What impact has the 2020 COVID-19 pandemic had on cycling patterns in Melbourne?

Sun 17 May, 2020

[fully revised 12 July 2020 with data up to 5 July 2020]

There has been talk about about a boom in cycling during the COVID-19 pandemic of 2020 (e.g. refer The Age), but has that happened across all parts the city, across lanes and paths, and on all days of the week?

About the data

In Melbourne there are bicycle counters on various popular bike paths and lanes around the city (mostly inner and middle suburbs), and so I thought it would be worth taking a look at the data. But I should stress that the patterns at these sites may or may not cycling patterns across Melbourne.

Here’s a map of the sites, including my classification of bike path sites into ‘recreational’ and ‘other’ (based on time of day demand profiles):

There’s also one bicycle counting site on Phillip Island, which I’m excluding this from this analysis as it is outside Melbourne.

But before plotting the data, it’s important to understand data quality. Since 2015 there have been 35 bicycle counting sites in Melbourne (most of them pairs counting travel in each direction). But for whatever reasons, data is not available at all sites for all days. Here is the daily number of sites reporting from January 2015 to 5 July 2020 (at least with data available as of 9 July 2020).

There are notable gaps in the data, including most of the latter part of November 2017, and around mid-2018.

So any year-on-year comparison needs to includes sites that were active in both years. For my first chart I’m going to filter for sites with complete data for 2019 (all) and 2020 (to 5 July). I’ve also filtered out a few sites with unusual data (very low counts for a period of time – possibly due to roadworks).

How do 2020 volumes compare to 2019?

Here is a chart showing average daily counts as a four week rolling average, dis-aggregated by whether the site was a bike lane (5 sites), recreational path (12 sites), or other path (9 sites) and whether the day was a regular weekday, or on a weekend/public holiday.

Weekday bike lane travel has reduced substantially, although in June the percentage reduction was less. This makes sense as most of these sites are on roads leading to the CBD, and most workers who normally work in the CBD have been working from home.

Volumes in bike lanes on weekends in 2020 have been very similar to 2019. This might reflect bike lanes not attracting additional recreational cyclists, or perhaps an increase in recreational cycling is offset by a decline in commuter cycling.

Volumes on recreational paths have been much higher than in 2019, most significantly on weekends. Again this makes sense, as people will be looking to exercise on weekends in place of other options no longer available (eg organised sports, gyms). In late June and early July, volumes did however reduce, perhaps as gyms reopened (22 June) and some sports resumed. This may change again during the second Melbourne lock down that commenced 9 July 2020.

Weekday traffic on paths not classified as recreational was down significantly in 2020. I’ll explore this more shortly.

How have volumes changed at different sites?

Here’s a look at the percentage change at each site on weekdays. I’m comparing weeks 14-19 of years 2020 and 2019 (33 sites have complete data for both periods). Weeks 14-19 mark the first four full weeks of the first full lock down.

You can see significant reductions near the CBD, and on major commuter routes (lanes and paths). The biggest reduction was 71% on Albert Street in East Melbourne.

The blue squares are mostly recreational paths where there has been massive growth, the highest being the Anniversary trail in Kew at +235%! However I should point out that these growth figures are often off very low 2019 counts. It may be that people working from home (or who have lost their jobs) are now going for recreational rides on weekdays.

You might notice one square with two numbers attached – the +27% is for the Main Yarra Trail (more recreational), and the -32% is for the Gardiners Creek rail (probably more commuter orientated at that point). The two counters are very close together so the symbols overlap.

Here is the same again, but with the changes in average daily counts:

Many of the high growth percentages were not huge increases in actual volumes. The bay-side trail experienced some of the bigger volume increases.

On weekends and public holidays, there were smaller percentage reductions near the city centre, and large increases in the suburbs:

The percentage increases on weekends are not as high because there was a higher base in 2019. The reductions in the central city are smaller, but still significant – this may reflect fewer CBD weekend workers with a downturn in retail activity.

Again, here is a map of the changes in volume on weekends:

How have volumes changed by distance from the CBD?

Here’s another way to view the data – sites by distance from the CBD:

Bike lane volumes are down significantly at most sites, particularly on weekdays. Bike path volumes are down on weekdays at most sites within 6 km of the CBD, but up at sites further out, and up at most sites on weekends.

How have volumes changed by time of day?

I’m curious about the volume changes on paths on weekdays, so I’ve drilled down to hourly figures. Here are the relative volumes per hour for the months April – June:

Bicycle volumes are down in weekday peak periods on all site types, which you might expect as a lot of peak period cycling trips are to/from the central city.

Daytime bicycle volumes are significantly higher on recreational paths, and to a lesser extent on other paths. For the warmer months of April and May there was a recreational peak around 4pm, while in June the profile was more of a single hump across the day.

So the changes in volumes on paths are certainly a mix of reduced peak traffic, and increased off-peak traffic. The middle of the day increase is perhaps people breaking up the day when working from home, or people who are no longer working.

On weekends bike lane volumes are slightly up in the middle of the day, but down in the morning and evening. There’s been a substantial increase in bike path volumes on weekends – suggesting people seeking recreational riding opportunities on the weekend are choosing the much more pleasant bike path environments.

What will happen post COVID-19?

Of course this data only tells us about what’s been happening during the first lock down and the gradual recovery thereafter (until just before the second lock down).

It will be interesting to see if there is an uptick in recreational cycling during the second lock down period, although it is in mid-winter.

Eventually there may well be a boom in cycling (particularly on bike lanes) when more people start returning to work – particularly in the central city – and look for alternatives to (what might be) crowded public transport.

I’ll try to keep an eye on the data over time and update this post periodically.

3 Comments | Cycling, Melbourne | Tagged: | Permalink
Posted by chrisloader

Changes in Melbourne’s journey to work – by mode (2006-2016)

Sun 10 December, 2017

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

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 Pascoe Vale (some of which might be gentrification leading to more central city workers?).

There was also a significant shift to trains in Point Cook, 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):

Melbourne Train mode share 2011 2016 work.gif

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 Dandenong, 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. Note the mode shares are very small, and I’m not willing to calculate a mode share where less than 6 trips were reported but they result in more than 3% mode share (I’ve shaded those zones grey):

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).

If you look closely, you’ll see higher shares in the Essendon – East Keilor corridor, where bus route 465 provides high peak frequencies meeting just about every train (service levels have not changed between 2006 and 2016)

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).

Melbourne tram share

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 +13% in Docklands, followed by +10% 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% in Docklands and 6% in the CBD.

Abbotsford had a 9% 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. In Port Melbourne there was a shift from tram to bus and bicycle.

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

Melbourne tram share workplace

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 were 2% in Brunswick West and 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, with Brunswick SA2 showing the largest growth:

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%) and Fitzroy North (8%).

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 walk-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 (+56 journeys), South Yarra – West (+54), Carlton North – Princes Hill (+80), Fitzroy North (+162) and Brunswick West (+158).

Walking led Fitzroy (+147) and Keilor Downs (+15, with most other modes in small decline, so don’t get too excited).

Bus topped SA2s in the Doncaster corridor, but also Port Melbourne (+176), Vermont South (+30), Kings Park (+10) and Ormond – Glen Huntly (+275 with rail replacement buses operating on census day in 2016).

Tram topped several inner SA2s including the CBD, Docklands and Southbank.

A caution on this map: the contest might have been very close between modes and the map doesn’t tell you how close.

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:

By work location:

Have fun exploring the data!

This post was updated on 24 March 2018 with improved maps. Also, data reported at SA2 level is now as extracted at SA2 level for 2011 and 2016, rather than an aggregation of CD/SA1/DZ data (each of which has small random adjustment for privacy reasons, which amplifies when you aggregate, also some work destinations seem to be coded to an SA2 but not a specific DZ). This does have a small impact, particularly for mode shifts, and mode with the most growth.

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

9 Comments | Cycling, Melbourne, Mode share, Mode shift, Multi-modal | Tagged: | Permalink
Posted by chrisloader

Trends in journey to work mode shares in Australian cities to 2016 (second edition)

Tue 24 October, 2017

[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.

14 Comments | Australian Cities, Brisbane, Cycling, Melbourne, Mode share, Mode shift, Sydney | Tagged: , | Permalink
Posted by chrisloader

What does the census tell us about cycling to work?

Mon 27 January, 2014

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.

Cyclcing only mode share for cities time series

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).

Census day weather

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:

ACT 2011 bicycle

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):

Canberra 2011 SA2 dest bicycle any

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:

Melb bicycle any zoom

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):

bicycle mode share DZ Melbourne inner

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:

Adl bicycle any zoom

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:

Adl 2011 SA2 dest bicycle

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:

Perth cycling inner

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:

Perth 2011 dest SA2 bicycle

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:

Bris cycling

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):

Bris 2011 dest bicycle

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:

Sydney cycling zoom

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

By work location (by smaller destination zone geography):

Syd dest bicycle

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.

Australia 2011 dest bicycle mode share

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:

SA2 distances sample map

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.

2011 Melb JTW cycling distances

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:

cycling - presence of other modes 2006 2011

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:

Other modes with cycling 2011

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:

JTW bicycle + train raw numbers

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:

Melb bicycle + train

How does commuter cycling vary by age and sex?

bicycle mode share by age 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%):

Melb 2011 cycling gender ratio home

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:

Melb 2011 cycling share gender ratio WP

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):

gender ratio and overal mode share

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:

commute distance and gender

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:

cycling by employer type

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:

Council State Bicycle mode share
Tumby Bay (DC) SA 23.5%
Kent (S) WA 18.8%
Carnamah (S) WA 16.0%
Central Highlands (M) Qld 14.3%
Uralla (A) NSW 13.8%
Wakefield (DC) SA 13.5%
Nannup (S) WA 12.5%
Broome (S) WA 12.1%
Alice Springs (T) NT 11.8%
Narembeen (S) WA 11.5%
Blackall Tambo (R) Qld 11.3%
Kowanyama (S) Qld 11.2%
Exmouth (S) WA 11.1%
Yarra (C) Vic 10.4%
Glamorgan/Spring Bay (M) Tas 8.7%
Torres (S) Tas 8.6%
Yarriambiack (S) Qld 8.3%
Mallala (DC) Vic 8.0%
Richmond Valley (A) NSW 7.2%
McKinlay (S) Qld 6.7%

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 share 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:

cycling mode share by profession

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:

cycling mode share by migration year

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.

3 Comments | Australian Cities, Cycling, Melbourne, Mode share | Tagged: | Permalink
Posted by chrisloader

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