

Some people might prefer to measure mode shares on Urban Centres which excludes rural areas within the larger blobs that are Greater Capital City Statistical Areas and Statistical Divisions (use this ABS map page to compare boundaries). However, “place of work” data is not readily available for that geography, and this method also excludes satellite urban centres that might be detached from the main urban centre, but are very much part of the economic unit of the city.

Another option is “Significant Urban Area”, which includes more fringe areas, and some more satellite towns, and in Canberra’s case crosses the NSW border to capture Queanbeyan.

What difference does it make?

Here’s a comparison of public transport mode shares for the different methods for 2011.

If you look closely, you’ll notice:

• The more than you remove non-urban areas, the higher your public transport mode share, which makes sense, as those non-urban areas are mostly not served by public transport.
• Place of usual residence tends to increase public transport mode shares for smaller cities (people probably visiting larger cities) and depresses public transport mode share in larger cities (people visiting smaller cities and towns).
• Place of work is only readily available for Greater Capital City Statistical Areas. For the bigger cities it tends to inflate PT mode share where people might be using good inter-urban public transport options, or driving to good public transport options on the edges of cities (eg trains). However it has the opposite impact in Darwin and Canberra, where driving into the city is probably easier.

But I think the main point is that for any time series trend analysis you should use the same measure if possible.

If you want to compare the two, I’ve created a Tableau Public visualisation that has a large number of mode shares by both place of work and place of enumeration.

Appendix 2 – Estimating pre-2006 mode shares from aggregated data

For 2006 onwards, ABS TableBuilder provides counts for every possible combination of up to three modes (other than walking, which is assumed to be part of every journey). For example, in Melbourne in 2006, 36 people went to work by taxi, car as driver, and car as passenger (or so they said!). Unfortunately for years before 2006 data is not readily available with a full breakdown.

The 2001 data includes only aggregated counts for the following categories:

• train and other (excluding bus)
• bus and other (excluding train)
• other two modes (no train or bus)
• train and two other modes
• bus and two other modes (excluding train)
• three other modes (no train or bus)

Together these accounted for 3.7% of journeys in Melbourne and 4.5% of journeys in Sydney.

However all but two of those aggregate categories definitely involve train and/or bus, so can be included in public transport mode share calculations.

Journeys in the aggregate categories “Other two modes” and “Other three modes” might involve tram and/or ferry trips (if such modes exist in a city), but we don’t know for sure.

I’ve used the complete modal data for 2006 to calculate the percentage of 2006 journeys that fit into these two categories that are by public transport. I’ve then assumed these same percentage apply in 2001 to estimate total public transport mode shares for 2001 (for want of a better method).

Here are the 2001 relevant stats for each city:

(note: totals do not add perfectly due to rounding)

The estimates add up to 0.2% to the total public transport mode shares in cities with significant modes beyond train and bus (namely ferry and tram in Sydney, tram in Melbourne, ferry in Brisbane, tram and Adelaide). This almost entirely comes from “other two modes” category while “other three modes” is tiny. For these categories, almost no journeys in Perth, Canberra and Hobart actually involved a public transport mode.

In the past I have knowingly ignored public transport journeys that might be part of these categories, which almost certainly means public transport mode share is underestimated (I suspect most other analysts have too). By including some assumed public transport journeys my estimate should be closer to the true value, which I think is better than an underestimate.

But are these reasonable estimates? Are the 2001 modal breakdowns for these categories likely to be the same as 2006? Maybe not exactly, but because we are multiplying small numbers by small numbers, the impact of slightly inaccurate estimates is unlikely to shift the total by more than 0.1%. I tested the methodology between 2006 and 2011 results (eg using 2011 full breakdown against created 2006 aggregate categories and vice versa) and the estimated total mode shares were almost always exactly the same as the perfectly calculated shares (at worst there was a difference of 0.1% when rounding to one decimal place).

In the first edition of this post I had to estimate 2016 place of work mode shares in a similar way for public and private transport, but I wasn’t confident enough to estimate mode share of journeys involving cycling.

I now have the final data and I promised to see how I went, so here’s a comparison:

If you round to one decimal place, the estimates were no different for public and private transport and out by up to 0.1% for cycling (which is relatively significant for the small cycling mode shares).

I’ve applied a similar approach to estimate several other mode share types, and these are marked on charts.

Appendix 3 – How different is the re-issued place of work data?

In December 2017, ABS re-issued Place of Work data due to data quality issues. This is how they described it:

**The place of work data for the 2016 Census has been temporarily removed from the ABS website so an issue can be corrected. There was a discrepancy in the process used to transform detailed workplace location information into data suitable for output. The ABS will release the updated information in TableBuilder on December 2. The Working Population Profiles will be updated on December 13.**

I have loaded the new data, and here are differences in public transport and private transport mode shares for capital cities:

You can see differences of up to 0.3% (Melbourne PT mode share), but mostly quite small.

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

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

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

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

Public transport share by home location

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

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

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

(explore in Tableau)

The biggest shifts to public transport in the middle and outer suburbs were in Wyndham Vale, Tarneit, South Morang, Lynbrook/Lyndhurst, Point Cook South, Williams Landing, Rockbank, and Glenroy. That’s almost a roll call of all the new train stations opened between 2011 and 2016. The exceptions are Rockbank (a small community at present which received significantly more frequent trains in 2015), Point Cook South (which now has buses operating every 11 minutes in the AM peak to nearby Williams Landing Station), and Glenroy (where more people are commuting to the city centre and increasingly by public transport).

Inner suburban areas with high mode shifts include West Footscray, Yarraville, Seddon – Kingsville, Collingwood, Kensington, and Brighton. The Melbourne CBD itself had a 12% shift to public transport – and actually a 7% mode shift away from walking (which probably reflects the new Free Tram Zone in the CBD area).

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

Public transport mode share by work location

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

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

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

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

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

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

Explore the data yourself in Tableau.

Here’s an enlargement of the inner city area:

And here’s a map showing the mode shift between 2011 and 2016 by workplace location:

The biggest shifts to public transport were in the inner city. The biggest shift away from public transport was Altona Meadows (but volumes were tiny – 73 journeys went down to 51).

Here’s a closer look at the inner city:

Docklands had the highest mode shift to public transport of 8.8% (almost all of it involving train) followed by Collingwood with 7.0% and Parkville with 6.1%.

North Melbourne saw a decline of 1.5% – at the same time private transport mode share and active (only) mode shares increased by 1%. Brunswick West saw a 2.3% decline in public transport mode share, a 1.2% increase in active transport and a 3.4% increase in private transport share.

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

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

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

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

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

What about job density?

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

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

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

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

Explore this map in Tableau.

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

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

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

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

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

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

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

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

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

(see a map of CLUE areas)

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

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

It’s little surprise to see a strong relationship between the two, although Carlton is seeing increasing parking provision but decreasing private transport mode share (maybe those car parks aren’t priced for commuters?). North Melbourne increased on both measures between 2011 and 2016.

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

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

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

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

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

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

The biggest growth in jobs was in the CBD, followed by Docklands, and then Dandenong in the south-east.

And here’s an enlargement of the inner city:

(explore this data in Tableau)

The CBD added 33,210 jobs, and almost all of those were accounted for by public transport journeys, although 2,750 were by active transport, and only 867 new jobs by private transport (3%).

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

However, Southbank still has a relatively high private transport mode share of 44.5% for an area so close to the CBD. The earlier car parking chart showed that Southbank has about one off-street non-residential car park for every two employees. These include over 5000 car parks at the Crown complex alone (with $16 all day commuter parking available as at November 2017). It stands to reason that the high car parking provision could significantly contribute to the relatively high private transport mode share, which is in turn generating large volumes of radial car traffic to the city centre on congested roads. Planning authorities might want to consider this when reviewing applications for new non-residential car parks in Southbank.

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

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

Public transport dominated new journeys to work up to 2km from the city centre and only just outnumbered private transport between 2 and 4 km. Private transport dominated new journeys to workplaces more than 4km from the city centre – however that doesn’t necessarily mean a mode shift away from public transport if the new trips have a higher public transport mode share than the 2011 trips. Indeed there was a mode shift towards public transport for workplaces in most parts of Melbourne.

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

Private transport had the lowest mode share of new jobs in the inner city. As seen on the map, some relative anomalies for their distance from the CBD include Hampton (70%), Brunswick East (40%), and Albert Park (24%). Explore the data in Tableau.

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

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

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

There are many middle suburban SA2s with declines. These are also suburbs where there has been population decline – which I suspect are seeing empty nesting (adult children moving out) and people retiring from work. For example Templestowe generated 561 fewer private transport trips, 48 fewer active transport only trips, but only 50 new public transport trips.

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

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

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

(explore in Tableau)

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

You can see many areas where private transport accounted for a minority of new trips.

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

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

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

(explore in Tableau)

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

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

• Wyndham in the south-west where two new train stations opened. 38% of new trips from Wyndham Vale and 30% of new trips from Tarneit were by public transport.
• Sunbury in the north-west, to which the Metro train network was extended in 2012.  Around 28% of new trips from Sunbury were by public transport (that’s 329 trips).

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

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

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

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

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

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

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

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

You can see:

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

Where are commuters headed on different modes?

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

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

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

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

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

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

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

Notes on the data:

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

Where do commuters using different modes live?

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

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

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

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

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

Here’s the same for private transport only journeys:

There is a much more even distribution.

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

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

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

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

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

My last post looked at the overall trends in journeys to work in Melbourne, with a focus on public and private transport at the aggregate level. This post dives down to look at particular modes or modal combinations, including mode shares, mode shifts and the origins and destinations of new trips.

Train

Here’s mode share for journeys involving train by home location (journeys may also include other modes):

The highest train mode shares can be seen mostly along the train lines, which will surprise no one.

In fact, we can measure what proportion of train commuters live close to train stations. The following chart looks at how far commuters live from train stations, for commuters who use only trains, used trains and possible other modes, and for all commuters.

This chart shows that almost 60% of people who only used train (and walking) to get to work lived within 1 km of a station, and almost three-quarters were within 1.5 km. But around 8% of people only reporting train in their journey to work were more than 3 km from a train station. That’s either a long walk, or people forgot to mention the other modes they used (a common problem it seems).

For journeys involving train, 50% were from within 1 km of a station, but around a quarter were from more than 2 km from a station.

Interestingly, around a third of all Melbourne commuters lived within 1 km of a train station, but a majority of them did not actually report train as part of their journey to work.

So where were the mode shifts to and from train (by home location)?

There were big mode shifts to train around new stations including Wyndham Vale, Tarneit, Lynbrook, South Morang, and Williams Landing. Other bigger shifts were in West Footscray – Tottenham, South Yarra – East, Brighton, Viewbank – Yallambie, Yarrville, Footscray, Kensington, and Flemington (some of which might be gentrification leading to more central city workers?).

There was also a big shift to trains in Point Cook – South, which doesn’t have a train station, but is down the road from the new Williams Landing Station. Almost 28% of commuters from Point Cook South work in the Melbourne CBD, Docklands or Southbank, and most of those journeys were by public transport.

We can also look at mode shares by work location. Here is train mode share by workplace location for 2011 and 2016 (I’ve zoomed into inner Melbourne as the mode shares are negligible elsewhere, and I do not have equivalent data for 2006 sorry):

The highest shares are in the CBD, Docklands and East Melbourne. Notable relatively high suburban shares include the pocket of Footscray containing State Trustees office tower (30.7% in 2016),  a pocket of Caulfield including a Monash University campus (29.5%), Box Hill (up to 19.6%), Swinburne University in Hawthorn (37.4%), and 17.5% in a pocket of Yarraville.

The biggest workplace mode shifts to train were in Docklands (+8.6%), Southbank (+5.5%), Abbotsford (+5.5%), Richmond (+5.3%),  Collingwood (+5.1%), Parkville (+4.9%), and South Yarra – East (+4.8%).

Bus

Across Melbourne, bus mode share had a significant rise from 2.6% in 2006 to 3.3% in 2011, and then a small rise to 3.4% in 2016. Here’s how it looks spatially for any journey involving bus:

The highest bus mode shares are in the Kew-Doncaster corridor, around Clayton (Monash University), in the Footscray – Sunshine corridor, a pocket of Heidelberg West, around Box Hill and in Altona North. These are areas of Melbourne with higher bus service levels (and most lack train and tram services).

Here’s a map showing mode shift 2011 to 2016 at the SA2 level:

Outside the Kew – Doncaster corridor there were small mode shifts in pockets that received bus network upgrades between 2011 and 2016, including Point Cook, Craigieburn, Epping – West, Mernda, Port Melbourne, and Cairnlea.

There was also a shift to buses in Ormond – Glenhuntly, which can be largely explained by Bentleigh and Ormond Stations being closed on census day due to level crossing removal works, with substitute buses operating.

There were larger declines in Laverton / Williams Landing (where a new train station opened), Footscray, and Abbotsford.

In terms of workplaces, Westfield Doncaster topped Melbourne with 14.4% of journeys involving bus, followed by Monash University Clayton with 12.8% (remember this figure does not include students who didn’t also work at the university on census day), 13.3% at Northland Shopping Centre, and 12.3% in a pocket of Box Hill.

SmartBus

“SmartBus” services operate from 5 am to midnight weekdays, 6 am to midnight Saturdays, and 7 am to 9 pm Sundays, with services every 15 minutes or better on weekdays from 6:30 am to 9 pm, and half-hourly or better services at other times. These are relatively high service levels by Melbourne standards.

SmartBus includes four routes that connect the city to the Manningham/Doncaster region via the Eastern Freeway, three orbital routes, and a couple of other routes in the middle south-eastern suburbs. All routes are relatively direct and none are particularly short. Seven of these routes serve the Manningham region.

To assist analysis, I’ve created a “SmartBus zone” which includes all SA1 and CD areas which have a centroid within 600 m of a SmartBus route numbered 900-908. These routes were all introduced between 2006 and 2011, generally replacing existing routes that operated at lower service levels (I’ve excluded SmartBus route 703 because it was not significant upgraded between 2006 and 2016).

Here are mode shares inside and outside the SmartBus zone:

In 2006 the SmartBus zone already had double the bus mode share of the rest of Melbourne, as existing routes had relatively good service levels, including Eastern Freeway services. Following SmartBus (and other bus) upgrades between 2006 and 2011, there was a 2.5% mode shift to bus in the SmartBus zone, and a 1.3% mode shift to bus elsewhere. The SmartBus zone had a further 0.5% shift between 2011 and 2016 while the shift was only 0.2% in the rest of Melbourne.

Here’s an animated look at bus mode shares for just the SmartBus zone.

You can see plenty of mode shift in the Manningham area (where many SmartBus routes overlap), but also some mode shifts along the others routes – particularly in the south-east.

Notes:

• the SmartBus zone includes overlaps with some other high service bus routes – those pockets generally had higher starting mode shares in 2006.
• The orbital SmartBus routes do overlap with trains and/or trams which provide radial public transport at high service levels, negating the need or bus as a rail feeder mode (still useful for cross-town travel).
• I haven’t excluded sections of SmartBus freeway running from the SmartBus zone. Sorry, I know that’s not perfect analysis, particularly along the Eastern Freeway.

Train + bus

Journeys involving train and bus rose from 1.1% in 2006 to 1.5% in 2011 and 1.7% in 2016, which is fairly large growth off a small base and represents around half of all journeys involving bus. I suspect there might be some under-reporting of bus in actual bus-train journeys, as we saw many people a long way from train stations only reporting train as their travel mode.

Here’s a map showing train + bus mode share at SA2 level. Note the colour scale is in half-percent increments:

Large increases are evident around the middle eastern suburbs (particularly around SmartBus routes), the Footscray-Sunshine corridor (which have frequent bus services running to frequent trains at Footscray Station), Point Cook (where relatively frequent bus routes feeding Williams Landing Station were introduced in 2013, resulting in 750 train+bus journeys in 2016), Craigieburn (again bus service upgrades with strong train connectivity), and Wollert (likewise).

Ormond – Glen Huntly shows up in 2016 because of the rail replacement bus services at Bentleigh and Ormond Stations at the time (as previously mentioned).

Tram

Here’s a map of tram mode shares, overlaid on the 2016 tram network (there haven’t been any significant tram extensions since 2005).

Higher tram mode shares closely follow the tracks, with the highest shares in Brunswick, North Fitzroy, St Kilda, Richmond, and Docklands.

It’s also interesting to note that several outer extremities of the tram network have quite low tram mode shares – including East Brighton, Vermont South, Box Hill, Camberwell / Glen Iris (where the Alamein line crosses tram 75), Carnegie, and to a lesser extent Airport West and Bundoora. These areas have overlapping train services and/or are a long travel time from the CBD.

Overall tram mode share increased from 4.0% in 2006 to 4.6% in 2011 and 4.8% in 2016. Here’s a map of tram mode shift 2011 to 2016 by home SA2:

The biggest mode shift was +12.6% in Docklands, followed by +9.5% in the CBD. This no doubt reflects the introduction of the free tram zone across these areas. Walk-only journey to work mode share fell 4.4% in Docklands and 7% in the CBD.

Abbotsford had a 8.5% mode shift to trams, which possibly reflects the extension of route 12 to Victoria Gardens, providing significantly more capacity along Victoria Street (the only tram corridor serving Abbotsford).

There were small mode share declines in many suburbs, although this does not necessarily mean a reduction in the number of journeys by tram.

Here are tram mode shares by workplace for 2011 and 2016:

The highest workplace tram mode shares were in the CBD, along St Kilda Road south of the CBD, Carlton, Fitzroy, Parkville, Albert Park, South Melbourne, and St Kilda.

Cycling

Cycling mode share increased from 1.5% in 2006 to 1.8% in 2011 and 1.9% in 2016. These are low numbers, but the bicycle mode share was anything but uniform across Melbourne.

Firstly here’s a map of cycling mode share by home location:

There’s not much action outside the inner city, so let’s zoom in:

The highest mode shares are in the inner northern suburbs (pockets around 25%) where there has been considerable investment in cycling infrastructure.

Here’s a chart showing the mode shift at SA2 level:

The biggest mode shift was 2.2% in Brunswick West, followed by 2.1% in South Yarra West. However aggregating to SA2 level hides some of the other changes. If you study the detailed map you can see larger mode shifts in more isolated pockets and/or corridors (including a corridor out through Footscray).

Here is the growth in bicycle trips between 2011 and 2016 by home distance from the city centre:

Significant growth was only seen for homes within 10km of the city centre. Here are those new trips mapped:

What about cycling mode shares by workplaces? I’ve gone straight to the inner city so you can see the interesting detail:

The highest workplace mode shares are in the inner northern suburbs, including Parkville (9.1%) and Fitzroy North (8.2%).

You’ll note the CBD does not have a high cycling mode share (3.8%) compared to the inner northern suburbs. But if you look at the concentration of cycling commuter workplaces, you get quite a different story:

This shows the CBD having the highest concentrations of commuter cycling destinations, although there were also relatively high densities at the Parkville hospitals and the Alfred Hospital. The highest concentration of commuter cyclists in 2016 was a block bound by Lonsdale Street, Exhibition Street, Little Lonsdale Street and Spring Street (it had a mode share of 4.3%).

However if you look at the increase in bicycle commuter trips between 2011 and 2016 by workplace distance from the city, the biggest growth was for destinations 1-4 km from the city centre:

Note: I am using a different scale for charts by workplace distance from the CBD.

How has walking changed?

Overall walking-only mode share in Melbourne as measured by the census has hardly changed, from 3.6% in 2006 to 3.5% in both 2011 and 2016. However there are huge spatial variations.

Here’s walking by home location:

The highest walking mode shares are around the central city with mode shares above 40% in parts of the CBD, Southbank, Carlton, Docklands, North Melbourne, and Parkville. Outside the city centre relatively high mode shares are seen around Monash University Clayton, the Police Academy in Glen Waverley, Box Hill, and Swinburne University in Hawthorn. Walking-only trips are very rare in most other parts of the city.

Here are walking mode shares by workplace location:

The highest walking shares by SA2 in 2016 were in St Kilda East, Prahran – Windsor, South Yarra, Carlton, Carlton North, Fitzroy, and Elwood. There were also smaller pockets of high walking mode share in Yarraville, Footscray, Flemington, Northcote, Ormond – Glenhuntly, Richmond, and Box Hill.

The biggest mode shifts away from walking were in the CBD (-7.3%) and Docklands (-4.0%), which also had big shifts to tram – probably due to the new Free Tram Zone.

Overall, the biggest increase in walking journeys was seen within 5km of the city centre:

For workplaces, the biggest growth in walking was to jobs between 2-4 km from the CBD (be aware of different X-axis scales):

Most common non-car mode

Here is a map showing the most common non-car mode in 2016*. Note the most common non-car mode might still have a very small mode share so interpret this map with caution.

*actually, I’ve not checked motorbike/scooter, taxi, or truck on the basis they are very unlikely to be the most common.

Train dominates most parts of Melbourne, with notable exceptions of the Manningham region (served by buses but not trains), several tram corridors that are remote from trains, and walking around the city centre.

The southern Mornington Peninsula is a mix of bus and walking, plus some SA1s where no one travelled to work by train, tram, bus, ferry, bicycle, or walking-only!

The next map zooms into the inner suburbs, showing the tram network underneath:

Generally tram is only the dominant mode in corridors where trains do no overlap (we saw lower tram mode shares in these areas above). In most of the inner south-eastern suburbs served by trams and trains, train is the dominant non-car mode.

If you look carefully, there are a few SA1s where bicycle is the dominant non-car mode.

In case you are wondering, there are places in Melbourne where train, tram, or walking-only trumped car-only as the most common mode. They are all on this map:

Mode with the most growth

Finally, another way to look at the data is the mode with the highest growth in trips.

Here is a map showing the mode (out of car, train, tram, bus, ferry, bicycle, walk-only) that had the biggest increase in number of trips between 2011 and 2016, by SA2:

Car trips dominated new trips in most outer suburbs (particularly in the south-east), but certainly not all of Melbourne. Train was most common in many middle suburbs (and even some outer suburbs).

Bicycle was the most common new journey mode in Albert Park (+69 journeys), South Yarra – West (+58), Carlton North – Princes Hill (+65), Fitzroy North (+150) and Brunswick West (+165).

Walking led Southbank (+1292 journeys), Fitzroy (+136), and Keilor Downs (+13 with most other modes in small decline, so don’t get too excited).

Bus topped SA2s in the Doncaster corridor, but also Port Melbourne (+187), Wantirna (+16), Kings Park (+11) and Ormond – Glen Huntly (+284 with rail replacement buses operating on census day in 2016).

Tram topped several inner SA2s but also Vermont South (+37).

Want to explore the data in Tableau?

I’ve built visualisations in Tableau Public where you can choose your mode of interest, year(s) of interest, and zoom into whatever geography you like.

By home location:

• Mode share
• Mode shift
• Trip growth 
• Most common non-car mode
• Mode with largest journey growth

By work location:

• Mode share
• Mode shift
• Trip growth
• Destination density by mode

Have fun exploring the data!

The Australian census provides incredibly rich data about journeys to work, with every journey classified by origin, destination, and mode(s) of transport. So you can ask questions such as “where did workers living in X commute to and how many used public transport?” or “where did workers in Y commute from and what percentage used private transport?”, or “What percentage of people in each home location work in the central city?”.

It’s very possible to answer these questions with census data, but near-impossible to produce an atlas of maps that would answer most questions.

But thanks to new data visualisation platforms, it’s now possible to build interactive tools that allow exploration of the data. I’ve built one in Tableau Public, using both 2011 and 2016 census data for all of Australia at the SA2 geography level (SA2s are roughly suburb sized). This means you can look at each census year, as well and the changes between 2011 and 2016.

I’m going to talk through what I’ve built with plenty of interesting examples from my home city Melbourne.

I hope you find exploring the data as fascinating and useful as I do. I also hope this tool makes it easier to inform transport discussions with evidence.

Also, a warning that this is a longer post, so get comfortable.

About the data (boring but important)

The census asks people which modes they used in the journey to work, and the data is encoded for up to three modes.

I’ve extracted a count of the number of trips between all SA2s within each state, by “main mode” for both 2011 and 2016. I’ve aggregated all responses into one of the following “main mode” categories:

• Private (motorised) transport only – any journey involving car, truck, motorbike or taxi, but no modes of public transport, or people who only responded with “other”. Around 89% of journeys in this category were simply “car as driver”.
• Walking/cycling only (or “active transport”) – journeys by walking or cycling only.
• Public transport – any journey involving any public transport mode (train, tram, bus, and/or ferry). These journeys might also involve private motorised transport and/or cycling.

There are 466,597 rows of data all up – so you will need to be a little patient while Tableau prepares charts for you.

Things to note:

• I’ve had to extract each state separately to stop the number of possible origin-destination combinations getting too large. This means that interstate journeys to work are not included in the data. I have however combined New South Wales (NSW) and the small Australian Capital Territory (ACT), as many people commute between Queanbeyan (NSW) and Canberra (ACT). Apologies to other areas near state borders!
• When you ask the ABS for the number of people meeting certain criteria, the answer will never be 1 or 2. The ABS randomly adjust small numbers to protect privacy, and it’s not a good idea to add up lots of small randomly adjusted figures. That’s another reason why I haven’t gone smaller than SA2 geography and why I’ve aggregated mode combinations to just three modal categories. You will still see counts of 3 or 4, which need to be treated with caution.
• Not all SA2s are the same size in terms of residential population, and particularly in terms of working population. The biggest source of commuters for a work area might simply be an SA2 with a larger total residential population.
• The ABS change the SA2 boundaries between censuses. With each census some SA2s are split into smaller SA2s, particularly in fast growing areas. If you want to compare 2011 and 2016 figures, it is necessary to aggregate the 2016 data to 2011 boundaries, which the tool does where required. Some visualisation pages will give you the option of aggregating 2016 data to 2011 boundaries to make it easier to compare 2011 and 2016 data.
• I’ve only counted journeys where the origin, destination and mode are known. Anyone who didn’t go to work on census day, didn’t state their mode(s) of travel, or didn’t state a fixed land-based work location are excluded.
• Assigning “other” only trips as private transport might not be perfect, as it might include non-motorised modes like skateboards and foot scooters. It will also count air travel, and it’s arguable whether that is private or public transport (it’s certainly not low-carbon transport). However, overall numbers are quite small – 0.81% of all journeys with a stated mode in Australia.

Mode share maps to/from a location

First up, you can produce maps showing the main mode share of commuters from all home SA2 for a particular work SA2, or all workplaces for a particular home SA2.

Here is a map of private transport mode shares for journeys to work from Point Cook North:

Private transport dominates most middle and outer work destinations (even local trips), with many at 100%. Lower shares are evident for central city destinations, although Southbank next to the CBD is relatively high at 65%, and 100% of commuters who travelled to Fishermans Bend did so by private transport.

You can also look at it the other way around. Here’s private transport mode share for commutes to Parkville (just north of the CBD):

There was a low private transport mode share from the city centre and Brunswick to the north, roughly 40-50% mode shares from the south-eastern suburbs (accessible by train), but very high mode shares from the middle and outer suburbs to the north and west (public transport access more difficult). The new Metro Tunnel could make a dent in these mode shares, with a new train station in Parkville.

Here is a map of private transport only mode share for journeys to the “Melbourne” SA2 (which represents the Melbourne CBD):

Private transport (only) mode shares were lower than 30% for most areas, as public and active transport options are generally cheaper and more convenient for travel to the CBD. However you can see corridors with higher private transport mode share, including Kew – Bulleen – Doncaster – Warrandyte, and Keilor East – Keilor – Greenvale (around Melbourne Airport). These corridors are more remote from heavy rail lines. Other patches of higher private mode share include Rowville – Lysterfield, Altona North, and Point Cook East (including Sanctuary Lakes).

A high private transport mode share does not necessary mean a flood of private vehicles are coming from these areas. Kinglake is the rich orange area in the north-east of the above map, and according the 2016 census, 57% of people commuted to the Melbourne CBD by private transport only. Except that 57% is actually just 23 out of just 40 people making that commute – which is pretty small number in whole scheme of things.

Which leads me to…

Journey volume and mode split maps

These maps show the volume (size of pie) and mode split for journeys from/to a selected SA2.

The following map shows the volume and mode split of journeys to the “Melbourne” SA2 in 2016:

As I discussed in a recent post, not many people actually commute from the outer suburbs to the central city. Indeed, only 767 people commuted from Rowville to the Melbourne CBD in 2016, which is less than one train full.

Unfortunately all the pie charts in the inner city tend to overlap, while the pie charts in the outer suburbs are tiny. Here’s a zoomed in map for the inner suburbs with a lot less overlap:

You can see large green wedges in the inner city, where walking or cycling to the CBD is practical. You can also see that almost everywhere the blue wedges (public transport) are much larger than the red (private transport).

What does stand out more in this map is Kew – where 716 people travelled to the Melbourne CBD by private transport (highest of any SA2) – with a relatively high 41% mode share for a location so close to the city, despite it being connected to the CBD by four frequent tram and bus lines. Kew is also a quite wealthy area, so perhaps parking costs do not trouble such commuters (maybe employers are paying?). Other home SA2s with high volumes and relatively high private mode shares are Essendon – Alberfeldie (521 journeys, 28% private mode share), Brighton (493, 33%), Keilor East (419, 41%), Toorak (404, 35%) and Balwyn North (396, 35%). Most of these are wealthy suburbs, with the notable exception of Keilor East, which does not have a nearby train station.

Here is the same for Parkville:

The home areas with significant numbers of Parkville commuters are in the inner northern suburbs, and active and public transport were the dominant mode share for these trips. While 92% of commuters from Burnside Heights to Parkville were by private transport, there were only 35 such trips. The overall private transport mode share for Parkville as a destination was 50%.

Here is the same type of map for Fishermans Bend (Port Melbourne Industrial), which is just south-west of the CBD:

Private transport dominates mode share, and you can see a slight bias towards the western suburbs. Which means a lot of cars driving over the Westgate Bridge.

Around 30,000 people travelled to work in Clayton in Melbourne’s south-east. Here’s a map showing the origins of those commutes:

Almost half of the workers who both live and work in Clayton walked or cycled (only) to work, of which I suspect many work at Monash University. The public transport mode shares are higher towards the north-west, particularly around the Dandenong train line that connects to Clayton. Very few people put themselves through the pain of commuting from Melbourne’s western and northern suburbs to Clayton.

Over 60,000 people commuted to Dandenong in 2016, which includes the large Dandenong South industrial area. Here are the volumes and mode splits for where they came from:

You can see a significant proportion of the workforce lived to the south-east, and much less to the north and west. You can also see private transport dominates travel from all directions (despite there being two train lines through the Dandenong activity centre, and a north-south SmartBus route through the industrial area).

Here‘s a look at people who commuted to work at Melbourne Airport:

You can see that airport workers predominantly came from the nearby suburbs, and the vast majority commuted by private transport. The most common home locations of airport workers include Sunbury South (543), Gladstone Park – Westmeadows (411), and Greenvale – Bulla (351 – note Greenvale has a much higher population than Bulla).

The largest public transport volume actually came from the CBD (48 out of 67 commuters, which is a 72% mode share), probably using staff discount tickets on SkyBus. The biggest trip growth 2011 to 2016 was from Craigieburn – Mickelham: 367 more trips of which 355 were by private transport only.

The data can also be filtered to only show a particular main mode. For example, here is a map of the origins for private transport trips to the Melbourne CBD (ie who drives to work in the CBD):

Which can also be shown as a sorted bar chart:

The most common sources of private transport trips to the CBD were generally very wealthy suburbs, where many people are probably untroubled by the cost of car parking (they can easily afford it, or someone else is paying). However bear in mind that not all SA2s have the same population so larger SA2s will be higher on the list (all other things being equal).

This data can also be viewed the other way around. Here are the volumes and mode splits of journeys from Point Cook South in 2016. The Melbourne CBD was the biggest destination (994 journeys) with 69% public transport mode share followed by Docklands (342 journeys) with 64% public transport mode share.

Here is yet another way to look at this data, which is particularly relevant for the central city…

Percentage of commuters who travel to selected workplace SA2s

Here is a map showing the proportion of commuters in each home SA2 who work in the Melbourne, Southbank or Docklands SA2s (the tool allows selection of up to three workplace SA2s):

There are some interesting patterns in this map. Generally the percentage of people commuting to central Melbourne declined with distance from the CBD. There are however some outlier SA2s that had relatively high percentages of people travelling to central Melbourne, despite being some distance from the city centre.

In fact, here is a chart showing distance from the CBD, and the percentage of commuters travelling to the central city:

Tableau has labelled some of the points, but not all (interact with the data in Tableau to explore more). The outliers above the curve are generally west or north of the city, with Point Cook South being the most significant outlier. Further from the city, the commuter towns of Macedon, Riddells Creek and Gisborne have unusually high percentage of commuters travelling to the central city for that distance from the city (made possible by upgraded V/Line train services).  Many of the outliers below the curve are less wealthy areas, where people were less likely to work in the central city.

The previous map showed the proportion of all commuters that went to the central city. The tool can also filter that by mode. Here’s a map showing the percentage of public transport commuters who had a destination of Melbourne, Docklands or Southbank:

Typically around two-thirds of public transport journeys to work from most parts of Greater Melbourne are to Melbourne, Docklands, or Southbank SA2s. The lowest percentages were in the local jobs rich SA2s of Clayton (49%) and Dandenong (40%).

Adding Carlton and East Melbourne to the above three central city SA2s roughly takes the proportion up to around 70%. That’s a lot of public transport commutes to other destinations, but still a vast majority are focussed on the central city.

We can also look at this data from the origin end…

Where do people from a particular area commute to?

As an example, here is a map showing the percentage of commuters from Point Cook – South (a new and relatively wealthy area in Melbourne’s south-west) who worked in each work SA2 (destinations with less than 20 workers excluded):

You can see that 20% worked in the Melbourne CBD, followed by 7% in Docklands, and 6% in each of Point Cook North and Point Cook South (local). The largest nearby employment area is the industrial areas of Laverton, but this industrial area only attracted 4% of commuters from Point Cook South.

Here is a map for “Rowville – Central” SA2:

You can see that journeys to work are very scattered, with only 6% travelling to the Melbourne CBD.

(these maps can also be filtered by mode)

Another way to look at that data is a…

List of top commuter destinations

Here’s a chart showing the top work destinations from Rowville – Central in 2016, split by mode (this is a screenshot so the scroll bar doesn’t work):

You can see local trips are most numerous, and are dominated by private transport (although there were 48 active transport local trips). Dandenong was the second most common destination, with 97% private transport mode share, followed by Melbourne CBD with 40% private transport mode share (137 private transport journeys). The only other destination with high public transport mode share was Docklands at 59% (48 private transport journeys).

Changes between 2011 and 2016

We’ve so far looked at volumes and mode shares, but of course we can also look at the changes in volumes and mode share between 2011 and 2016.

There were around 15,000 more commutes to Dandenong in 2016 compared to 2011. Here are the changes in volumes by main mode for home SA2s with the largest total number of journeys:

You can see almost all of the new journeys to work were by private transport, no doubt putting a lot of pressure on the road network. A lot of the growth was from the suburbs to the east and south-east, none of which had a direct public transport connection to the Dandenong South industrial area at the time of the 2016 census. That’s now changed, with new bus route 890 linking the Cranbourne train line at Lynbrook with the Dandenong South industrial area (it operates every 40 minutes).

Note: a row with no figure or bar drawn (quite common in the Active only column) means that there were no such trips in either 2011 and/or 2016. Unfortunately the tool doesn’t show the change in volume in such circumstances (I’ll try to fix this in the future).

Contrast this with Parkville:

Brunswick is Parkville’s biggest source of workers, and there were many more such workers coming in by public and active transport, and a decline in workers who commuted by private transport. However there was an increase in private transport from places further out like Coburg and Pascoe Vale.

Of course you can do this the other way around too. Here‘s the new trips from Tarneit, a major growth area in Melbourne’s south-west where a train station opened in 2015:

Access to the Melbourne CBD by public transport improved significantly with the new train station, and 527 more people did that trip in 2016 compared to 2011. But the number of people who drove declined by only 35. The train line didn’t reduce the number of people driving out of Tarneit in total, but there probably would have been a lot more had it not opened. In the case of the Melbourne CBD, there were simply a lot more CBD workers living in Tarneit in 2016 (some CBD workers may have moved to Tarneit, and people otherwise in Tarneit were probably more likely to choose the CBD for work).

Here is a map of private transport mode shifts for journeys to the Melbourne CBD (were blue is mode shift to private transport and orange is mode shift away from private transport):

The biggest shifts away from private transport include Narre Warren North (-19%, but small volumes), Tarneit (-17%, with a train station opening in 2015), Wyndham Vale (-15%, also new train station), Don Vale – Park Orchards (-15%, with buses being primary mode for access to the CBD), Melton (-13%), and then -12% in Point Cook (new train station and bus upgrades in 2013), West Footscray – Tottenham, Sunbury (rail electrification 2012), South Morang (new train station), and Warrandyte – Wonga Park (SmartBus to city).

The biggest mode shifts to private transport were in low volume areas, including Monbulk – Silvan (+14%, which is an extra 5 trips), Keilor (+8%, 8 extra trips), Tullamarine (+8%, 16 extra trips), Lysterfield (+7%, 4 extra trips), Panton Hill – St Andrews (+7%, 4 extra trips) and more surprisingly Coburg North (+6%, up from 47 to 97 trips).

Again, you can see the problem with mode share and mode shift figures is that the volumes may be inconsequential. The map doesn’t show regions with less than 30 travellers, or less than 4 travellers by the selected mode. There was an overwhelming mode shift away from private transport for travel to the Melbourne CBD.

Here’s another view of the data: the change in the number of private transport trips to the Melbourne CBD, mapped:

That’s a peculiar mix of increases in decreases, but most of the volume changes are relatively small (note the scale).

The biggest increase was +142 trips from Truganina, a growth area with two nearby train stations built between 2011 and 2016. If that sounds alarming, it should be compared with an increase of 555 public transport trips from Truganina to the Melbourne CBD.

The larger declines were from suburbs like:

• -85 from Doncaster East (bus upgrades),
• -67 from Donvale – Park Orchards (bus upgrades),
• -66 from Templestowe (also bus upgrades), and
• -61 from Deer Park – Derrimut (also bus and train service upgrades).

Curiously, there was an increase of 71 private transport journeys to work entirely within the Melbourne CBD (to a new total of 236). Why anyone living and working in the CBD would go by private transport is almost beyond me – it’s very walkable and the trams are now free. Digging deeper…in 2016: 137 drove a car, 20 were a car passenger, 17 used motorbike/scooter, 13 a taxi, and 31 were “other” (okay, some of those 31 might have been skateboards or kick scooters, but we don’t know).

We can do the same by home location. Here are the net new trip destinations from Wyndham Vale in Melbourne’s outer south-west:

Wyndham Vale added more trips to the Melbourne CBD than trips to local workplaces.

Find your own stories

As mentioned, I’ve built interactive visualisations for all of this data, in Tableau Public, which you can use for free.

If you have a reasonably large screen, you might want to start with one of these four “dashboards” that show you volumes and mode shares, or volume changes and mode shifts. Choose a state, then an SA2, then you might need to zoom/pan the maps to show the areas of interest (unfortunately I can’t find a way to change the map zoom to be relevant to your selected SA2). The good thing about these dashboards is that you see mode shares and volumes on the same page.

• Mode shares and volumes for a selected work SA2 (2011 or 2016)
• Mode shares and volumes for a selected home SA2 (2011 or 2016)
• Mode shifts and volume changes for a selected work SA2 (changes 2011 to 2016)
• Mode shifts and volume changes for a selected home SA2 (changes 2011 to 2016)

Play around with the various filtering options to get different views of the data, including an option to turn on/off labels (which can overlap a lot when you zoom out), and change the colour scheme for mode share maps.

If you want more detail and/or have a smaller screen, then you might want to use one of the following links to a single map/chart:

Once you have the tool open in Tableau Public you can switch between the dashboards and worksheets with the tabs at the top (note: it will reset if you don’t use it for a while). You can mouse over the data to see more details (I’ve tried to list relevant data for each area), and often your filtering selections will apply to related tabs.

Finally remember to be careful in your analysis:

• A large mode share or mode shift might not be for a significant volume.
• A large change in volume might not be a significant mode shift.

Have fun!

[This post and the Tableau tool were updated 3 February 2018 with better label positions on maps. For larger SA2s, label positions better reflect the centre of residential or working population, as appropriate to the type of map. The Tableau tool should also be faster to load]

Between 2011 and 2016, Greater Brisbane saw a 2% mode shift towards private motorised transport for journeys to work, the largest such shift of all large Australian cities. Was it to do with where jobs growth happened, or because public transport became less attractive over that time?

This post takes a more detailed look at the spatial changes in private transport mode shares, and then examines the relative impact on spatial variations in jobs growth compared to other factors.

Greater Brisbane main mode shares

Firstly for reference, here are the Brisbane Greater Capital City Statistical Area main mode shares and shifts for 2011 and 2016, measured by place of enumeration and place of work:

More information about main mode definitions and data in general is available at the appendix at the end of this post.

Mode shares and shifts by home location

Here are private transport mode shares by home location for 2006, 2011, and 2016:

(you might need to click on these charts to see them larger and more clearly)

You can see lower private mode shares around the central city and to some extent along the rail lines. In case you are wondering, the Redcliffe Peninsula railway opened in October 2016 – after the August 2016 census.

The changes between years are a little difficult to make out on the map above, so here are the mode shifts to private transport by home location at SA2 level:

Mode shifts to private transport can be seen over most parts of Brisbane, with the biggest being Auchenflower (+6%), Lawnton (+6%), Toowong (+5%), Norman Park (+5%), Strathpine – Brendale (+5%), Keperra (+5%), and Sandgate – Shorncliffe (+5%). Many of the large mode shifts to private transport were actually seen around the train network.

The Redland Islands area had a larger shift to public transport – but keep in mind this will include use of car ferries.

Here’s a map showing the mode split of net new trips by home SA2:

There were a lot of new trips from outer growth areas in the north, west and south, and the vast majority of these trips were by private transport (although the southern growth area of Springfield Lakes, where a rail line opened in 2010, had a relatively high 15% of new trips by public transport). Private transport mode shares of new new trips were also high in middle and most inner suburbs (unlike inner Melbourne).

To sum all that up, here are the changes in trip volumes by main mode and home distance from the CBD:

Private transport dominated most new trips, and there were net declines in public transport trips beyond 2 km from the CBD.

Here’s a look at the main mode split over time, by distance from the CBD:

Brisbane achieved significant mode shift away from private transport between 2006 and 2011, but that was pretty much reversed between 2011 and 2016.

Private transport mode shares dropped in 2011 but pretty much returned to 2006 values in 2016. On average, only the city centre saw a mode shift away from private transport between 2011 and 2016, and that’s only a tiny fraction of the Brisbane’s population.

Mode shares and shifts by work location

Here are workplace private transport mode shares for 2011 and 2016:

(more areas are coloured in 2016 because they reached my minimum density threshold of 4 jobs per hectare at destination zone level for inclusion on the map)

Low private mode share is only really seen around the city centre. Some lower mode share areas further out include St Lucia (UQ campus, 52% in 2016) and Nundah (74%), but most of the suburban jobs are dominated by private transport.

Here are the mode shifts by workplace location:

The biggest mode shifts to private transport were to workplaces in Wooloowin – Lutwyche (+7%), Spring Hill (just north of the CBD, +5%) and Jindalee – Mount Ommaney (+5%). The biggest shifts away from private transport were in Newstead – Bowen Hills (-6%), St Lucia (-4%, which includes the University of Queensland main campus), and West End (-3%).

Notably, the job rich Brisbane CBD had a 2% shift to private transport (with 3,135 more private transport trips in 2016).

Here’s a map of the net new jobs and their main mode splits:

And a zoom in on the inner city to separate the overlapping pie charts:

The SA2 with the biggest jobs growth was “Brisbane City” (covering the CBD) with 4584 new jobs – with 68% of this net increase attributable to private transport. North Lanes – Mango Hill in the northern suburbs was not far behind (4472 new jobs at 96% by private transport), followed by Newstead – Bowen Hills (4266 new jobs at 49% private transport) and Brisbane Airport (4197 new jobs at 95% private transport).

The distribution of jobs growth was not heavily concentrated in central Brisbane – in stark contrast to Melbourne where the central city jobs growth was much more signficant.

Here’s a clearer view of new jobs by workplace distance from the city centre and main mode:

At all distances from the CBD, private transport new trips outnumbered active and public transport new trips (and there was a decline in public transport trips to the very city centre). The vast majority of net new trips were to workplaces more than 4 km from the city centre, and by private transport.

So why was there an overall 2% mode shift to private transport?

The relative lack of jobs growth in the public transport rich city centre is very likely to have contributed to the mode shift to private transport. The vast majority of new jobs were in the suburbs where public transport is significantly less competitive (relative to the CBD).

Others will point to factors that have made public transport less attractive relative to private transport, including problems on the train network, extensive new motorway infrastructure, and public transport fares growing around twice the rate of inflation after 2010.

There was very rapid growth in fares between 2010 and 2015, but then fares were frozen in 2016 and substantially reduced in 2017:

Looking at people working in Greater Brisbane (Greater Capital City Statistical Area), there were 94,055 new private transport commutes, just 246 new public transport commutes, and 2,506 new active transport commutes. So around 97% of net new trips in 2016 were by private transport, much higher than the 2011 baseline private transport mode share of 79% of trips (measured for workplaces in Greater Brisbane), hence the overall 2% mode shift.

Looking at people living in Greater Brisbane, there were 61,557 new private transport commutes, a net reduction of 6,069 public transport commutes, and a net reduction of 54 active transport commutes. Thus every new commute was accounted for by private transport, and further to this there was mode shift away from active and public transport.

So how much of the mode shift can be explained by spatial changes in jobs distribution? If mode shares in each workplace SA2 had not changed between 2011 and 2016 then city level mode shares would be influenced only by spatial variations in jobs growth.

I’ve done the calculations at SA2 geography: if place of work mode shares in Brisbane had not changed between 2011 and 2016 (but volumes had), then the overall private transport mode share would have increased only 1.0% in 2016 (essentially because of higher jobs growth in the suburbs compared to the centre).

Actual private mode share increased by 2.0% (measured by place of work).

So this suggests only half of the mode shift can be explained the spatial variations in jobs growth. The other half will be explained by other factors, particularly changes in the relative attractiveness of modes.

Changes in the relative attractiveness of modes will include public transport service quality, public transport fares, fuel prices, toll prices, and infrastructure provision for private and active transport. Car ownership will undoubtedly be a factor, but I suspect many ownership decisions will be influenced by workplace locations and relative modal attractiveness. Other factors might include changes in real incomes, demographic changes, changes in employment density, and the locations of population growth. I’ll explore the last two in more detail.

What about the relationship between job density and mode share?

You could argue that if general public transport “attractiveness” had not changed, you could still expect a mode shift towards public transport in areas with both high and increasing job density, as car parking might struggle to grow at the same rate as jobs growth (as the land becomes increasingly valuable/scarce). This might particularly be the case in the city centre.

I’ve calculated weighted job density for each SA2 – that is, the average density of destination zones in the SA2, weighted by the number of jobs in each zone (similar to population weighted density, so that large areas within SA2s that house few jobs make little contribution to such scores).

Here’s how weighted job density and workplace private mode share changed in Brisbane for higher density SA2s:

While there is some relationship between job density and private mode share overall, there wasn’t a consistent negative correlation between changes in those values. If there was, you would expect all lines on the chart to be on a similar diagonal orientation (upper left – lower right).

South Brisbane and Upper Mount Gravatt saw increased density but little change in private mode share. Chermside, Auchenflower, and Woolloongabba (which incidentally is at the southern end of the Clem 7 motorway) saw increased job density but also increased private transport mode share (the opposite effect of what you might expect). Spring Hill had only a small drop in job density but a large increase in private mode share.

Newstead – Bowen Hills had the largest shift away from private transport, and also one of the largest increases in job density

You might be wondering how the Brisbane City SA2 (which includes the CBD) can have had an increase in total jobs, but a slight decline in weighted jobs density. It turns out that the 2016 SA2 boundary goes further into the Brisbane River than the 2011 boundary. Here’s a map generated on the ABS website, where blue lines are the 2011 boundaries and red the 2016 boundaries:

If you discounted the increase in area, you might expect a slight increase in job density (about 4% in unweighted average density) to result in a small mode shift away from private transport, quite the opposite of what actually happened. If increasing job density by itself might have pushed a mode shift away from private transport, it appears it was overpowered by factors working in the opposite direction.

The Brisbane City SA2 accounted for 12.5% of Brisbane’s jobs so its mode split impacts more than most on overall city mode shares.

So what might be the stand-alone impact of increased job density in the city centre on private mode share? It’s very hard to quantify. I can certainly look at other city centres, but there will be so many factors at play in those cities that it would be almost impossible to isolate the impact.

But as a rough stab, had Brisbane City SA2’s private mode share increased from 29.0% to 29.5% (instead of 30.6%), and all other things were the same, then the overall Brisbane private mode share would have been 0.14% lower.

While the actual impact is uncertain, it would only increase the influence of the “other factors” that are responsible for at least half of the 2% mode share towards private transport.

And what about the spatial distribution of population growth?

All other things being equal, if population growth had disproportionately occurred in places with high private transport mode share (eg the middle and outer suburbs), you might expect a mode shift to private transport. However I don’t think this was significant in Brisbane as there has also been inner city population growth.

Indeed, if the home-based private transport mode share of each SA2 had not changed between 2011 and 2016 (but population numbers had), then the overall Brisbane private mode share (by place of enumeration) would have increased only 0.1% (rather than 1.9%). So the overall mode shift doesn’t seem to have a lot to do with where population growth happened.

So what are these effects other cities? I’ll cover that in an upcoming post.

Appendix: about the data

Here’s how I have defined “main mode”:

I have extracted data from the ABS census for 2006, 2011, and 2016 for areas within the 2011 boundary of the Brisbane Significant Urban Area. The detailed maps are at the smallest available geography – Census Collector Districts (CD) for 2006 and Statistical Area Level 1 (SA1) for 2011 and 2016 for home locations, and Destination Zones (DZ) for workplaces in 2011 and 2016 (detailed workplace data is not readily available for 2006 for most cities). I’ve aggregated this data for distance from city centre calculations (filtered by 2011 Significant Urban Area boundaries), which means the small randomisations will have amplified slightly.

In 2011, a significant number of jobs were not assigned to a destination zone:

• 3.8% of jobs were assigned to an SA2 but not a DZ – I’ve imputed these proportionately to the DZs in their SA2 based on modal volumes reported for each DZ (for want of something better).
• 18,540 Queensland jobs (0.9%) were only known to be somewhere in Greater Brisbane.
• 115,011 jobs (5.8%) were only known to be somewhere in Queensland (hopefully mostly outside Greater Brisbane!).

These special purpose codes are not present in the 2016 data – presumably the ABS did a much better job of coding jobs to DZs. It means that the volumes in 2011 may be slightly understated, and so growth between 2011 and 2016 might be slightly overstated.

I’ve also extracted the data at SA2 (Statistical Area Level 2) based on 2016 boundaries for the purposes of calculating mode shifts and changes in trip volumes at SA2 level (to avoid aggregating small random adjustments ABS applies). However this wasn’t possible for jobs where 2011 SA2s were split into smaller SA2s in 2016 – because some 2011 jobs were assigned an SA2 but not a DZ, so we cannot map those to a specific 2016 SA2 (I aggregated imputed DZ numbers to 2016 SA2 boundaries instead).

I also extracted data at the Brisbane Greater Capital City Statistical Area level, as noted (the boundary did not change between 2011 and 2016).

I have not counted jobs that were reported to have no fixed address in my place of work analysis. I’ve also excluded people who worked at home, did not go to work on census day, or did not provide information about their mode(s) of travel. These workers are also excluded from job density calculations.

Relatively dense suburban employment clusters can deliver more knowledge-based jobs closer to people living in the outer suburbs. Sydney has many such clusters, and Melbourne is now aiming to develop “National Employment and Innovation Clusters” as part of the city’s land use strategy, Plan Melbourne.

So what can we learn about existing employment clusters in Australian cities, particularly in regards to journeys to work? Can relatively dense suburban employment clusters contribute to more sustainable transport outcomes? Do such clusters have lower private transport mode shares than other parts of cities? How are mode shares changing for these clusters? How far do people travel to work in these clusters? Is there a relationship between job density, parking prices, and mode shares? How well served are these clusters by public transport? How do these clusters compare between cities?

This post investigates 46 existing clusters in Australia’s six largest cities. This is a longer post (there is a summary at the end), but I hope you find at least half as interesting as I do.

What’s a dense suburban employment cluster?

That’s always going to be an arbitrary matter. For my analysis, I’ve created clusters based on destination zones that had at least 40 employees per hectare in 2011 or 2016, were more than 4km from the city’s main CBD, and where collectively at least around 6,000 employees travelled on census day in 2016.

Unfortunately I can only work with the destination zone boundaries which may or may not tightly wrap around dense employment areas. Also, in order to ensure reasonable comparisons between census years, I’ve had to add in some otherwise non-qualifying zones to keep the footprints fairly similar. To mitigate potential issues with low density zones being included, I’ve used weighted employment density for each cluster in my analysis. But still, please don’t get too excited by differences in weighted job density as it’s far from a perfect representation of reality.

In particular, the following clusters include destination zones comprising both dense employment and non-employment land and so will potentially have understated weighted job density:

• Nedlands
• Fremantle
• Bedford Park
• Tooronga
• Camberwell Junction
• Hawthorn
• Belconnen
• Campbelltown
• Hurstville
• Kogarah
• Randwick
• North Ryde (quite significant – actual density is probably double)
• Macquarie Park (a destination zone for the university includes large green areas)
• Rhodes (significant residential area)
• Parramatta (includes parkland)
• Penrith (residential areas)
• Bella Vista – Norwest – Castle Hill (includes a golf course)

Some of these clusters are a little long and thin and so are literally stretching things a little (eg Bella Vista – Norwest – Castle Hill, and Alexandria – Mascot), but it’s hard to cleanly break up these areas.

I think my criteria is a fairly low threshold for suburban employment clusters, but raising the criteria too much would knock out a lot of clusters. I should note that some potential clusters might be excluded simply because they did not contain small destination zones concentrated on more dense areas.

Belmont in Perth was the lowest density cluster to qualify (weighted jobs density of 42 jobs / ha). Here’s what it looks like (in 3D Google Maps in 2018):

Chatswood in Sydney was the highest density cluster – with a weighted job density of 433 jobs / ha. Here’s what it looks like (in 3D Apple Maps in 2018):

Apologies if your favourite cluster didn’t make the criteria, or you don’t like my boundaries. You can look up the 2016 boundaries for each cluster here, or view them all through Google maps.

Where are these clusters?

On the following maps I’ve scaled the clusters by employment size and used pie charts to show the modal split for journeys to work in 2016. All pie charts are to the same scale across the maps (the size of the pie charts is proportional to the number of journeys to the cluster in 2016).

Note that North Sydney is excluded because it is within 4 km of the CBD.

All of Melbourne’s clusters are east of the CBD, with Clayton the largest. Places just missing out on the cluster criteria include parts of the Tullamarine industrial area (5271 jobs at 55 jobs/ha), Doncaster (around 5000 jobs at 40+ jobs/ha), Chadstone Shopping Centre (5375 jobs at 105 jobs/ha), and La Trobe (around 7700 jobs but low density – and even if there was a destination zone tightly surrounding the university campus I suspect it would still not qualify on density ground).

Only three suburban clusters qualified in Brisbane.

Note: the Nedlands and Murdoch clusters are essentially the hospital precincts only and do not include the adjacent university campuses.

Adelaide only has one suburban cluster that qualifies – Bedford Park – which includes the Flinders University campus and Flinders Medical Centre.

The Canberra clusters cover the three largest town centres, each containing at least one major federal government department head office.

What proportion of jobs are in these dense suburban employment clusters?

The following chart shows that Sydney and Canberra have been most successful at locating jobs in suburban employment clusters (well, clusters that meet my arbitrary criteria anyway!):

The proportion of jobs not in the inner 4km or a suburban employment cluster increased between 2011 and 2016 in all cities except Sydney (although the shift was very small in Melbourne).

Here’s a summary of private transport mode shares for the clusters, versus the inner city versus everywhere else:

Inner city mode shares vary considerably between cities, in order of population size. Total job cluster private mode shares are only 4-7% lower than elsewhere in most cities, except for Sydney where they are 17% lower.

Sydney’s clusters combined also have a significantly lower private mode share of 68% – compared to 84-89% in other cities.

How do the clusters compare?

Here is a chart showing their size, distance from CBD, and private transport mode share for journeys to work in 2016:

Next is a chart that looks at weighted job density, size, and private mode share for 2016. Note I’ve used a log scale on the X axis.

(Unfortunately the smaller Kogarah dot is entirely obscured by the larger Alexandria – Mascot dot – sorry that’s just how the data falls)

There is certainly a strong relationship between weighted job density and private mode shares (in fact this is the strongest of all relationships I’ve tested).

Sydney has many more clusters than the other cities (even Melbourne which has a similar population), it has much larger clusters, it has more dense clusters, and accounts for most of the clusters in the bottom-right of the chart.

And there’s just nothing like Parramatta in any other city. It’s large (~41,000 jobs in 2016), has relatively low private transport mode share (51%), is about 20 km from the Sydney CBD, and has a high jobs density.

Melbourne’s Clayton has about three-quarters the jobs of Parramatta, is around the same distance from its CBD, but is much less dense and has 90% private mode share for journeys to work.

Curiously Sydney’s Macquarie Park – which on my boundaries has about the same number of jobs as Parramatta – is closer to the Sydney CBD and has a much higher private transport mode share and a lower job density. However it’s rail service is relatively new, opening in 2009.

Perth’s Joondalup and Murdoch are relatively young transit oriented developments with relatively new train stations (opening 1992 and 2007 respectively), however they also have very high private transport mode shares, which I think highlights the challenge of creating suburban transit-adjacent employments clusters surrounded by low density suburbia.

Also, many of Sydney’s suburban clusters have a lower private mode share than that of the overall city (67.6%). That’s only true of Hawthorn and Camberwell Junction in Melbourne, Fremantle in Perth, and Woden and Belconnen in Canberra.

Some outliers to the top-right of the second chart include Heidelberg (in Melbourne), Liverpool (in Sydney), and Nedlands (in Perth). The Heidelberg and Nedlands clusters are relatively small and are dominated by hospitals, while 37% of jobs in Liverpool are in “health care and social assistance”. Hospitals employ many shift workers, who need to travel at times when public transport is less frequent or non-existent which probably explains their relatively high private transport mode shares. Heidelberg is located on a train line, and is also served by several relatively frequent bus routes, including one “SmartBus” route, but still has a very high private transport mode share of 85%.

Outliers to the bottom-left of the second chart include Randwick, Burwood, and Marrickville (all in Sydney). While these are less dense clusters, I suspect their relatively low private transport mode shares are because they are relatively inner city locations well served by public transport.

As an aside, if you were wondering about the relationship between job density and private mode shares for inner city areas, I think this chart is fairly convincing:

Of course this is not to say if you simply increase job density you’ll magically grow public transport patronage – there has to be capacity and service quality, and you probably won’t get the density increase without better public transport anyway.

How well connected are these job clusters to public transport?

Arguably the presence of rapid public transport is critical to enabling high public transport mode shares, as only rapid services can be time competitive with private transport. By “rapid” I consider services that are mostly separated from traffic, have long stop spacing, and therefore faster average speeds. For Australian cities this is mostly trains, but also some busways and light rail lines (but none of the clusters are served by what I would call “rapid” light rail). Of course there is a spectrum of speeds, including many partly separated tram and bus routes, and limited stops or express bus routes, but these often aren’t time competitive with private cars (they can however compete with parking costs).

I have classified each cluster by their access to rapid transit stations, with trains trumping busways (note Parramatta, Blacktown, Westmead, and Liverpool have both), and some clusters sub-classified as “edge” where only some edge areas of the cluster are within walking distance of a rapid transit station (although that’s not clear cut, eg Murdoch). Here are the public transport mode shares, split by whether journeys involved trains or not:

It’s probably of little surprise that all of the high public transport mode share centres are on train lines (except Randwick), and that most public transport journeys to these clusters involve trains. However the presence of a train station certainly does not guarantee higher public transport mode share.

Only four clusters have some degree of busway access (Chermside and Randwick are not actually on a busway but have a major line to them that uses a busway). Only Upper Mount Gravatt has a central busway stations, and it has the third highest non-train (read: bus) access share of 12%.

Randwick is an interesting exception – the University of New South Wales campus in this cluster is connected to Central (train) Station by high frequency express bus services which seem to win considerable mode share. A light rail connection is being constructed between Randwick and the Sydney CBD.

Non-rail (essentially bus) public transport mode shares are also relatively high in Bondi Junction (15%), Parramatta (11%), Belconnen (10%), Brookvale (10%), Woden (10%), Fremantle (9%), Macquarie Park (9%). These are all relatively strong bus nodes in their city’s networks.

Clayton and Nedlands are not on rapid transit lines, but both have high frequency bus services to nearby train stations which results in slightly higher train mode shares (4% and 5%). For Clayton, only the Monash University campus is connected by a high frequency express bus and it had a 17% public transport mode share, whereas the rest of the cluster had public transport mode shares varying between 3 and 7%.

The Bedford Park cluster is frustratingly just beyond reasonable walking distance of Tonsley Railway Station (12 minutes walk to the hospitals and almost half an hour’s walk to the university campus) – so only about 10 people got to work in the cluster by train in 2016. However that’s going to change with an extension of the train line to the Flinders Medical Centre.

The train-centred clusters with low public transport mode shares are mostly not in Sydney, and/or towards outer extremities of the train network (except Box Hill and Heidelberg in Melbourne). So what is it about Sydney’s trains that makes such a difference?

Sydney’s train network is distinctly different to all other Australian cities in that there are many more points where lines intersect (outside the central city), creating many “loops” on the network (for want of a better expression). In all other cities, lines only generally intersect in the central city and where radial lines split into branches, and cross city trips by public transport generally only possible by buses (in mixed traffic). In Sydney lines do branch out then but then often bend around to intersect other neighbouring lines. This provides significantly more connectivity between stations. For example, you can get to Parramatta from most lines directly or with a single transfer somewhere outside central Sydney. Indeed, Sydney is the only city with a regular non-radial train service (T5 Leppington – Richmond, although it only runs every half-hour).

I’ve roughly overlaid Sydney’s dense suburban job clusters (in red) on its rail network map, and then marked the train mode shares:

While some clusters can only be accessed by a radial train line (or are off-rail), many are at intersection points, and most can be accessed by multiple paths along the network. The 29%+ train mode shares for Chatswood, Parramatta, St Leonards, Burwood, and Rhodes might be partly explained by these being highly accessible on the train network.

Here are Melbourne’s dense suburban employment clusters and train mode shares overlaid on Victoria’s rail network map:

The clusters connected to more train lines (Hawthorn and Camberwell) have higher train mode shares, although they are also closer to the city.

The Spatial Network Analysis for Multimodal Urban Transport Systems (SNAMUTS) methodology (led by Professor Carey Curtis and Dr Jan Scheurer) uses graph-based analysis of public transport networks to develop several indicators of network performance. One indicator that measures network accessibility is closeness centrality, which looks and speed and frequency of services to connect to other nodes in the network (it actually uses inter-peak frequencies and speeds, but they probably correlate fairly well with services in peak periods). A lower score indicates better accessibility.

I’ve extracted the closeness centrality scores for public transport nodes in each employment clusters (from the nearest available data to 2016 at the time of writing, some as old as 2011 so not perfect) and compared this with private transport mode shares to these clusters:

Some clusters were not really centred on a public transport node in the SNAMUTS analysis (eg Osborne Park in Perth, Clayton in Melbourne) and hence are not included in this analysis. These clusters have very high private transport mode shares, and would likely be towards the top right of the chart.

There’s clearly a relationship between the closeness centrality and private mode shares, with low private more shares only occurring where there is high accessibility by public transport. But it’s not super-strong, so there are other factors at play.

Some of the outliers in the bottom right of the distribution include Upper Mount Gravatt (based on a large shopping centre but also on a busway), Murdoch (dominated by hospitals a moderate walk from the station), Nedlands (also dominated by hospitals), Chermside (a combination of hospital and large shopping centre, with the bus interchange remote from the hospital), and Bedford Park (where 63% of jobs are in health) . Again, the pattern of higher private transport mode shares to hospitals is evident.

So do you need strong public transport access to support higher job densities? Here’s the relationship between closeness centrality and weighted job density:

There are no clusters with poor public transport access and high job density, which is not surprising. But this does suggest it could be difficult to significantly increase job densities in clusters currently in the top left of this chart without significantly improving public transport access.

Interestingly, Box Hill in Melbourne does have a similar closeness centrality score to Parramatta and Chatswood in Sydney, suggesting it might be able to support significantly higher job density. However, it only has rapid (train) public transport from two directions. It might be more challenging to maintain bus and tram travel times from other directions if there is significant jobs growth.

Melbourne’s largest cluster – Clayton – is not on the chart because it is not centred on a public transport node. There is however a bus interchange on the southern edge of the cluster at Monash University, which has a relatively low closeness centrality score of 64. I suspect the main employment area would probably have a higher closeness centrality score if it were to be measured because it not connected to the train network by a high frequency express shuttle service and has fewer bus routes. That would place it in the top-left part of the above chart (2016 weighted job density being 63 jobs/ha).

Do higher density clusters have fewer car parks?

The higher density centres certainly tended to have lower private mode shares, but does that mean they don’t have much car parking?

Well I don’t know how many car parking spaces each centre had, but I do know how many people travelled to work by car only, and from that I can calculate a density of car-only journeys (and I’ve calculated a weighted average of the destination zones in each centre). That’s probably a reasonable proxy for car park density.

Here’s how it compares to jobs density (note: log scales on both axes):

There is a very strong correlation between the two – in general centres with higher job density also have higher car density. The strongest correlation I can find is for a quadratic curve that flattens out at higher job densities (as drawn, with R-squared = 0.77), which simply suggests you get lower private mode shares in higher density clusters (in general).

The clusters on the bottom side of the curve have lower car mode shares, and so have a lower car density. Many are inner city locations with better public transport access, but also many nearby residents.

Heidelberg (a hospital-based cluster in Melbourne), has the highest car density of all centres and a high job density, but isn’t a large centre.

Do walking mode shares increase when there are many nearby residents?

If there are many residents living within walking distance of a cluster, relative to the size of that cluster, then you might expect a higher walking mode share, as more employees of the cluster are likely to live nearby.

I’ve roughly summed the number of residents who travelled to work (anywhere) and lived within 1km of each cluster. I’ve then taken the ratio of those nearby working residents to the number of journeys into the cluster, and then compared that with walk-only mode shares for 2016:

Yes, there’s definitely a relationship (although not strong), and this may explain some of the outliers in the previous charts such as Randwick, Marrickville, St Leonards and Bondi Junction.

Is there a relationship between parking costs and mode shares?

It’s quite difficult to definitively answer this question because I don’t have parking prices for 2016, and many car commuters might not be paying retail prices (eg employer-provided free or subsidised parking).

I’ve done a quick survey using Parkopedia of parking prices for parking 8:30 am to 5:30 pm on Monday 2 July 2018, and picked the best price available in each cluster. Of course not everyone will be able park in the cheapest car park so it’s certainly not an ideal measure. An average price might be a slightly better measure but that would be some work to calculate.

But for what it worth, here is the relationship between July 2018 all day parking prices and 2016 private transport mode shares:

You might expect an inverse correlation between the two. Certainly clusters with very cheap or free parking had very high private transport mode shares, but other centres are scattered in the distribution.

Looking at outliers in the top right: I suspect Bedford Park (63% health workers), Heidelberg (hospital precinct), Tooronga (with one major employer being the Coles HQ), Chermside (including Prince Charles Hospital), and Rhodes will have significantly cheaper parking for employees (with visitors paying the prices listed on Parkopedia). Indeed, I could not find many parking prices listed for Rhodes, but there are clearly multi-storey parking garages near the office towers not on Parkopedia.

Looking at outliers in the bottom left: Relatively cheap $15 parking is available at multiple car parks in Bondi Junction. The $10 price in Chatswood was only available at one car park, with higher prices at others, so it is probably below the average price paid. Maybe traffic congestion is enough of a disincentive to drive to work in these centres?

For interest, here’s the relationship between weighted car density and parking prices:

The relationship is again not very strong – I suspect other factors are at play such as unlisted employer provided car parking, as discussed above.

So does job growth in suburban employment clusters lead to lower overall private transport mode shares?

Here is a chart showing the effective private mode share of net new trips in each job cluster, plus the inner 4 km of each city:

(Fremantle, Dandenong, Burwood, and Woden had a net decline in jobs between 2011 and 2016 and so have been excluded from this chart)

The chart shows that although many suburban jobs clusters had a low private mode share of net new trips, it was always higher than for the inner 4 km of that city.

Here’s a summary of net new trips for each city:

So every new 100 jobs in suburban employment clusters did generate many more private transport trips than new jobs in the inner city, particularly for Sydney (45 : 10), Melbourne (68 : 13), and Canberra (84: 18). But then new jobs in suburban employment clusters had significantly lower private transport mode shares than new jobs elsewhere in each city.

So arguably if you wanted to minimise new private transport journeys to work, you’d aim for a significant portion of your employment growth in the central city, and most of the rest in employment clusters (ideally clusters that have excellent access by rapid public transport). Of course you would also want to ensure your central city and employment clusters were accessible by high quality / rapid public transport links (not to forget active transport links for shorter distance commutes).

One argument for growing jobs in suburban employment clusters is that new public transport trips to suburban employment clusters will often be on less congested sections of the public transport network – particularly on train networks (some would even involve contra-peak travel relative to central city). On the other hand, new jobs in the central city have much higher public transport mode shares, but relatively expensive capacity upgrades may be required to facilitate the growth.

New active transport trips to the central city and employment clusters probably requires the least in terms of new infrastructure, and there are probably very few congested commuter cycleways in Australian cities at present.

Another argument for suburban employment clusters is to bring jobs closer to people living in the outer suburbs.

Are new private transport trips to suburban employment clusters much shorter than new private transport trips to the central city, and therefore perhaps not as bad from a congestion / emissions point of view?

Certainly many of these clusters will have congested roads in peak periods, but the distance question is worth investigating.

So how far do people travel to work in different employment clusters?

The 2016 census journey to work data now includes on-road commuting distances (thanks ABS!).

Of course for any jobs cluster there will be a range of people making shorter and longer distance trips and it is difficult to summarise the distribution in one statistic. Averages are not great because they are skewed by a small number of very long distance commutes. For the want of something better, I’ve calculated medians, and here are calculations for Sydney job clusters:

(I’ve added a “Sydney” jobs cluster which is the “Sydney – Haymarket – The Rocks” SA2 that covers the CBD area).

There’s a lot going on in this data:

• Median distances for private transport commutes to most employment clusters are longer than to the CBD (particularly the big clusters of Macquarie Park and Parramatta).
• The clusters of Brookvale, Bondi Junction, and Randwick near the east coast have lower medians for motorised modes, probably reflecting smaller catchments. Randwick and Brookvale also do not have rail access, which might explain their low median public transport commute distances.
• Public transport median commute distances were longer in the rail-based near-CBD clusters of Bondi Junction, Alexandria – Mascot, and St Leonards, but also in some further out rail-based clusters, including Parramatta, Westmead and Penrith.
• Penrith – the cluster furthest from the Sydney CBD – curiously had the longer public transport median commute distance, which probably reflects good access from longer distance rail services (but public transport mode share was only 14%).
• Active transport medians vary considerably, and this might be impacted by the mix of shorter walking and longer cycling trips. For example, North Ryde saw more cycling than walking trips, but also had only 1% active transport mode share.

Here’s the same for Melbourne (with a cluster created for the CBD):

Clayton, Dandenong, and Melbourne CBD median commute distances were very similar, whereas median commutes to other clusters were mostly shorter.

Here are results for clusters in the smaller cities:

In Perth, Joondalup had shorter median commuter distances, while Osborne Park and Murdoch (both near rapid train lines) had the longest median public transport journey distances (but not very high public transport mode shares: 7% and 15% respectively). Half of the suburban clusters had a longer median private transport distance than the CBD, and half were shorter.

In Brisbane, median private commute distances were shorter in Chermside, but similar to the city centre for other clusters.

Coming back to our question, only some suburban employment clusters have shorter median private transport commute distances. I expect the slightly shorter distances for those clusters would not cancel out the much higher private transport mode shares, and therefore new suburban cluster jobs would be generating more vehicle kms than new central city jobs.

But perhaps what matters more is the distance travelled by new commuters. New trips from the growing urban fringe to a CBD would be very long in all cities. While ABS haven’t provided detailed journey distance data for 2011, some imperfect analysis of 2011 and 2016 straight line commuter distances between SA2s (sorry not good enough to present in detail) suggests average commuter distances are increasing by 1-2 kms across Sydney and 2-3 kms across Melbourne, and these increases are fairly consistent across the city (including the central city). This may reflect urban sprawl (stronger in Melbourne than Sydney), with new residents on the urban fringe a long way from most jobs.

So did private transport mode shares reduce in suburban employment clusters?

Yes, they did reduce in most clusters, but some saw an increase of up to 2%.

The cluster with the biggest shift away from private transport was Rhodes in Sydney (relatively small and only moderately dense), followed by Perth’s fastest growing hospital cluster of Murdoch.

But perhaps more relevant is how fast each cluster is growing and the mode share of new jobs:

If you want to reduce private transport travel growth, then you don’t want to see many clusters in the top right of this chart (growing fast with high dependency on private transport). Those centres could be experiencing increasing traffic congestion, and may start to hit growth limits unless they get significantly improved public transport access.

Of the cluster in the top-right:

• Bella Vista – Norwest – Castle Hill will soon have a rapid rail service with Sydney Metro.
• Murdoch’s high private transport mode share might reflect the fairly long walking distance between the station and hospitals (up to 10 minutes through open space with no tree canopy), but also hospital shift workers who may find private transport more convenient.
• Clayton might reflect most jobs being remote from the train line (although it is served by three SmartBus routes that have high frequency and some on-road priority). Note: my Monash cluster unfortunately does not include the Monash Medical Centre that is closer to Clayton Station and very job dense. The hospital precinct had its own destination zone in 2016 with 88% private transport mode share, but was washed out in a larger destination zone in 2011 which made it difficult to include in the cluster (for the record, that 2011 destination zone also had an 88% private transport mode share).
• Joondalup is a large but not particularly dense employment area, and I suspect many jobs are remote from the train/bus interchange, and some local bus frequencies are low.

Can you predict mode shares with a mathematical model?

I have put the data used above into a regression model trying to explain private transport mode shares in the clusters. I found that only weighted job density, walking catchment size, and distance from CBD were significant variables, but this might be for want of a better measure of the quality of public transport accessibility (SNAMUTS Closeness Centrality scores are not available for many centres).

I also tested the percentage of jobs in health care and social assistance (looking for a hospital effect), the surrounding population up to 10km (nearby population density), median travel distances, and the size of clusters, but these did not show up as significant predictors.

Can you summarise all that?

• Compared to other cities, Sydney has many more clusters and they are larger, more dense, and generally have much lower private transport mode shares.
• With the exception of Canberra, less than half of all jobs in each city were in either the inner city area or a dense suburban jobs cluster. In Perth it was as low as 32%, while Sydney was 45%, and Canberra 54%.
• Higher density clusters correlate with lower private transport mode shares.
• Only higher density clusters centred on train stations with strong connections to the broader train network achieve relatively high public transport mode shares of journeys to work.
• High quality bus services can boost mode shares in clusters, but the highest bus-only mode share was 15% (in 2016).
• High-frequency express shuttle bus services can boost public transport mode shares in off-rail clusters.
• Walk-only mode shares for journeys to work are generally very low (typically 2-5%) but generally higher in clusters where there are many nearby residents.
• Private transport mode shares are generally 90%+ in clusters with free parking.
• I suspect there is a relationship between parking prices and private mode share, but it’s hard to get complete data to prove this. Subsidised employer provided parking probably leads to higher private transport mode shares, and may be common at hospitals. However unexpectedly cheap parking in Bondi Junction and Chatswood needs to be explained (perhaps an oversupply, or just horrible traffic congestion?).
• There is some evidence to suggest hospitals are prone to having higher private transport mode shares, possibly due to significant numbers of shift workers who need to commute at times when public transport service levels are lower.
• Private transport shares in suburban clusters are much higher than central cities, but lower than elsewhere in cities. The private transport mode share of net new jobs in clusters is much higher than for central city areas, but generally lower than elsewhere in cities.
• High density clusters still have large amounts of car parking.
• Median commuter distances to suburban employment clusters are sometimes longer and sometimes shorter than median commuter distances to each cities CBD.
• The clusters of Joondalup, Clayton, Murdoch, and Bella Vista – Norwest – Castle Hill have grown significantly in size with very high private transport mode shares. These centres might be experiencing increased traffic congestion, and their growth might be limited without significant improvements in public transport access.

What could this mean for Melbourne’s “National Employment and Innovation Clusters”?

One motivation for this research was getting insights into the future of Melbourne’s National Employment and Innovation Clusters (NEICs). What follows is intended to be observations about the research, rather than commentary about the whether any plans should be changed, or certain projects should or should not be built.

Firstly, the “emerging” NEICs of Sunshine and Werribee didn’t meet my (arguably) low criteria for dense employment clusters in 2016 (too small). The same is true for the Dandenong South portion of the “Dandenong” cluster (not dense enough).

Parkville and Fishermans Bend would have qualified had I not excluded areas within 4km of the CBD.

Significant sections of the Parkville, Fishermans Bend, Dandenong, Clayton, and La Trobe NEICs are currently beyond walking distance of Melbourne’s rapid transit network. Of these currently off-rail clusters:

• Parkville: a new rail link is under construction
• Fishermans Bend: new light and heavy rail links are proposed. In the short term, paid parking is to be introduced in some parts in 2018 (which had commuter densities of 47-63 per hectare in 2016). The longer term vision is for 80% of transport movements by public or active transport.
• Clayton: New light and heavy rail links are proposed. The Monash University campus has had paid parking for some time, but there appears to be free parking for employees in the surrounding industrial areas to the north and east. It will be interesting to see if/when paid parking becomes a reality in the industrial area (commuter densities ranged from 48 to 74 jobs/ha in 2016, not dissimilar to Fishermans Bend). The Monash Medical Centre area is relatively close to Clayton train station, has very high commuter density (329 per hectare in 2016 before a new children’s hospital opened in 2017) and had 88% private transport mode share in 2016. No doubt car parking will be an ongoing challenge/issue for this precinct.
• La Trobe: No rapid transit links are currently proposed to the area around the university, which had an 83% private transport mode share in 2016. There is a currently a frequent express shuttle bus from Reservoir station to the university campus, and a high frequency tram route touches the western edge of the campus.
• Dandenong South: The area is dominated by industrial rather than office facilities, and the job density ranges from 7 to 33 commuters per hectare, which is relatively low compared to the clusters in my study. There are no commercial car parks listed on Parkopedia so I assume pretty much all employees currently get free parking. No rapid transit stations are proposed for the area. The area is served by a few bus routes, including one high frequency SmartBus route, but 98% of new jobs between 2011 and 2016 were accounted for by private transport trips. This suggests it is difficult even for high-frequency (but non-rapid) public transport to complete with free parking in such areas.

Another potential challenge is connectivity to Melbourne’s broader train network. Parkville (and Fishermans Bend should Melbourne Metro 2 be built) will be well connected to the broader network by the nature of their central location. The area around Sunshine station has excellent rail access from four directions (with a fifth proposed with Melbourne Airport Rail). Dandenong, La Trobe and Werribee are on or near 1 or 2 radial train lines.

You can read more about Melbourne’s employment clusters in this paper by Prof John Stanley, Dr Peter Brain, and Jane Cunningham, which suggests there would be productivity gains from improved public transport access to such clusters.

I hope this post provides some food for thought.

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.