Are Melbourne’s suburbs full of quarter acre blocks?

Sun 22 May, 2016

A lot has been said about the great Australian dream of moving to the suburbs and living on a quarter acre block. But is Melbourne suburbia actually full of quarter acre blocks? Where are they to be found? Are they disappearing? This post delves into block sizes in Melbourne.

Where are the quarter acre blocks?

A quarter-acre translates to 1011.7 square metres in modern units, but for the purposes of this post I’ll allow some leeway and count any block between 900 and 1100 square metres. For this post I’ve also filtered out blocks in planning zones that cannot include dwellings (eg industrial areas), but that does mean I’ve included blocks in mixed use zones, commercial zones, etc. So not every block counted is residential. Also some larger blocks might contain multiple small dwellings but not actually be subdivided (eg a block of flats).

First up, here is a map of Melbourne showing the prevalence of quarter acre blocks. It looks like there are lots of them, but because the blocks are so small, the total area occupied by quarter-acre blocks is significantly over-represented on this large scale map.

Melbourne quarter acre block map

There are larger concentrations in the outer north-east and outer-east, but very few blocks in the current growth areas to the west, north and south-east.

Here are the top 20 suburbs for numbers of quarter-acre blocks:

Mooroolbark 1625
Rye 1545
Ferntree Gully 1504
Boronia 1471
Croydon 1437
Mount Martha 1430
Eltham 1229
Mount Eliza 1125
Werribee 1054
Sunbury 1035
Lilydale 996
Mornington 982
Reservoir 978
Balwyn North 936
Berwick 898
Upwey 897
Pakenham 772
Langwarrin 767
Kilsyth 732
Greensborough 724

There are almost 78,000 quarter-acre blocks within Melbourne’s Urban Growth Boundary, which sounds like a lot, but is only 3.75% of the 1.8 million blocks in my dataset.

So what are typical block sizes in Melbourne?

For this analysis I’m considering blocks within land use zones that can include dwellings, that are also within the urban growth boundary. But I’ve excluded blocks of less than 40 square metres on the assumption these are unlikely to contain dwellings.

Here’s the frequency distribution of block sizes in Melbourne:

The most common block size is 640-660 square metres, and 34.5% of blocks are between 520 and 740 square metres. The median is 540-560 square metres. 180-200 is the most common smaller block size, and there is a small spike in block sizes of 1000-1020 square metres, which includes the quarter-acre block. But quarter-acre blocks are certainly very uncommon.

I’ve calculated the median block sizes for all suburbs within Melbourne’s Urban Growth Boundary.

The inner city has median block sizes under 300 square metres, and 300-500 is typical in the inner northern and western suburbs. Block sizes are larger in the middle and outer eastern suburbs, older suburbs in the south-east, and blocks along the Mornington Peninsula. But the more recent growth areas to the west, north and south-east see median block sizes of between 400 and 500 square metres (purple), reflecting higher dwelling densities encouraged by current planning policy for growth areas. Quarter-acre blocks are the median only in places like Upwey, Belgrave and Portsea.

Inner city Carlton has the lowest median of 100-120 square metres, followed by Cremorne, North Melbourne, South Melbourne at 120-140 square metres, and then Abbotsford, Fitzroy North, Port Melbourne, Richmond, West Melbourne at 140-160 square metres. Urbanised suburbs at the other end of the scale include Park Orchards at 3020, Selby at 1440, and Warrandyte at 1260.

There are two interesting outliers in the central city: Southbank (in yellow) has a median block size of 980 square metres, and Docklands (in blue) has a median of 660 square metres. Both have been redeveloped in recent decades with many medium to high-rise apartment towers on those larger blocks.

Beyond these medians, there is a lot of variation within suburbs. Let’s go for a wander around the city.

Mooroolbark has the highest count of quarter-acre blocks and a median size of 840 square metres. As well as larger blocks, you can see a lot of further subdivision, particularly close to the train line (thin black line).

You may have noticed in the suburb map above a black coloured suburb in the middle south-eastern suburbs. That suburb is Clayton, and here is how it looks:

While blocks of 700-800 square metres were probably typical in the original subdivision, further subdivided blocks now outnumber the larger blocks, with a median of 260 square metres. Clayton of course is home to a major Monash University campus, and I suspect a lot of the smaller blocks house students.

A bit further down the line in Noble Park you can see extensive further subdivision near the rail line, surrounded by almost uniform blocks of 500-600 square metres:

Heading further south, Cranbourne is an interesting mix. The inner core (old town) has larger blocks but lots of further subdivision. This is surrounded by many blocks of around 700-800 square metres, but the most recent development has much smaller bocks, most less than 500. It’s a bit like tree rings, with each ring of incremental urban growth reflecting the preferred new block size of the time.

The area around Berwick also has a wide variety of block sizes, depending on the timing of development:

Here is the Frankston area:

Again significant further subdivision in central Frankston, a variety of block sizes in different parts of Langwarrin, and lots of large blocks in Frankston South and Mount Eliza (in some of the pink areas most blocks are over 2500 square metres).

In the middle northern suburbs you can see suburbs from an era when new block sizes were relatively large, and they’ve since had extensive subdivision. Here is Pascoe Vale:

Here is Reservoir. You can see smaller blocks in the surrounding suburbs:

The large block area to the west of the train line was apparently developed around the 1960s.

And to the west St Albans is another suburb with larger blocks being subdivided:

And further east there is a lot of further subdivision in Boronia and Bayswater, particularly near the rail stations:

The north-west corner of Templestowe has not too many larger blocks yet to be subdivided. But to the south-east you can see areas with blocks larger than 1200 square metres (light pink).

The area around Eltham has many large blocks, including many larger than quarter-acres. There has been quite a bit of subdivision around the rail stations however.

Another area with many large blocks is around Upwey/Belgrave:

A significant proportion of blocks are larger than a quarter-acre, with a median of 1060 in Belgrave, 1120 in Upwey, 1000 in Tecoma, and 980 in Upper Ferntree Gully.

If you want a quarter-acre block relatively close to the city, then Balwyn North has quite a few (many with swimming pools). Good luck saving a deposit for those.

But if a quarter-acre block isn’t big enough and you can afford the real estate, then you might want to try Canterbury or Deepdene, also relatively close to the city:

Or of course Toorak with plenty of very large blocks even closer to the city (although many will contain apartment buildings).

Essendon also has some larger blocks, including some quarter-acres:

There has been plenty of further subdivision, but there is also a stripe of green that is mostly in tact (a restrictive covenant applied perhaps?). You can also see the recent Valley Lake development in purple in Niddrie.

Most of the growth areas have small blocks, but here are some exceptions in eastern Doreen:

So there is plenty of variation in block sizes across Melbourne, but not that many quarter-acre blocks. Perhaps we should talk more about the one-seventh-acre block.

Data acknowledgement

This analysis was made possible with data available from data.vic.gov.au under a creative commons license. The data is Copyright © The State of Victoria, Department of Environment, Land, Water & Planning 2016.

I have used November 2015 property boundary data and May 2016 planning zones (sorry, not quite aligned, but this post has been a while in the making and the differences are unlikely to be significant).


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

Thu 26 November, 2015

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

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

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

Why Population Weighted Density?

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

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

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

Sydney harbour

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

Defining cities

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

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

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

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

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

AU EU CA NZ Population Weighted Density

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

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

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

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

How much diversity is there in urban density?

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

AU EU CA NZ urban density distribution

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

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

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

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

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

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

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

How different is population-weighted density from regular density?

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

PWD v regular density 2

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

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

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

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

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

Barcelona

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

 

Perth

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

Paris

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

London

There are many more interesting patterns in other cities.

What does this mean for transport?

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

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

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

All the density maps

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

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


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.


Are Australian cities becoming denser?

Tue 5 November, 2013

[Updated April 2017 with 2015-16 population estimates. First published November 2013]

While Australian cities have been growing outwards with new suburbia, they have also been getting denser in established areas, and the new areas on the fringe are often more dense than growth areas used to be (see last post). So what’s the net effect – are Australian cities getting more or less dense?

This post also explores measures of population-weighted density for Australian cities large and small over time. It also tries to resolve some of the issues in the calculation methodology by using square kilometre geometry, looks at longer term trends for Australian cities, and then compares multiple density measures for Melbourne over time.

Measuring density

Under the traditional measure of density, you’d simply divide the population of a city by the metropolitan area’s area (in hectares). As the boundary of the metropolitan areas seldom change, the average density would simply increase in line with population with this measure. But that density value would also be way below the density at which the average resident lives because of the inclusion of vast swaths of unpopulated land within “metropolitan areas”, and so be not very meaningful.

Enter population-weighted density (which I’ve looked at previously here and here). Population-weighted density takes a weighted average of the density of all parcels of land that make up a city, with each parcel weighted by its population. One way to think about it is the residential density in which the “average resident” lives.

So the large low-density parcels of rural land outside the urbanised area but inside the “metropolitan area” count very little in the weighted average because of their small population relative to the urbanised areas. This means population-weighted density goes a long way to overcoming having to worry about the boundaries of the “urban area” of a city. Indeed, in a previous post I found that removing low density parcels of land had very little impact on calculations of population-weighted density for Australian cities. However, the size of the parcels of land used in a population-weighted density calculation will have an impact, as we will see shortly.

Calculations of population-weighted density can answer the question about whether the “average density” of a city has been increasing or decreasing. But as we will see below, using geographic regions put together by statisticians based on historical boundaries is not always a fair way to compare different cities.

Population-weighted density of Australian cities over time

Firstly, here is a look at population-weighted density of the five largest Australian cities (as defined by ABS Significant Urban Areas), measured at SA2 level (the smallest geography for which there exists a good consistent set of time-series estimates). SA2s roughly equate to suburbs.

According to this data, most cities bottomed out in density in the mid 1990s. Sydney, Melbourne and Brisbane have shown the fastest rates of densification in the last three years.

What about smaller Australian cities? (120,000+ residents in 2014):

Darwin comes out as the third most dense city in Australia on this measure, with Brisbane rising quickly in recent years into fourth place. Most cities have shown densification in recent times, with the main exception being Townsville. On an SA2 level, population weighted density in Perth hardly rose at all in 2015-16 (a year when 92% of population growth was in the outer suburbs)

However, we need to sanity test these values. Old-school suburban areas of Australian cities typically have a density of around 15 persons per hectare, so the values for Geelong, Newcastle, Darwin, Townsville, and Hobart all seem a bit too low for anyone who has visited them. I’d suggest the results may well be an artefact of the arbitrary geographic boundaries used – and this effect would be greater for smaller cities because they would have more SA2s on the interface between urban and rural areas (indeed all of those cities are less than 210,000 in population).

For reference, here are the June 2014 populations of all the above cities:

Australian cities population 2014

The following map shows Hobart, with meshblock boundaries in black (very small blocks indicate urban areas), SA2s in pink, and the Significant Urban Area (SUA) boundary in green.  You can see that many of the SA2s within the Hobart SUA have pockets of dense urban settlement, together with large areas that are non-urban – ie SA2s on the urban/rural interface. The density of these pockets will be washed out because of the size of the SA2s.

Hobart SUA image

 

 

Reducing the impact of arbitrary geographic boundaries

As we saw above, the population-weighted density results for smaller cities were very low, and probably not reflective of the actual typical densities, which might be caused by arbitrary geographic boundaries.

Thankfully ABS have followed Europe and released of a square kilometre grid density for Australia which ensures that geographic zones are all the same size. While it is still somewhat arbitrary where exactly this grid falls on any given city, it is arguably less arbitrary than geographic zones that follow traditional notions of area boundaries.

Using that data, I’ve been able to calculate population weighted density for the larger cities of Australia. The following chart shows those values compared to values calculated on SA2 geography:

pop weighted density 2011 grid and SA2 australian cities

You’ll see that the five smaller cities (Newcastle, Hobart, Geelong, Townsville and Cairns) that had very low results at SA2 level get more realistic values on the kilometre grid.

You’ll notice that most cities (except big Melbourne and Sydney) are in the 15 to 18 persons per hectare range, which is around typical Australian suburban density.

While the Hobart figure is higher using the grid geography, it’s still quite low (indeed the lowest of all the cities). You’ll notice on the map above that urban Hobart hugs the quite wide and windy Derwent River, and as such a larger portion of Hobart’s grid squares are likely to contain both urban and water portions – with the water portions washing out the density (pardon the pun!). While most other cities also have some coastline, much more of Hobart’s urban settlement is near to a coastline.

But stepping back, every city has urban/rural and/or urban/water boundaries and the boundary has to be drawn somewhere. So smaller cities are always going to have a higher proportion of their land parcels being on the interface – and this is even more the case if you are using larger parcel sizes. There is also the issue of what “satellite” urban settlements to include within a city which ultimately becomes arbitrary at some point. Perhaps there is some way of adjusting for this interface effect depending on the size of the city, but I’m not going to attempt to resolve it in this post.

International comparisons of population-weighted density

See another post for some international comparisons using square km grids.

Changes in density of larger Australian cities since 1981

We can also calculate population-weighted density back to 1981 using the larger SA3 geography. An SA3 is roughly similar to a local government area (in Melbourne at least), so getting quite large and including more non-urban land. Also, as Significant Urban Areas are defined only at the SA2 level, I need to resort to Greater Capital City Statistical Areas for the next chart:

This shows that most cities were getting less dense in the 1980s (Melbourne quite dramatically), with the notable exception of Perth. I expect these trends could be related to changes in housing/planning policy over time. This calculation has Adelaide ahead of the other smaller cities – which is different ordering to the SA2 calculations above.

On the SA3 level, Perth declined in population-weighted density in 2015-16.

When measured at SA2 level, the four smaller cities had almost the same density in 2011, but at SA3 level, there is more separating them. My guess is that the arbitrary nature of geographic boundaries is having an impact here. Also, the share of SA3s in a city that are on the urban/rural interface is likely to be higher, which again will have more impact for smaller cities. Indeed the trend for the ACT at SA3 level is very different to Canberra at SA2 level.

Melbourne’s population-weighted density over time

I’ve taken a more detailed look at my home city Melbourne, using all available ABS population figures for the geographic units ranging from mesh blocks to SA3s inside “Greater Melbourne” (as defined in 2011) or inside the Melbourne Significant Urban Area (SUA, where marked), to produce the following chart:

Note: I’ve calculated population-weighted density at the SA2 level for both the Greater Capital City Statistical Area (ie “Greater Melbourne”, which includes Bacchus Marsh, Gisborne and Wallan) and the Melbourne Significant Urban Area (slightly smaller), which yield slightly different values.

All of the time series data suggests 1994 was the turning point in Melbourne where the population-weighted density started increasing (not that 1994 was a particularly momentous year – the population-weighted density increased by a whopping 0.0559 persons per hectare in the year to June 1995 (measured at SA2 level for Greater Melbourne)).

You’ll also note that the density values are very different when measured on different geographic units. That’s because larger units include more of a mix of residential and non-residential land. The highest density values are calculated using mesh blocks (MB), which often separate out even small pockets of non-residential land (eg local parks). Indeed 25% of mesh blocks in Australia had zero population, while only 2% of SA1s had zero population (at the 2011 census). At the other end of the scale, SA3s are roughly the size of local councils and include parklands, employment land, rural land, airports, freeways, etc which dilutes their average density.

In the case of SA2 and SA3 units, the same geographic areas have been used in the data for all years. On the other hand, Census Collector Districts (CD) often changed between each five-yearly census, but I am assuming the guidelines for their creation would not have changed significantly.

Now why is a transport blog so interested in density again? There is a suggested relationship between (potential) public transport efficiency and urban density – ie there will be more potential customers per route kilometre in a denser area. In reality longer distance public transport services are going to be mostly serving the larger urban blob that is a city – and these vehicles need to pass large parklands, industrial areas, water bodies, etc to connect urban origins and destinations. The relevant density measure to consider for such services might best be based on larger geographic areas – eg SA3. Buses are more likely to be serving only urbanised areas, and so are perhaps more dependent on residential density – best calculated on a smaller geographic scale, probably km grid (somewhere between SA1 and SA2).

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The growth of Melbourne 1986-2011, animated

Tue 29 October, 2013

Following on from my recent post about the changing socio-economic landscape of Melbourne, this post simply looks at the changing shape and density of urban Melbourne using 5-yearly census data at collector district (1986-2006) and SA1 level (2011).

Straight to it: here is map of Melbourne residential density, click to enlarge and animate:

Melb CD SA1 density

You can see the sprawl of Melbourne over the years, including changes that suggest shifts in the urban growth boundary after development previously seemed to have stopped against a line (particularly evident on the western edge of the City of Brimbank).

Here is another animated map showing the inner city area, with a density scale ranging from 10 to 100 persons/ha, so you can distinguish higher densities than the map above. Click to enlarge and animate.

Melb inner density

You can see a lot more going on in established areas on this map, including densification in the CBD, St Kilda, St Kilda Road (conversion from office space), Parkville, Port Melbourne around Bay Street, Kensington Banks, Brunswick, Fitzroy, Southbank, South Melbourne, Elwood, Maribyrnong, Carlton, and many more.

A few things to note:

  • The size of the districts changes each year, particularly around the fringe. You’ll often see a large red patch where a larger block is only partly inhabited in one year, only to be replaced by smaller denser patches in future years. Patches of green that disappear might be the enlargement of a district causing a blending out of a small pocket of high density, rather than an actual drop in density.
  • Shades of pink indicate densities between 5 and 10 per hectare on the large map, and between 10 and 20 per hectare on the inner map. Lower densities are shown as white.
  • In 2011 the ABS changed their statistical geography. I have used SA1s from 2011 as the most comparable area unit to a census collector district, however they are generally smaller and so densities may appear to jump slightly in 2011 in some areas.

See also earlier posts for:


Visualising the changing socio-economic landscape of Melbourne

Sun 29 September, 2013

This post is drifting a little away from transport, but I hope you will find this interesting…

How has the spatial distribution of socio-economic advantage and disadvantage changed over time in Melbourne? (oh, and Geelong too)

The animated maps below are fascinating, but of course there’s lots of important caveats regarding the data.

About the data

Since 1986, the Australian Bureau of Statistics (ABS) has calculated Socio-Economic Indexes For Areas (SEIFA) based on five-yearly census data. These include indexes of relative socio-economic disadvantage (IRSD), and – since 2001 – an index of relative socio-economic advantage and disadvantage (IRSAD). For 2006 and 2011, SEIFA was explicitly designed to measurepeople’s access to material and social resources, and their ability to participate in society” (with similar intent for prior years).

This post looks at the spatial changes over time in these index values. I must be upfront: ABS explicitly cautions this type of analysis. This is mostly because the component census variables that make up SEIFA scores and their respective weightings vary between each census, but also because statistical area boundaries change, the number of areas has increased, and indexes were calculated on usual residents from 2006 onwards (as opposed to people present on census night for 2001 and earlier). ABS also notes that middle range scores are very similar, so time-series analysis should focus more on the top and bottom ends of the spectrum. More discussion on this issue is available from ABS and .id consulting.

However, I’m going ahead noting the above (as readers also should!), on the following basis:

  • The intent of the indexes has not changed over time, although the quality has (perhaps one day ABS will recalculate SEIFA values for previous census using better measures where possible)
  • I’ve used percentile ranks within Victoria to get around the issue of the changing meaning of particular index values (although this might cause some issues if there has been a relative difference in changes between Melbourne and regional Victoria)
  • I’ve included a summary of the component variables that have changed between censuses (documentation is available from 1996 onwards)
  • I’m mapping this at a metropolitan scale with a view to looking at regional variations, rather than very local changes. In the following maps you’ll see fairly strong regional patterns
  • My analysis will focus only on substantial shifts (which have indeed occurred)
  • Excessive caution may mean that we never do any interesting analysis!

Changes in Index of Relative Socio-economic Disadvantage (IRSD)

This index has been available from 1986 onwards.

More significant changes in the make up of this index in recent years include:

  • 2011 added: families with jobless parents
  • 2011 dropped: indigenous persons, renting housing from government authority
  • 2006 added: household overcrowding (replacing multiple-family households), low rent payments, lack of an internet connection, low skill community and personal services workers, people who need assistance with core activities
  • 2006 dropped Elementary Clerical, Sales and Service workers and tradepersons
  • 2006 changed the evaluation of household income to consider ‘equivalised household income’ replacing a number of measures that try to capture income levels relating different household make-up scenarios. It also stopped using gender specific measures of people with certain occupations or unemployed
  • 2001 saw no changes to the included variables from 1996
  • Variables for persons who did or didn’t finish year 12 at school have changed slightly in both 2006 and 2011

check the SEIFA documentation for full details.

Click on this map to enlarge and see an animation of IRSD percentile values for the years 1986 to 2011.

Melbourne SIEFA ISRD

You can see some quite dramatic changes over time. Two big trends of note are:

  • Most inner city suburbs have gone from being some of the most disadvantaged to much less disadvantaged. It’s hard to imagine suburbs such as South Yarra and East Melbourne as being highly disadvantaged, but the data suggests that was the case in the 1980s. During this transformation, pockets of high disadvantage have remained, probably reflecting older government housing estates. There appears to have a been a fairly large change between 1986 and 1991. This could represent dramatic demographic change and/or reflect changes in the calculations of SEIFA index values.
  • Areas with the highest disadvantage have generally shifted away from the city centre (including some middle suburbs such as Carnegie), perhaps reflecting the growth in high-end CBD jobs driving the attractiveness of near city living.
  • New urban fringe growth areas often begin with low levels of disadvantage, but have become more disadvantaged over time. This is particularly evident in areas such as Hoppers Crossing, Werribee, Melton, Deer Park, Craigieburn, Keysborough, Karingal, Epping, Hampton Park, Cranbourne, Altona Meadows and Keilor Downs. Perhaps this is because when these areas were initially settled there were many double-income-no-kids households that now have more kids and less income? It could also be a reflection of a turnover in the resident population.
  • The maps only show geographic units with a population density of 5 per hectare or more, so you can also see the urban growth of Melbourne (more on that in a upcoming post).

Changes in Index of Relative Socio-economic Advantage and Disadvantage (IRSAD)

This index was first calculated in 2001 and aims to also measure advantage, not just factors that suggest disadvantage. In 2011 it included all but one of the IRSD variables, plus a number that describe levels of advantage (eg high income, higher education, occupations such as managers and professionals, high rent or mortgage payments, spare bedrooms).

The component variables of IRSAD have changed in line with the changes to IRSD, plus some other variables:

  • 2011 added people with occupation classed as managers, houses with spare bedrooms, households with 3 or more cars
  • 2006 added people paying low/high rent, high mortgage payments, renting from government authority, households with no car, households with broadband internet connection (replacing persons using the internet at home)

Again, check the SEIFA documentation for full details.

An aside: SEIFA associates higher car ownership with advantage, but I suspect some inner-city types might consider not needing to own a car an advantage.

Here is an animation of the Index of Relative Socio-economic Advantage and Disadvantage for years 2001 to 2011.  Again, click to enlarge and see the animation.

Melbourne SIEFA ISRAD

The changes between 2001 and 2011 are much less dramatic, probably because of the shorter time span. Some observations:

  • The Melbourne CBD drops in 2011 – possibly because of a change of demographics (more students?) and/or a change in the component variables.
  • Many parts of the middle eastern suburbs (particularly the Whitehorse area) appear to drop from the upper to the middle percentiles in 2011.

What’s also interesting to see is some socio-economic fault lines in Melbourne, such as:

  • Altona North versus South Kingsville/Newport (north-south divide along Blenheim Road/Hansen Street/New Street)
  • Skeleton Creek between Point Cook (including Sanctuary Lakes) and Altona Meadows
  • A north-south line being the boundary between the Shire of Melton and the City of Brimbank in the north-western suburbs
  • Along Hume Drive / Lady Nelson Way (an east/west line in northern Brimbank)
  • Greenvale versus Meadow Heights (split by the proposed north-south Aitken Boulevard)
  • A north-south divide through Heidelberg Heights, roughly parallel to the Hurstbridge rail line
  • Along the Dingley Arterial between Dingley Village and Springvale

How different are IRSAD and IRSD values?

IRSAD contains a lot more variables and uses different weightings. See the ABS website for full details.

For those who are interested in the correlation between the two, here’s a scatter plot for both 2006 and 2011 data comparing the two index values (as percentile ranks) for all CDs and SA1s (respectively) in Victoria:

SEIFA IRSD v IRSAD v2

You can see the relationships between the two indexes is stronger in 2011 (R-squared = 0.96) versus 2006 (R-squared = 0.89). This might reflect the make up of the variables in each year and/or the smaller geographic units in 2011 (SA1s) which may reduce diversity within each geographic unit.

I’m sure others could spot other interesting patterns, and/or offer explanations for the changes over time (comments welcome).


A detailed look at changes in Melbourne residential density 2006-2011

Mon 8 July, 2013

Since my first post looking at 2011 Melbourne residential density, there’s been a heap of new 2011 census data released. This post includes new maps showing Melbourne’s population density in maximum detail, as well as some more calculations of Melbourne’s urban/residential density for the density nerds.

Melbourne’s residential density in extremely high resolution

2011 population figures are now available for mesh blocks – the smallest ABS geographic unit. This allows a fine-grained look at 2011 residential density, and comparisons with 2006 as we now have a time series.

Here’s a very large animated map (4.7MB, 6825 x 4799 pixels) showing residential density at mesh block level for 2006 and 2011. You’ll need to click on it to download and see the animation (I’d suggest a new tab or window). Use your browser to zoom in and scroll around to areas of interest.

Melbourne mesh block density

 

[update 10 July: It has been brought to my attention that some people are unable to view this map because they are restricted to using certain versions of Internet Explorer. If you cannot see the large map above, I have also created a smaller animated map showing only the inner areas of Melbourne]

You can see that new growth areas on the fringe actually have relatively high densities, contrary to conventional wisdom. I also note a relatively high and increasing density in the Springvale/Keysborough/Noble Park area, quite some distance from the CBD. If you look carefully you will also spot infill developments like Waverley Park, Parkville (ex-Commonwealth Games village), Gresswell Hill in Macleod, Docklands, Maidstone, Edgewater estate in Maribyrnong, along St Kilda Road, Waterways, and no doubt many more.

More values for the urban/residential density of Melbourne

Okay, you might want to stop reading here unless you have a deep interest in density calculation methodology.

Along with mesh blocks, the recently released census data provides boundaries for urban centres and localities, which each representing a relatively continuous urban area (including residential and non-residential land). There is an urban centre of “Melbourne” defined, which excludes the satellite urban centres of Pakenham, Melton, Sunbury, Healesville and towns along the Warburton Highway, but includes the major urban regions along the Mornington Peninsula to Portsea and Hastings.

All this new data enables calculation of yet more values of the urban/residential density of Melbourne, adding to my previous list (some of which I have repeated for comparison purposes). The areas covered by each calculation are shown on the map below.

Geography Area 
(km2)
Population Average density 
(pop/ha)
Areas on map below
“Greater Melbourne” Greater Capital City Statistical Area 9990.5 3,999,982 4.0 white + yellow + green
SA1s within Greater Melbourne with population density > 1 person/ha 2211.4 3,903,450 17.7  (not shown exactly, slightly less than yellow + green)
Mesh blocks within Greater Melbourne, with population density > 1 person/ha 1713.1 3,913,215 22.8  yellow + green
Mesh blocks within Greater Melbourne, with population density > 5 person/ha 1348.5 3,824,999 28.4 green
Melbourne urban centre 2543.2 3,707,530 14.6 all within blue boundary
Mesh blocks within Melbourne urban centre, with population density > 1 person/ha 1443.8 3,696,316 25.6 yellow + green within blue boundary
Mesh blocks within Melbourne urban centre, with population density > 5 person/ha 1238.3 3,642,685 29.4 green within blue boundary

I note that the Melbourne urban centre is approximately a quarter of the area of “Greater Melbourne”.

Here’s a reference map of Melbourne showing the Greater Capital City Statistical Area, Statistical Division and Urban Centre boundaries of “Melbourne”, together with mesh blocks of above 1 and 5 persons/ha.

Density area scope map mesh blocks2

Finally, for the density nerds who are still reading this post, I have calculated the 2011 population-weighted density of Greater Melbourne using mesh blocks to be 42.8 persons/ha, which is much higher than the population-weighted density using SA1 geography of 31.8 persons/ha. It’s higher because more non-residential land parcels have been excluded from the overall calculation. If I restrict myself to mesh blocks within the Melbourne urban centre, the population-weighted density is only slightly higher at 45.1 persons/ha.

So if you want to compare population-weighted densities of different cities, you’ll need to make sure you are using equivalent geographic units, which I suspect would be very difficult for international comparisons. An attempt at Australian and Canadian city comparisons was made in the comments section of a previous post.

There you go. Next time someone claims to know the urban density of Melbourne, you can now argue with them for hours about whether you agree with their number and how it should be measured.