Great Britain – CityGeographics

Pandemic Geographies and Challenges with the 2021 England & Wales Census Results

August 16, 2022December 15, 2022Posted in City Planning, Housing, London, MappingTagged census, Census 2021, comparative urbanism, demographics, Great Britain, Housing, LondonLeave a comment

The Census is the most comprehensive demographic survey in the UK, providing detailed data for government and researchers in many fields, from health and education, to planning and transport. The 2021 Census has a unique context, as the 2021 census day (21st March 2021) occurred when the UK was still in the 3rd national lockdown which began on the 6th of January 2021. The lockdown will likely have various impacts on the census results, particularly on groups who may have changed their residence during lockdown, such as students (many of whom were studying remotely) and employees in the hardest hit sectors, such as retail, arts and hospitality.

The issue is not that the census will be inaccurate per se (indeed the Census has a very thorough survey methodology) but rather that the period in time captured of March 2021 will have aspects unique to the pandemic. These aspects are likely to be temporary as society returns to something more like normality in 2022 and beyond. While Scotland chose to delay its 2021 census for a year (which may prove to be a sensible decision), researchers in England and Wales will need to be make the most of the 2021 results and be made aware of any unusual aspects.

At present only the early population results have been released for the 2021 Census, so more detailed breakdowns of population groups will have to wait for further releases later this year. The following analysis compares the Census 2021 local authority totals to the ONS mid-year population estimates for 2020 to check how the census population results compare to the next most recent population estimate.

The differences between the 2020 data and 2021 Census are likely to reflect several factors-

The higher accuracy of the census methodology. The ONS mid-year estimates can have some errors due to limited data on some groups, such as international migrants, which are better represented in the census. Potentially Brexit could have increased the degree of error in the mid-year estimates, given changes in international migration.
Temporary pandemic changes to places of residence. These could include for example students working remotely from home during term time (including international students not coming to the UK), younger populations returning to live with parents as jobs furloughed/ended/changed to remote working, and wealthier residents choosing to live in second homes.
Longer term pandemic changes to residential preferences. This could reflect changing residential preferences towards larger houses with more space/gardens following a dramatic rise in remote working during the pandemic.

Right now the extent of these different factors is not known, and it is very difficult to separate them without more analysis and data. So the following discussion is speculative in nature.

Comparing the Census 2021 Populations to the 2020 ONS Mid-Year Estimates
The map below shows the percentage differences between the 2020 mid-year population estimates, and the 2021 Census. Blue areas show where the census 2021 population is lower than the 2020 estimates, and red areas where the census 2021 population is higher than the 2020 estimates. The differences are substantial. In South East England there is a strong geographical pattern with Inner London populations down dramatically (Camden and Westminster both have 24% lower populations in the census results). London as a whole has a population of 8.8 million in the 2021 census, which is 200k lower than the estimated 2020 total. In contrast, commuter towns and the home counties surrounding London have distinctly higher populations of around 5-10%. This pattern very much looks like a pandemic geography of Inner London residents leaving during the lockdown. Analysis by the GLA using PAYE income data confirms this general conclusion, and also points to this population drop being concentrated in young adults (note also the GLA analysis shows this population largely returning to Inner London by 2022). It is possible however that other factors such as post-Brexit emigration and very high rents are also reducing Inner London populations, and could have produced errors in the 2020 mid-year estimate data.

It is not just in the South East where there are differences between the 2020 and 2021 data. The South West and the Midlands are also areas where generally 2021 Census populations are higher than the 2020 data. The higher populations are mainly in more rural authorities, as well as some urban areas including Leicester, Lincoln, Derby, Worcester and Swindon, while Coventry and Nottingham have lower 2021 populations (university related?). There is no simple pattern here, and there are likely some 2020 mid-year population errors here in addition to any pandemic related changes. There also appear to be higher populations in areas within 1-2 hour journey times to London, possibly linked to changing residential preferences following the rise in flexible working.

North-West England has a mixed pattern with higher census populations in Cheshire to the South and in Burnley, but not in central Manchester or Liverpool. In Yorkshire and Humberside, Leeds and Hull have higher populations in the 2021 Census, while Sheffield is lower. The North East and Wales generally have a much closer alignment between the 2020 and 2021 data. The higher than expected populations in many rural and smaller town authorities fits with pandemic related patterns, but the mixed picture for many cities implies that the situation is complex, and may include both pandemic changes and errors in the 2020 data.

London and the South East
As mentioned above, the 2021 Census data for London and the South East does look to have been significantly influenced by the pandemic, with much lower than expected populations in Inner London, and higher populations in towns surrounding Greater London, and those with longer distance rail connections, such as Peterborough, Milton Keynes and Reading. We can look in more detail at some of these patterns.

As well as higher populations in commuter towns surrounding London, there are also higher population results recorded in the Outer West London boroughs of Ealing and Hounslow. This is quite an outlier compared to the rest of Greater London, and it is not clear why pandemic or mid-year population error factors would affect these boroughs in particular. In relation to the student population argument, it is interesting that both Oxford and Cambridge have higher than expected 2021 Census populations, likely because Oxbridge colleges insisted on students being on campus in 2021, and likely because the 2020 data has underpredicted wider population increases.

The big question on the geography of the South East is to what extent these pandemic related changes are a temporary lockdown phenomena, or may relate to longer term trends in residential preferences. The analysis by the GLA using PAYE data pointed to the population decreases in Inner London being a short term trend for younger adults, which in turn could have pushed up populations in the wider South East in 2021. However, an argument can also be made that some of the patterns observed fit trends of households looking for more spacious residences, and adapting to flexible working patterns that do not require daily attendance at the office. Areas beyond 1 hour travel to London with more affordable housing become much more attractive in this context (and have seen big house price increases). The map above shows a ring of local authorities surrounding London with higher than expected populations in 2021 that stretches beyond the South East into the Midlands and South West. We will need to wait for more data to see whether this is a trend beyond the immediate residential changes during the pandemic.

Age Profile Comparison, 2011 and 2021
In the comparison above, it is very difficult to separate out errors in the mid-year estimates from genuine population changes. Another approach is to look at the age profiles in 2011 and 2021 for those areas with significant population differences in the 2021 census. Firstly for Inner London boroughs with lower than expected populations, you can see very clearly in the charts for Westminster and Camden that the lower populations are focussed on younger adults, 20-40. This fits with the temporary pandemic residential changes argument. There are however other factors aside from the pandemic, such as increased rents and post-Brexit visa issues, that could also lower the population of younger adults.

For London as a whole, there is a modest drop in the population in their 20s, and increase in nearly all other age groups, with the average age increasing overall. The comparison between the 2020 population data with the 2021 census above did not pick up unexpectedly lower populations in other large English cities apart from London. Looking at other English cities in terms of age profiles, generally there does not appear to be this fall in the proportion of younger adults. Leeds is a fairly typical example shown below. Manchester on the other hand has a pattern a bit more like London, and perhaps this signals more pandemic related changes here, or maybe more similarity to London in terms of international migration.

Turning to those cities with higher than expected population increases in the 2021 census, we can also look at their age profiles. The examples below of Peterborough and Milton Keynes show really big increases in populations in their 30s and to a lesser extent 40s. Many of these households will have kids, and so there are similar jumps in the population of young children (though this does not appear in the age 0-4 group). This pattern looks very much like these towns are attracting families looking for more affordable housing, and the 2020 data has underestimated this trend. It is possible the pandemic has further encouraged this, but it looks overall like a longer term trend. Note that other towns growing rapidly in the South East such as Reading and Bedford has similar age profile charts (as does Ealing in London). The big outlier is Cambridge, where the population increase is geared more towards adults in their 20s.

Summary
This analysis has found some significant differences between the new 2021 census data, and mid-year population estimate data from 2020. It is very difficult to know whether this is due to errors in the 2020 data, or alternatively pandemic factors affecting the population in March 2021. Some of the biggest differences are in London, and it does appear that London experienced a drop in the younger adult population during the pandemic, particularly in Inner London. Manchester also has signs of a similar trend. GLA analysis indicates this drop was temporary in London, though there are longer term factors such as high rents which could also be playing a role.

Another big difference between the 2020 and 2021 data is much faster growth in many towns and small cities in the South East. Places like Milton Keynes and Bedford have growth of around 17% between 2011 and 2021. The age profile data shows this is driven mainly by adults in their 30s and 40s, often with children. The population differences look more like errors in the 2020 data here, though it is possible that the pandemic has accelerated families moving to more affordable towns to purchase larger housing.

Overall is not straightforward to separate out errors in the ONS mid-year estimates from pandemic changes, or to separate temporary pandemic changes from any longer term trends that are emerging. When the full data is released it will likely be possible to filter out certain demographics (e.g. students, younger populations) more affected by the pandemic. But it does look like the census 2021 data is going to be less certain than usual, particularly for London, and maybe for other large cities. Given that the census is traditionally used as a basis for investment in public services, more caution will be needed when using the 2021 census results (indeed London Councils have already responded that the 2021 census is underpredicting London’s population).

Table of Local Authorities with Greatest Increases Between 2020 ONS and 2021 Census Populations

Name	2011 Census Population	2020 Mid-year Population	2021 Census Population	Population Change 2011-2020	Population Change 2011-2021	Difference Between 2020 ONS and 2021 Census
Cambridge	123867	125063	145700	1.9	17.6	16.5
Reading	155698	160337	174200	3.2	11.9	8.6
Ealing	338449	340341	367100	0.3	8.5	7.9
Oxford	151906	151584	162100	0.9	6.7	6.9
Harlow	81944	87280	93300	6.2	13.9	6.9
Peterborough	183631	202626	215700	9.8	17.5	6.5
Milton Keynes	248821	270203	287000	8.1	15.3	6.2
Bedford	157479	174687	185300	10.7	17.7	6.1
Hounslow	253957	271767	288200	6.6	13.5	6.0
Cherwell	141868	151846	161000	6.7	13.5	6.0
Burnley	87059	89344	94700	2.7	8.8	6.0
Slough	140205	149577	158500	6.3	13.0	6.0
Watford	90301	96623	102300	6.6	13.3	5.9
Rushmoor	93807	94387	99800	0.0	6.4	5.7
Luton	203201	213528	225300	4.9	10.9	5.5
Crawley	106597	112474	118500	5.1	11.2	5.4
Swindon	209156	222881	233400	6.3	11.6	4.7
West Northampton.	375101	406733	425700	8.2	13.5	4.7
Merton	199693	206453	215200	2.9	7.8	4.2
Basingstoke and Deane	167799	177760	185200	5.5	10.4	4.2
Leicester	329839	354036	368600	7.4	11.8	4.1
Pendle	89452	92145	95800	2.9	7.1	4.0

Table of Local Authorities with Greatest Decreases Between 2020 ONS and 2021 Census Populations

Name	2011 Census Population	2020 Mid-year Population	2021 Census Population	Population Change 2011-2020	Population Change 2011-2021	Difference Between 2020 ONS and 2021 Census
Camden	220338	279516	210100	27.0	-4.6	-24.8
Westminster	219396	269848	204300	22.9	-6.9	-24.3
City of London	7375	10938	8600	47.6	16.6	-21.4
Islington	206125	248115	216600	20.3	5.1	-12.7
Coventry	316960	379387	345300	19.7	8.9	-9.0
Kensington and Chelsea	158649	156864	143400	-0.9	-9.6	-8.6
Hackney	246270	280941	259200	13.7	5.3	-7.7
Richmondshire	51965	53732	49700	0.8	-4.4	-7.5
Tower Hamlets	254096	331969	310300	29.7	22.1	-6.5
Kingston upon Thames	160060	179142	168000	11.7	5.0	-6.2
Gwynedd	121874	125171	117400	3.0	-3.7	-6.2
Isles of Scilly	2203	2226	2100	0.1	-4.7	-5.7
Canterbury	151145	166762	157400	10.7	4.1	-5.6
Sheffield	552698	589214	556500	6.8	0.7	-5.6
Brighton and Hove	273369	291738	277200	6.9	1.4	-5.0
Newcastle-under-Lyme	123871	129610	123300	4.6	-0.5	-4.9
Guildford	137183	150352	143600	9.3	4.7	-4.5
Blaenau Gwent	69814	70020	66900	0.3	-4.2	-4.5
Nottingham	305680	337098	323700	10.9	5.9	-4.0

Graduate Mobility and Closing the Productivity Gap for UK Cities

April 11, 2016April 11, 2016Posted in Economy, MappingTagged economy, Flows, Great Britain, higher education, PolicyLeave a comment

There has been much discussion in recent years about the UK ‘productivity puzzle’: the shortfall in productivity between the UK and comparable EU states like Germany and France, with this gap widening in the last decade. One important perspective for understanding productivity relates to skills and education, and how well graduate skills are integrated with businesses and are helping to expand knowledge economy industries. This is where the UK has a distinct advantage due to the high number of world leading universities across the country. Yet this strong higher education base is not currently translating into sufficient numbers of productive graduate jobs in the UK.

The Foresight Government Office for Science has been investigating this topic, and recently published the Future of Cities: Graduate Mobility and Productivity report. I contributed to the report with data analysis on graduate flows from higher education institutions to workplaces using HESA data from 2013/2014.

There are several interesting aspects of the Foresight report. Firstly there is a strong city focus, which is vital when you see that productivity is highly city dependent, and has close links with regional patterns such as the north-south divide in the UK.

Productivity (Gross Value Added(GVA) per person employed) across British cities, 1981 and 2011 (Source Martin, Gardiner and Tyler 2014) — Productivity (Gross Value Added(GVA) per person employed) across British
cities, 1981 and 2011 (Source Martin, Gardiner and Tyler 2014)

The productivity gap at the city level is further linked to graduate flows. London dominates the UK as a graduate employer, both in absolute terms and in proportional flows from higher education institutions to workplaces. The scale of the labour market and graduate recruitment programs in London, as well as its reputation as an ‘escalator region’, all add to this huge reach.

LondonPropFlows_02 — Data HESA Destination of Leavers Survey 2013/2014

That is not to say however that other large city-regions do not also have significant national graduate flows. Birmingham, Leeds and Manchester all draw significant numbers of graduates, with respective strengths in industries such as advanced manufacturing, creative industries and financial services (note HESA data is at county level, with Birmingham part of West Midlands and Leeds part of West Yorkshire). This is the foundation on which future growth will build.

ManchesterPropFlows_01 — Data HESA Destination of Leavers Survey 2013/2014

WestYorkshirePropFlows_01 — Data HESA Destination of Leavers Survey 2013/2014

WestMidlandsPropFlows_01 — Data HESA Destination of Leavers Survey 2013/2014

A second interesting aspect of the Foresight report is that it has been produced in collaboration with regional and local government agencies in Birmingham, Manchester, Leeds, Liverpool, Bristol and Cardiff. There are a number of initiatives in development to address key aspects of graduate employment, including:

• The Skills Engine being developed in Birmingham brings together a network of key players from the local area in order to improve the matching of demand for and supply of talent in the local economy.

• FASTTRACK is an initiative being tested by Leeds University to attract and assist graduate integration into small and medium-sized businesses in the region through placements and specially designed induction and training programmes.

• The Graduate Business Lounge builds on Bristol’s existing engagement in student enterprise to integrate existing graduate enterprise service providers and platforms to foster greater student entrepreneurship.

• New Economy Hubs in Birmingham, Liverpool and Manchester will take a multi-sector approach to understanding key economic growth areas at the city regional level.

• The GRAData Project, working with Leeds City Council and Leeds Institute for Data Analytics, aims to improve university and council use of national graduate data. The hope is that this will improve local careers support for students, and illuminate graduate mobility to enable the development of regional talent strategies.

These cities are well aware of the challenges in graduate skills and recruitment, and recent devolution processes are providing opportunities for improving graduate employment offers and addressing regional economy issues more generally. Data analysis and policy support are important is this role, with organisations set up such as New Economy Manchester and the University of Birmingham City REDI institute expanding.

For more details on the Foresight research, read the report here, and it is also worthwhile exploring the wider Foresight Future of Cities page.

Exploring the Users of Interactive Mapping Platforms

November 20, 2015March 11, 2016Posted in Mapping, VisualisationTagged Great Britain, interactive mapping, research impact, VisualisationLeave a comment

CASA and UCL Geography have substantial experience in developing online interactive mapping sites for research outreach. The purpose of these tools is to take spatial analysis and visualisation outputs from the research lab and make them accessible and useful for many users from a wide variety of sectors and backgrounds, including: wider academia, central and local government, built-environment professionals, business, technology, community groups and the general public. Interactive mapping tools are part of the movement to make science and research more accessible, supported by the main UK research funding bodies as well as specific campaign movements like Open Data and Open Science.

The positive media coverage of recent projects and our communications with users has indicated that interactive mapping sites do reach a wide audience, including various expert users as well as the general public. These mapping projects are however a relatively new set of tools, and there is a lack of detailed information and evidence on who is using interactive mapping sites and the degree of research impact that they can deliver. In this post I explore two recent interactive mapping projects, DataShine.org.uk & LuminoCity3D.org, and analyse who has shared these sites using data from Twitter. This method is not without its flaws as described below, but is an early attempt to gather evidence and understand the user base.

‘Engaged’ Users and Social Media Sharers
A well designed interactive mapping site can generate a lot of hits, particularly if it gets picked up by national media sites. DataShine generated a huge 99,000 unique users in its first three months after launch in June last year, while LuminoCity had a reasonably large 24,000 unique users in its first three months from September 2014.

How many of these hits are truly engaged users? We can approach this question in terms of web statistics. On the LuminoCity site during the first three months, 16% of users made at least one return visit; 18% of users stayed for at least three minutes; and 26% of users explored at least four different maps during their session. So we can estimate that around 20% of the total users are exploring the site in some depth. That’s not a bad return where there is a high number of total users, e.g. this would equate to 19,800 people for the first three months of DataShine, and 4,800 people for the LuminoCity site.

We do not know however who these users are. Are they mainly interested members of the general public? Are they expert professional users? This is harder to gauge.

Classifying Twitter Users
We do have further information about the most engaged group of users- the social media sharers. These are the people who actively promoted the site to their network of followers/friends. The two major social media sites are Facebook and Twitter, with 4% of visitors of both DataShine and LuminoCity either sharing/liking the site on Facebook or posting the link on Twitter in the first three months. This is a high proportion of social media sharers, and reflects the novel and accessible nature of the sites which helped to generate enthusiastic users.

In this analysis I have classified Twitter users who shared site links to Datashine and LuminoCity according to their profession. Naturally there are some problems with this approach- this selection reflects only the most enthusiastic users of the mappings sites; Twitter users are a biased sample (generally towards affluent professionals, tech and media users); many users have multiple professions (I tried to pick the main one); and professional and personal opinions on Twitter overlap significantly. However this is an early effort to explore types of users of interactive mapping sites, and hopefully this can be built on in the future.

The DataShine Census Site
Below is the classification of 350 Twitter sharers from the DataShine site. It is clear that a wide variety of users are covered, including both professional and community groups (a more detailed table is at the end of the post)-

Geographers were not surprisingly the main group of academic users, but DataShine also attracted many users from across the natural sciences, social sciences and the humanities. Health researchers were particularly well represented, as the site provides many useful health related maps from the 2011 census. This result also chimes with a high number of business users in the public policy sector, mainly with a health and planning focus.

The innovative visualisation technology behind the DataShine site appeals to IT users, and there were many sharers from IT, cartography, data journalism and data science backgrounds.

One of the biggest successes with the DataShine site was in reaching beyond academic and professional experts to local communities. The site provides high quality maps of census data at the neighbourhood level, and this successfully appealed to local community groups, campaigners (e.g. cycling campaigns, local environment campaigns) and to local government users. Several councillors tweeted the site, as well as users from DCLG and local government planners. Media coverage also helped to generate many interested users from the general public.

The LuminoCity Site
The data from the LuminoCity site is based on a smaller sample of 140 Twitter shares. This covers a similarly wide variety of users, with more of a focus on built-environment professionals, and less on local government and the general public.

The LuminoCity site provides a range of maps and statistics for the comparative analysis of UK cities. This functionality appealed strongly to planners and transport consultants, as well as some business users in economic development and real estate. Academic users also had a more urban focus for the LuminoCity site. The site did not chime so strongly with local government and community users who generally want a more local scale of analysis. There were some users from Central Government who used the site for measuring economic performance in northern cities.

The more abstract minimalist aesthetic used on the LuminoCity site attracted quite a few architects and designers to the platform. These users are enthusiastic about visualisation while being less familiar with the range of open data available at city and national scales.

The ‘Other Education’ sector, which was popular for both sites, includes high schools, geography departments, museums and the wider education sector beyond universities. This was an unexpected outreach success for both of the websites, and shows how the open approach can help to create new connections.

Summary
This analysis of twitter shares from interactive mapping platforms shows how these tools can successfully appeal to a wide range of users, both professional and the general public. Academics are well respresented, but also business users, government, local communities and the wider education sector.

Twitter users are inevitably a biased sample and it would be useful in the future to look at methods that can capture a larger proportion of engaged users and assess to what extent the most engaged social media users represent the wider engaged audience for the sites.

Full Tables of Twitter Sharers

DataShine Twitter Sharers Classification

Sector	Sector Percentage	Group	Group Percentage
Academic	18.4	Geographer / Urban Academic	3.8
		Other academic	11.4
		Social Science Org	0.9
		Student	2.3
Other Education	5.8	Geography Education	1.8
Other Education	5.8	Other Education / Museum	4.1
Built Environment Professional	7.0	Transport Consultant/Planner	2.0
		Architect	1.2
		City Planning/Housing Org.	3.8
Business	9.6	Economic development	0.0
		General Business / Marketing	6.1
		Public Policy	3.2
		Real Estate	0.3
Design & Journalism	8.2	Design- graphic, interactive	2.3
		Data Journalism Specialist	1.8
		Journalist General	4.1
IT	16.7	Cartography & GIS exp.	4.7
		IT / Tech General	9.1
		Data Scientist	2.9
Government	7.3	Central Gov	1.8
		Local Gov	3.8
		Open Data	1.8
Local Community & Charity	8.8	Community / Place Activist / Charity	8.8
General Public	18.1	General Public	18.1

LuminoCity Twitter Sharers Classification

Sector	Sector Percentage	Group	Group Percentage
Academic	19.4	Geographer / Urban Academic	8.1
		Other academic	7.3
		Social Science Org	1.6
		Student	2.4
Other Education	7.3	Geography Education	4.8
Other Education	7.3	Other Education / Museum	2.4
Built Environment Professional	16.9	Transport Consultant/Planner	4.8
		Architect	4.0
		City Planning/Housing Org.	8.1
Business	10.5	Economic development	3.2
		General Business / Marketing	6.5
		Public Policy	0.0
		Real Estate	0.8
Design & Journalism	12.1	Design- graphic, interactive	7.3
		Data Journalism Specialist	2.4
		Journalist General	2.4
IT	18.5	Cartography & GIS exp.	5.6
		IT / Tech General	8.1
		Data Scientist	4.8
Government	3.2	Central Gov	1.6
		Local Gov	0.8
		Open Data	0.8
Local Community & Charity	3.2	Community / Place Activist / Charity	3.2
General Public	8.9	General Public	8.9

Britain’s Fracturing Political Geography

May 5, 2015October 20, 2015Posted in PoliticsTagged CASA, clustering, Great Britain, percolation, political geographyLeave a comment

[Post co-authored with Carlos Molinero]

The imminent UK General Election is fascinating for a host of reasons, not least because of the challenge to the long established dominance of the two main parties, Conservatives and Labour. Their share of the vote has been steadily in decline for over 50 years, from a high of 97% in 1951 to 65% in 2010-

Polls for 2015 indicate that the two main parties are tied at around 33-34%. But the difference in 2015 is that the rise of the smaller parties is going to translate into winning seats, most spectacularly in Scotland with the SNP set to wipe the floor and become the third biggest party in the UK with 50+ seats. There are also likely to be gains for the right wing party UKIP, and possibly for the Welsh nationalists Plaid Cymru and the left wing Green Party. The political map of Great Britain will look very different and increasingly fractured, with a coalition or minority government inevitable and essentially becoming the new normal-

Prediction2015_May2015Guardian — 2015 General Election predictions from May2015.com (left) and Guardian (right) in cartogram format.

How can we understand this changing political geography? There is a strong tendency towards spatial clustering of similar voting patterns, with votes for minor parties higher further away from the economic and political core of London. This relates to the nations of Scotland, Wales and Northern Ireland but also to regions like South West England and coastal towns where UKIP and the Greens could pick up seats. There is also a strong geographical element to the division between Labour and Conservative seats, with Labour strongly urban and northern while Conservatives are dominant in more rural areas and in the South East.

In research at CASA we have been using percolation as a method of exploring urban regions at multiple scales, and have a new paper applying percolation to understanding Britain’s political geography (paper by Carlos Molinero, Elsa Arcaute, Mike Batty and myself). The paper proposes that voting patterns are fracturing along long-standing historic national and regional divisions in Great Britain, and seeks to test this proposition using percolation analysis. The percolation method defines regions by building clusters of road junctions according to a threshold distance, with the road network used as a proxy of population settlement and connectivity. At a threshold distance of 5km Great Britain is one giant cluster-

We can then reduce this threshold distance to see how Great Britain fractures. At a threshold distance of 1.4km Scotland fractures from England & Wales (although interestingly some of the Scottish borders remain part of the England & Wales cluster). Then at a distance of 900m the North and South of England split, as does the North East of England and North East of Scotland-

By 800m South Wales splits off from England, and the South West and East Anglia become separate regions. Finally at a distance of 300m, we are left with the core of large cities-

These various levels of percolation clusters can be viewed as a tree (below).

Our question is then, do these regions generated through percolation analysis bear any relationship to voting patterns? We can test this by classifying parliamentary constituencies according to the composition of percolation clusters that fall within each constituency. Each of the parliamentary constituency groups is assigned an ‘average voting behaviour’ from the real voting behaviour in 2010, in terms of a vector of percentage votes for each of the parties. The average voting behaviour of each group can be compared to the real voting behaviour in terms of the percentage error. We can compared the percolation clustering outcomes against results using different datasets. Clusters created using the real voting data naturally produce the lowest error. It is interesting however that the percolation based results outperform clusters produced using common socio-economic data such as socio-economic class, age and education level.

Making Predictions for 2015
Finally the percolation clusters can also be used to try to make predictions about the forthcoming election using a universal swing method on the 2015 data (for full details see the paper). In the series of maps below we have (from left to right) the prediction using the real 2010 data and latest polls; the prediction using percolation clusters and occupational class data; the prediction using only percolation clusters; and the prediction using only socio-economic class data. The percolation based results appear relatively close to the prediction based directly on the real data. The percolation method is highly clustered spatially, leading to an exaggeration of regional divisions in the UK-

In terms of the total seats predicted, the results are not too far off current polling predictions. The percolation based method tends to exaggerate Labour’s predicted number of seats, as Labour benefit from a strong clustering of their vote in northern city-regions.

Overall the percolation method is very a promising approach for understanding regional divisions in the UK, and we continue this line of inquiry in further research. It remains to be seen whether the political geography of the UK will continue to fracture further along these regional lines. A key factor will be whether the rise of smaller parties raises the pressure for voting reform, as the First Past the Post System is becoming increasingly misrepresentative of the UK’s voting patterns and is failing to deliver the single party majority that is supposed to be the FPTP system’s main asset.

Uneven Growth, Devolution and Urban Futures Research in the UK

May 1, 2015October 20, 2015Posted in EconomyTagged devolution, economy, Great Britain, growthLeave a comment

This post was written for the UCL Big Question Debate on the UK General Election 2015.

The financial crises and recession that began in 2008 were initially viewed as an opportunity for rebalancing the UK economy away from financial services towards a broader base, and addressing Britain’s long term north-south divide. In reality however the post-recession period has seen a strengthening of regional divisions with high rates of growth in London and much of the South East, compared to mixed or negative performance in the rest of Britain (see the map below). While the South East now needs to tackle the knock-on effects of growth in terms of the severe housing shortage, many regions in the UK have been struggling to achieve growth at all.

City devolution policies are aimed at boosting growth in northern cities and narrowing regional disparities. The 2015 general election is unique for the prominence of these policies, with devolution manifesto commitments from all the major parties. The Conservatives would continue their programme of devolving some powers and budgets to specific northern cities, while Labour and the Lib Dems would legislate for more comprehensive city devolution. Are these policies likely to work? There is currently much debate and uncertainty over this question. I argue here that urban research can help us understand current trends in cities and the directions urban futures are likely to take.

Firstly we need to understand the continuing structural changes in the economy. Economic growth is being led by professional and business service jobs, so-called ‘knowledge economy’ sectors (see graph below). Despite zero growth in financial services jobs over the last 15 years, professional and business services continue to grow substantially led by sectors such as ICT, management consultancy, creative industries, legal and real estate. Other service sectors are more mixed, with a decline in administrative jobs, and some growth in retail and public services. Meanwhile manufacturing continues to be in decline, though has levelled off in the last five years.

The economic picture illustrated above is one that significantly favours cities and city-regions. Knowledge economy firms benefit from clustering together, sharing labour markets, knowledge spill-overs and other externalities. These agglomeration economies are strongest in cities, and strongest of all in large cities, where the density of transport and communications infrastructure facilitates connections and reduces costs. An expanding academic literature describes how larger cities are on average more innovative, competitive, diverse and sustainable, backed up with empirical evidence mostly from the USA. This line of reasoning chimes with the strong economic performance of London in the UK, and explains how the capital has been able to bounce back from the recession through its diverse economic base.

Yet in research at the Centre for Advanced Spatial Analysis (CASA) we have found that the relationship between city size and economic performance does not hold for Great Britain (see paper). Several small cities are the fastest growing in the country and have become highly specialised in knowledge economy industries, principally cities/towns in the South East with universities such as Milton Keynes, Cambridge and Brighton. Meanwhile the major post-industrial cities, such as Birmingham, Manchester, Liverpool, Leeds and Newcastle are underperforming given their relatively large size.

Are these northern cities capable of faster growth and developing stronger knowledge economy clusters? Recent regeneration in cities such as Manchester would suggest yes, and indeed some green shoots can be seen in the North West and West Midlands in the map above (these two regions are the fastest growing from 2010-2014 after London). Such regeneration does however require significant investment, planning and political collaboration. Thus this is where devolution policies come in. The intention is to give cities more powers for strategic planning, housing, transport and local budgets. More comprehensive devolution proposals allow cities to retain money raised by local taxation. At present the city with by far the most devolved powers is London, with the creation of the mayor and Greater London Authority having positive impacts on development over the last 15 years and helping attract infrastructure spending towards the capital (indeed to an unfair extent- there is a huge UK public investment bias towards London). Would devolution allow other large cities to repeat London’s success, or would fiscal devolution favour existing affluent cities and exacerbate divisions?

Many of these issues around the future of UK cities are being discussed by the Foresight Future of Cities project which UCL is significantly involved in. You can read current Foresight working papers exploring this and many other current urban debates here. We also have a new CASA paper investigating the fracturing political geography of Great Britain.

Overheating London and the Evolving North: Visualising Urban Growth with LuminoCity3D.org

September 27, 2014October 20, 2015Posted in City Planning, Mapping, VisualisationTagged Great Britain, LuminoCity3D, Planning, Urban Form, VisualisationLeave a comment

Urban policy is currently riding high on the UK political agenda. A combination of the desire to rebalance the UK economy away from financial services; debates over massive high-speed rail investment; the worsening housing crisis in the South-East; and city devolution demands following the Scottish referendum, all point to major reform. As we move towards the 2015 general election, addressing city concerns is going to be a key, perhaps even decisive, election debate.

It is therefore a good time to take stock of recent urban growth and change in Great Britain, assess policy successes and failures, and consider how better outcomes might be achieved in the coming decades. This post draws on map visualisations from the LuminoCity3D.org website.

London and the South-East: Global Boom Region to Elite Island?
London’s recent growth has been phenomenal, gaining over a million residents (+13%) between 2001 and 2011. As we can see in the figure below, population growth has occurred across all of Greater London (except Kensington & Chelsea), with the strongest concentrations in Inner London and East London, reflecting the priorities of successive London Plans. This spectacular growth has not been confined to Greater London either, but is found across the South East region. The fastest growing UK towns and cities are nearly all in London’s orbit, including Milton Keynes with 20% growth, Ipswich with 15% growth, Cambridge with 16% growth and Ashford with 21% growth. This shared growth clearly illustrates that the South East is a closely integrated region, as further demonstrated by extensive commuting flows.

LondonSE_PopChange — Population Change 2001-2011 in the South East region.

Inevitably it is strong economic growth that underpins this rise in population. London gained 650,000 jobs (+15%) between 2001-2011, strongly focussed in Inner London and Canary Wharf. Employment growth is much more unevenly spread across the South East, and arguably booming Inner London is taking jobs away from other centres, or pressuring some into becoming dormitory suburbs through soaring demand for housing. This is most clearly seen in Outer London in centres such as Croydon and Bromley where employment has fallen, while resident population has risen.

LondonSE_EmployChange — Employment density change 2001-2011 in the South East region.

Inner London is dominant for many employment sectors, not just financial and business services, but also creative industries, research, tourism, and increasingly for information technology, helping London to bounce back successfully from the great recession. The IT industry is an important growth sector, and has traditionally been concentrated in Reading, Bracknell and surrounding towns, an area dubbed the Western Sector by Sir Peter Hall in the 1980s. The Western Sector still retains the highest percentage of IT jobs in GB, but recent growth here has been sluggish. The current stars of the IT industry are now online and social media businesses, and these are attracted to the creative pull of Inner London. Meanwhile the most significant South East growth story outside the M25 has switched north, with Oxford (12% jobs growth), Milton Keynes (14% jobs growth) and Cambridge (22% jobs growth) forming a new northern arc of science and engineering based growth.

So with so many success stories, you be forgiven for thinking everything looking rosy for London and the South East. Unfortunately this is not the case. Soaring population growth has in no way been matched by new housing construction. What was previously a housing affordability problem in the South East is now an outright crisis that threatens to put the brakes on the entire region. Mean house prices just passed the incredible figure of £500,000 in July of this year, and a recent survey placed London as the most expensive city in the world to live and work. This is a looming disaster for future growth prospects. The crisis is not limited to London either, as shown below, with median prices above £300k for much of the South East, and the most popular cities experiencing similar extremes to London.

LondonSE_HousePrices copy — House prices 2013 in the South East region.

Soaring prices may seem like great news for property owners, but ultimately cities rely on their ability to attract talent and new businesses. And as London’s competitiveness falls, growth will go elsewhere. What has traditionally been a region of opportunity risks becoming a closed-shop for the wealthy.

And the situation is in danger of getting worse before it gets better. The current UK government did not create the housing shortage, but have overseen a period of historically low house building, with 2014 rumoured to hit rock-bottom. Mapping new-built housing sales leaves a sea of white, largely because there have been so few new houses constructed to sell. The recession presented an ideal opportunity for investing in housing and addressing unemployment, but this opportunity was missed. Trumpeted planning reforms have achieved very little, while right-to-buy policies have simply further increased prices.

Solving the housing crisis requires reform on a number of fronts. More power for local authorities to borrow money and make compulsory land purchases would certainly help. Linked to this is a desperate need for property tax reform to encourage housing to be used efficiently. Currently a £300k house pays the same council tax as a £10 million house, while empty housing is not discouraged, leaving many houses in Inner London as empty or underused investment vehicles. Similar arguments are made in favour of a land value tax to encourage land to be used efficiently and stop land banking.

Perhaps the most controversial issue is whether the green-belt can be retained in its current form. Calls from the eminent Richard Rogers that all new development can still be on brownfield frankly look out of touch with the reality in the South East. The debate really needs to switch towards how a controlled release of green belt land can be managed to avoid car-based sprawl and develop sustainable urban areas. Mapping rail infrastructure and urban density in the South East as shown below indicates that there are many potential locations with rail stations and room for growth. This approach would only however create more commuter towns, and ultimately there needs to be stronger planning for the entire South East region, likely with big urban extensions for successful cities such as Milton Keynes, Cambridge and Brighton. It is interesting that recent entries for the Wolfson prize were focussed on this approach.

LondonSE_greenbelt — Rail infrastructure, the green belt and urban density in the South East region

Northern Evolution: an Emerging Hierarchy of Urban Centres?
While the South East is in danger of overheating, the majority of the UK’s city-regions have been focussed on post-industrial regeneration and stimulating growth. And in the last decade there has been significant change for many northern cities. Starting in the North West and Yorkshire we can see rising populations in all the major city centres. Greater Manchester in particular has experienced high levels of growth, gaining 200,000 residents (+8%) and 100,000 jobs (+10%) between 2001 and 2011. By the regional definitions used in LuminoCity3D.org, Greater Manchester has overtaken the West Midlands to become the second largest city-region in the country with 2.6 million residents. Manchester city centre has also experienced high rates of employment growth and is the primary centre in the North West, with positive signs in the business services and science & engineering sectors.

The Leeds and West Yorkshire region is also growing quickly, gaining 120,000 residents (+8%) and 50,000 jobs (+6.6%). Population growth is greatest in Leeds city centre, but is evident across the region, particularly in Bradford and Huddersfield. Similar to Manchester, employment growth is focussed strongly on the largest centre, Leeds, with a concentration in financial and business services. Despite West Yorkshire and Greater Manchester being two of the most dynamic northern regions, there is very little travel interactions between them due to poor transport links, and this surely needs to be a policy priority.

Sheffield also displays significant city centre led growth, gaining 45,000 (+6.3%) residents and 21,000 jobs (+6.7%), as does Liverpool although there has been some population decline in the suburbs. Liverpool’s figures are a gain of 21,000 residents (1.8%) and a more impressive 44,000 jobs (10%).

NorthWest_PopChange — Population change 2001-2011 in the North West and West Yorkshire regions.

LuminoCity3D_EmpDenChangeNorth — Employment density change 2001-2011 in the North West and West Yorkshire regions.

The house prices map for the north-west and Yorkshire makes a very interesting comparison to London. The dramatic gentrification that has transformed Inner London towards increasing affluence and polarisation has not (yet?) occurred. The wealthy areas are mainly suburban in the north-west, often where large cities merge with national parks such as the Peak District and the Yorkshire Dales. There are some signs that wealthier South Manchester is beginning to move towards the city-centre, but this is still in earlier stages of city-centre transformation.

NorthWest_HousePrices — House prices 2013 in the North West and Yorkshire regions.

Moving on to the Midlands, again we can see population growth across all major city centres. Birmingham and the West Midlands gained 162,000 residents (7.3%) and 47,000 jobs (+4.8%) between 2001 and 2011, with similar city centre employment density levels to Manchester. The most dynamic cities in the Midlands seem to be medium sized cites, with Leicester growing 12.8%, Nottingham by 8.1% and Derby by 11.8%, although jobs growth is more mixed. There is a significant concentration of business service jobs in Birmingham city centre, but by far the most distinctive sector in the Midlands economy is hi-tech manufacturing and R&D jobs linked to the automotive industry. Clusters around major factories can be seen in Solihull Birmingham, Coventry, Derby, Telford, Warwick and Crewe, with manufactures including Jaguar Land Rover and Toyota. The distributed nature of employment contributes to considerable travel flows between neighbouring cities.

Midlands_PopChange — Population change 2001-2011 in the Midlands region

Midlands_JobsChange — Employment density change 2001-2011 in the Midlands region.

Similar to the North West and Yorkshire, city centre housing markets are relatively inexpensive in the Midlands, with wealthier areas in the suburbs, particularly between Birmingham, Coventry and Warwick/Leamington Spa. There are signs that wealthier groups to the south of Birmingham are moving further into the city centre.

Midlands_HousePrices — House prices 2013 in the Midlands region.

Will Growth Transfer from the South East to the North?
With the South East struggling to accommodate growth and northern regions trying to attract more growth, the answer seems obvious- transfer growth to the north. Unfortunately urban economics is seldom that straightforward. London is a global leader in a range of service sectors, and it does not automatically follow that existing firms and new firms would choose northern cities over the South East. There are however many encouraging signs in cities such as Manchester, Leeds and Birmingham with growth in a range of knowledge-economy sectors. The gap with the South East still remains extensive, and this essentially is the crux of the debates about city devolution and infrastructure investment: whether or not these policies can enable northern cities to bridge this gap. London currently has great advantages in terms of public money invested in infrastructure like public transport, and also in terms of political power to plan and manage growth through the Mayor and Greater London Authority. The argument in favour of empowering northern cities looks increasingly convincing, and we shall see in the coming months whether politicians are brave enough to instigate this process.

Explore the performance and dynamics of GB cities at LuminoCity3D.org

September 22, 2014June 5, 2017Posted in City Planning, Mapping, VisualisationTagged Density, Great Britain, LuminoCity3D, Planning, Urban Form, Visualisation3 Comments

Recent urban growth in the UK has further emphasised the role of cities in influencing economic prosperity, quality of life and sustainability. If we are to meet 21st century social and economic challenges then we need to plan and run our cities better. Data analysis can play a useful role in this task by helping understand current patterns and trends, and identifying successful cities for sharing best practice.

LuminoCity3D.org is a mapping platform designed to explore the performance and dynamics of cities in Great Britain. The site brings together a wide range of key city indicators, including population, growth, housing, travel behaviour, employment, business location and energy use. These indicators are mapped using a new 3D grid-based approach that allows consistent comparisons between urban areas to be made, and relationships between urban form and city performance to be identified (technical details are provided here). Press coverage of LuminoCity3D has included Londonist, Wired.co.uk, Independent Online and Guardian Cities.

Taking for example employment density change in northern English cities as shown below. Current growth is mainly in ‘knowledge-economy’ services that generally favour being clustered together in city centres, generally reinforcing a select few larger centres rather than many smaller centres. There is clear growth in Manchester, Leeds and Liverpool city centres, particularly Manchester which displays the biggest increase in employment density of any location in GB. But around these success stories there is a much more mixed picture of growth and decline for many other centres that are finding it more difficult to compete for firms and jobs.

Employment density change in the north of England (blue is an increase and orange decline). Manchester and Leeds city centres have established themselves as the largest centres, with the biggest increase in Manchester.

Interactive City Statistics

City statistics are available to make more precise comparisons between urban areas. Statistics can be viewed on LuminoCity3D.org by moving your mouse pointer over a city of interest, or by hovering/clicking on the GB Overview Chart at the bottom left of the screen. The graphs and statistics change depending on the map indicator selected, so that the LuminoCity maps and statistics are interactively integrated.

The example below shows public transport travel, a key sustainability indicator that also has important economic and equity implications. Greater London is by far the public transport centre of the UK with nearly 50% of commuting by public transport. Without the investment and historic advantages of London, city-regions like Manchester and Birmingham do not even manage 20% PT commuting. But we can see that it is not essential to be as gigantic as London to achieve more sustainable travel. Edinburgh, with a compact form and extensive publicly owned bus network, achieves 36% PT commuting.

Public transport commuting in central Scotland. Hovering over urban areas highlights indicator statistics and highlights the city’s position on the GB Chart.

Indicator Themes

The map indicators on LuminoCity3D.org are split into five themes- Population, Transport, Housing, Society and Economy- which are selected from the Indicators Selection box to the top right. Population covers resident and employment density; Transport looks at journey-to-work, accessibility and air-pollution; Housing covers house prices, types, tenure and household size; Society looks at various inequality measures; and finally Economy covers the distribution of growth industries such as ICT, creative industries and hi-tech manufacturing.

LuminoCity3D_HousePPSE — House prices 2013 in the South East of England.

Comments and feedback on the site are very welcome. Have a look at the Comments & FAQ page, tweet @citygeographics, or email duncan2001@gmail.com.

LuminoCity3D Credits

Site design and cartography © Duncan A. Smith 2014.

Duncan is a researcher at the Bartlett Centre for Advanced Spatial Analysis, University College London. Data hosted at CASA with generous help from Steven Gray.

Maps created using TileMill opensource software by Mapbox. Website design uses the following javascript libraries- leaflet.js, mapbox.js and dimple.js (based on d3.js).

Source data Crown © Office for National Statistics, National Records of Scotland, DEFRA, Land Registry, DfT and Ordnance Survey 2014.

All the datasets used are government open data. Websites such as LuminoCity would not be possible without recent open data initiatives and the release of considerable government data into the public domain. Links to the specific datasets used in each map are provided to the bottom right of the page under “Source Data”.

Mapping the Densification of Cities in England & Wales using the 2011 Census

June 24, 2014September 22, 2014Posted in UncategorizedTagged agglomeration, Census 2011, Density, Great Britain, Planning, Urban Form, Visualisation2 Comments

UK cities have been undergoing significant change over the last decade, and the 2011 census data provides a great basis for tracking current urban structure. I’ve mapped population and employment density for all of England and Wales in 2011, using a 1km² grid scale approach-

The main themes that emerge are the dramatic intensification of London, high densities in some medium sized cities such as Leicester and Brighton, and the regeneration of the major northern conurbations, with Manchester and Birmingham as the largest employment hubs outside of London.

Mapping all of England and Wales together is a useful basis for considering city-regions and their connections (note Scotland has not yet published census 2011 employment data and is not mapped). Certainly this is a major theme in current policy debates grappling with the north-south divide and proposed high-speed rail links. I’ll be looking at densities in relation to network connections in future posts as this topic is part of ongoing research at CASA as part of the MECHANICITY project.

It is also possible to directly map changes in density between using the same visualisation approach (note the grid height describes density in 2011, while colour describes change in density between 2001-2011)-

The change map really highlights the pattern of city centre intensification combined with static or marginally declining suburbs in England and Wales. This trend was discussed in a previous post. The two statistics of peak and average densities reinforce the city centre versus suburbs divide, with peak density measurements growing much more than average densities. But the peak density statistic is somewhat unreliable (such as in the case of Birmingham/West Midlands) and we will be doing further work at CASA to define inner cities and produce more robust statistics of these trends.

Notes on the Analysis Method-

The density values were calculated from the smallest available units- Output Area population and Workplace Zone employment data from the 2011 census. This data was transformed to a 1km² grid geography using a proportional spatial join approach, with the intention of standardising zone size to aid comparability of density measurements between cities. The transformation inevitably results in some MAUP errors. These are however minimised by the very fine scale resolution of the original data, which is much smaller than the grid geography in urban areas.

The workplace zone data is a very positive new addition by the Office for National Statistics for the 2011 census. There is a lot of new interesting information on workplace geography- have a look at my colleague Robin Edward’s blog, where he has been mapping this new data.

Defining city regions is another boundary issue for these statistics. I’ve used a simple approach of amalgamating local authorities, as shown below-

An Urban Renaissance Achieved? Mapping a Decade of Densification in UK Cities

September 9, 2013August 24, 2015Posted in UncategorizedTagged comparative urbanism, Density, Great Britain, LuminoCity, Planning, Population Change, UK Census 2011, Urban Form, VisualisationLeave a comment

It’s been 14 years since the landmark Urban Task Force report, which set the agenda for inner-city densification and brownfield regeneration in the UK. Furthermore we’ve seen significant economic and demographic change in the last decade that’s greatly impacted urban areas. We can now use the 2011 census data, mapped here on the LuminoCity GB site, to investigate how these policies and socio-economic trends have transformed British cities in terms of population density change.

The stand-out result is that there’s a striking similarity across a wide range of cities, with overall growth achieved through high levels of inner-city densification (shown in lighter blue to cyan colours) in combination with a mix of slowly growing and moderately declining suburbs (dark purple to magenta colours).

We can see this pattern in the growing urban regions of Manchester, Birmingham, Leeds and Sheffield above. Manchester has the fastest population growth after London, with 8.1% growth in the city-region, and a massive 28% growth in the core local authority. Average densities in Manchester have gone up by 28% (+35 residents per hectare), but it’s not a uniform growth. There are new development sites at a very high 300 or 400 residents per hectare, contrasting with low density surrounds and the extensive remaining brownfield sites. There is a patchy nature to the current urban fabric of Manchester, indicating that much further development could still take place.

The West Midlands Conurbation is the third fastest growing city-region at 7.3%, with a higher 10% growth in the core city authority Birmingham. Density increases are more modest here (+13 residents per hectare) but the same general pattern remains. Similar patterns of high density inner-city growth are also clear in Leeds (5% growth) and Sheffield (8% growth).

The trend applies to medium size cities also. Those cities with the highest growth rates like Leicester (+18%), Nottingham (+14%), Cardiff (+13%) and Bristol (+12.5%) show fewer signs of suburban depopulation-

Scottish cities have a stronger tradition of high density inner-city living. With compact cores already in place, Edinburgh (+6.5%) and Aberdeen (+5%) have been expanding the inner city into Leith and Old Aberdeen-

Meanwhile the UK’s former industrial powerhouses of Glasgow, Liverpool and Newcastle display a more problematic variation on this pattern. City centre intensification is still much in evidence, with core city authority populations growing at 8% in Newcastle, 6% in Liverpool and 4% in Glasgow. But this growth is in combination with outright decline in some surrounding towns and suburban areas, particularly around Glasgow. These patterns are linked to major programmes to overhaul poor inner-city housing stock, but are also inevitably linked to weaker economic growth in Glasgow and Liverpool. The picture is better in Tyne & Wear, where there are more positive employment signs (8% growth in workforce jobs 2001-2011).

What is driving this urban dynamic?

In addition to planning policy shifts, a series of economic and demographic changes are contributing to the pattern of central growth and struggling suburbs, as commentators have variously been observing in the UK and US (e.g. gentrification researchers, Erenhalt, Kochan). Demographic aspects include more students, immigrants, singles and childless couples. Economic aspects include city-centre friendly service and knowledge economy jobs, as well as increased costs of petrol. For these trends to occur over a wide range of demographically and economically diverse cities in the UK and beyond, clearly there are multiple factors pulling urban populations and growth in similar directions.

London Extremes

We’ve avoided the gigantic outlier of London so far. It’s a city apart in many ways- much larger (8.1 million in the GLA area) and faster growing (+14% 2001-2011). It’s also massively higher density, with average residents per hectare 50% higher (nearly 200 residents per hectare) than the next most dense city-region in GB. The biggest changes have been in Inner East London. Tower Hamlets (where Canary Wharf has boomed) is 1st on every indicator- highest population change (+28.8%), highest employment change (+50%!!), highest population density (324 residents / hectare). The pressures for growth in London are so high that there is little surburban decline in population terms (although employment has been declining significantly in Outer London).

Yet the high rate of densification in London has come nowhere near meeting housing demand. London is the midst of a massive housing shortage and crisis, with some of the world’s highest property prices. The debate is currently raging about what needs to be done to accelerate construction, with advocates of transforming more land to community ownership (e.g. Planners Network UK), relaxing planning regulations such as the green belt (e.g. LSE SERC), and implementing an array of measures simultaneously (e.g. Shelter Report). We can see London’s challenges in the maps, such as the failure thus far of the flagship housing expansion programme, the Thames Gateway, to deliver. Some high profile development sites like Stratford and Kings Cross have only recently opened for residents and so do not show in the 2011 data.

London2 — The Thames Gateway- aside from Woolwich, little housing has been delivered.

Another more surprising result is the fall in the population of Inner West London, particularly Kensington and Chelsea. While this finding does need some context- K&C is still the forth most densely populated local authority in the country- it’s still an amazing trend given the extreme population pressures in London. It is in line with arguments that the most expensive properties in London have become investments for international capital rather than homes for living. Such trends push prices up, cut supply and bring questionable benefits to the city. Addressing this issue would require tax changes, and macro economic factors like the value of the pound and yields on alternative investments are also clearly influential.

London3 — Inner London- expansion in the East and decline in Kensington & Chelsea

Summary- an Ongoing Renaissance and Suburban Challenges

Well to state the obvious GB cities are, with only a few exceptions, growing significantly. That’s not to be sniffed at given the history of widespread urban decline throughout the second half of the 20th century. And secondly the pattern of growth in density terms is clear- densifying inner cities, and fairly static or declining suburbs. The scale of London and the severe housing crisis has it’s own unique dynamics, while Glasgow and Liverpool are still dealing with significant population loss in many areas of the city region. But on the whole, the pattern is surprisingly consistent across cities in Great Britain.

Clearly this review prompts a series of further questions analysing the economic, demographic, gentrification, deprivation and property market processes inherent in this urban change, and what future city centres and suburbs will be like. Hopefully this mapping exercise should is a useful context for the ongoing research.

Launching LuminoCity GB: Urban Form and Dynamics Explorer

September 4, 2013March 11, 2016Posted in UncategorizedTagged comparative urbanism, Density, Great Britain, LuminoCity, Urban Form, VisualisationLeave a comment

Our cities have been changing dramatically in recent years, with the intensification of urban centres, redevelopment of old industrial spaces, new demographic trends, and the pressures of a volatile global economy. The aim of the LuminoCity website, which launches in beta today, is to visualise urban form and dynamics to better understand how these trends are transforming cities in Great Britain. Explore the site for yourself here- luminocitymap.org.

LuminoCity_PopDensity03 — London Population Density by Built-up Area 2011

LC_GlasgowJobDen01 — Glasgow Jobs Density by Built-up Area 2010

LC_ManchesterPopChan02 — Manchester Population Density Change 2001-2011

The visual style developed for LuminoCity combines urban activity data with built-form. Density values are calculated by dividing fine-scale (LSOA) employment and population data by built-up area, and then mapping the results to the same building footprint data (Ordnance Survey VectorMap). The result is a novel city perspective on common demographic indicators like population and employment density, with links between density and the texture of the built-environment clearly highlighted. So for example in the London map above, we can see the patchwork pattern of recent high density developments in Docklands (along the river to the east), and high density clustering around major rail stations like Paddington.

There are three layers included in the beta version of LuminoCity-

Each layer provides a complementary angle on urban form, with Employment Density showing business agglomeration patterns, and Population Density Change highlighting where intensification is occurring and where population losses are found. Examples of these three layers for major cities are shown above. The Population Density Change is particularly interesting in light of clear patterns of city centre growth and static or declining suburbs in many British cities, such as Manchester above. There is also in London a distinct pattern of population loss in the western inner-city, likely due to international capital speculation leaving under-occupied housing (see image below). These trends will be discussed in a further post later this week.

London Population Density Change 2001-2011

Multi-Scale Interactive Statistics

As well as browsing the map you can also click on particular locations to get a set of core statistics and rankings of that area for the current map layer. The statistics are at three spatial levels- City Region, Local Authority and LSOA. This feature shows how typical a particular area is compared to the wider city-region and the country as a whole. It also helps to communicate the variation in density measurements according to scale.

Location Statistics for Manchester, one of Britain's fastest growing cities — Location Statistics for Manchester, one of Britain’s fastest growing cities

Site Credits

The data used for the LuminoCity site is Crown Copyright Office for National Statistics, National Records of Scotland and Ordnance Survey. Cartography and site design by Duncan A Smith. The map layers were produced using the excellent TileMill software by MapBox.

The site concept was partly inspired by Ollie O’Brien’s ‘New Booth’ Map of Deprivation for Great Britain.

Datasets Used

The population data comes from the UK 2001 and 2011 Census, published by Office for National Statistics and National Records of Scotland. The employment data is derived from the Business Register and Employment Survey 2009-2011, also published by Office for National Statistics. The building footprint and urban area data is from the Ordnance Survey Vector District and Meridian products. These datasets have been published by the OS as Open Data, which is a fantastic recent development enabling sites like this to happen.

Spatial Analysis Method Details and Errors

All socio-economic mapping contains a degree of error, and the building footprint density approach used here introduces some issues. The Lower Super Output Area zone geography at which the population and employment data is published is fine scale but is not at the individual block level. Each LSOA zone represents groups of adjacent city blocks. The density results are therefore an average of the adjacent blocks in each zone. The results are affected by a particular version of the Modifiable Areal Unit Problem, and represent the density of fine-scale city neighbourhoods rather than of particular buildings. You can view the specific geography of the LSOA zones by turning on the ‘Admin Boundary’ layer on the LuminoCity site to see how blocks are aggregated.

Additionally the analysis does not consider building use (there are several technical and copyright challenges with this) and so population and employment density measures include all buildings rather than distinguishing residential and commercial property densities.

Finally, the ONS has not yet published census 2001 and 2011 population counts at the same LSOA geography, and a proportional spatial join method by building area was used to convert the 2001 LSOA census data to 2011 LSOAs for the Population Density Change layer.

Feedback and Comments

If you like the site or have any feedback or comments then you can tweet me @citygeographics, or email duncan2001@gmail.com. The site is in beta at the moment, and I plan to add more layers and interactivity in future releases. I’ll be blogging here in more detail about what the visualisations reveal about the changing geography of British cities over the coming weeks.

Visualising Flows: Great Britain Journey-to-Work

June 21, 2012October 14, 2014Posted in UncategorizedTagged Flows, Great Britain, Sustainability, transport, Visualisation3 Comments

There have been some wonderful flow maps appearing online recently, such as Paul Butler’s global facebook friend’s map, and maps of global trade and flight patterns. Inspired by these, I’ve been mapping travel patterns in Great Britain using a similar “night-lights” visual style.

The above maps use data from the UK census connecting where people live to where they work, showing how transport flows form complex urban networks and extensive metropolitan regions. The data is at ward level, allowing a good level of detail:

Taking this visualisation further, a key issue for policy makers is how people travel, with private cars having greater energy, pollution and congestion impacts than alternatives. The final map below groups work trips into car, public transport and walking-cycling travel using an RGB colour scheme, creating a galactic effect (click for larger):

The aim of the visualisation is to put travel patterns in the context of the diverse urban scale and geography of Great Britain, and reveal the degree of regional variation.

The map really highlights how different London is in terms of its extensive regional public transport network, with the other major English conurbations like the West Midlands, Manchester and West Yorkshire being highly car dominant in comparison. The variation in public transport levels could be argued to relate to London’s massive size, yet the Scottish cities of Glasgow and Edinburgh perform well in public transport terms, despite being smaller than England’s northern cities.

Active travel modes of walking and cycling are generally minimal. The cities that do relatively well are the “cathedral cities” like Cambridge and York, with a few surprises like Hull.

The maps were created in ArcGIS using the XY to Line tool, then exported to Illustrator. A key aspect of such flow visualisations is that the thousands of overlapping flows add together to form denser links using a cumulative transparency effect. This is much easier to achieve using a vector graphics program such as Illustrator. Would be nice in a future post to add Northern Ireland and the Republic, and will get a data update with the 2011 census next year.