• Talk to us on
    (+44) (0)1225 320050

Search Geofutures:

Archive for February, 2012

Geofutures celebrates its tenth anniversary

Monday, February 27th, 2012

27 February 2012: It’s ten years ago today that Geofutures was incorporated.

Surviving and thriving over a decade which saw bust, boom and bust, the growth of geographic information from mysterious rocket science to mainstream business tool, the launch of online slippy maps and rapidly multiplying download speeds, we think we’ve made it to quite a milestone.

Ten years ago today, UK housebuilders were celebrating record sales, a “gung-ho” newly formed HBOS was announcing a new share issue, and interest rates were at a 38-year low of “just” 4 per cent. And we were cementing the existence of a business which had grown out of academia (at UCL’s Centre for Advanced Spatial Analysis), going on the create the government’s Town Centres statistics methodology, the spatial sampling strategy for the Consumer Prices Index, a ground-breaking property value modelling tool and a few other achievements.

So many thanks go to all the colleagues and partners who have contributed so much along the way; and thanks to the clients who have kept us hard at it answering the tricky strategic questions that call for a bit of creative analysis.

We’re still dong that, and busy developing the next generation of online insight sharing tools alongside. More of that anon. Now for some cake.

Mapping migration

Thursday, February 9th, 2012

You can’t always get what you want… but if you try sometimes you might just find… you get what you need.

Now with that song firmly playing as my mental soundtrack for the day, I’ll explain: it’s a rare thing to find the exact data you need for a research task, but sometimes you can get what you need another way. We call it proxy data, and it works on the principle that if you didn’t have summer temperature data, say, you could measure the sales of barbecues to give you a good idea of the weather pattern.

Inward migration to the UK is an example. With open borders within the EU and it being a long time since the 2001 Census, the influx of migrants during the last decade is a matter of estimation only. However, other information can give us a view on the patterns of movement over a decade which saw ten new member states join the EU in 2004 and a booming UK economy draw in motivated and qualified economic migrants to particular areas of the country – until the economy shuddered to a halt.

Inward migrants to England and Wales registering with a GP 2000-2010: a Geofutures data map

Source: NHS data via ONS

The map above visualises annual new registrations with GPs (family doctors) per 1000 population in the districts of England and Wales between 2000 and 2010, where the previous address of the registrant was outside the UK. The darkest shade indicates more than 60 per 1000 in a given year. All kudos to my colleague Gaynor who recalled that ‘Flag 4′ as the non-UK address is called is such a useful nugget of insight.

She has then animated the maps to illustrate the dynamic shift over the decade, starting with 2000-01 and showing each year before looping back to the beginning. A couple of patterns are worth highlighting (see below).

Of course, this isn’t a perfect proxy, since not every migrant will register with a GP, and we’d expect a skew in these data towards people arriving with families and those intending to stay for some time.

Throughout as you’d expect, the urban centres show the highest rates of new registrants, but early on we can detect higher numbers per 1000 population arriving in East Anglia and Lincolnshire, with some warm spots emerging in the midlands and further west as the years go by. By 2004 East Cambridgeshire, Peterborough and the Lincolnshire districts of South Holland and Boston clearly emerge with faster rates of new registrants – an area popular with migrant workers.

The rate of new registrations in this area peaks at a rate over 30 per 1000 in 2007-08, and we all remember what happened then: the beginning of the banking crisis, the credit crunch and the slowdown of the economy. Sure enough, the rates of inward migration start to slow down, no doubt as the relative merits of hard farm labouring jobs near the Wash and skilled manufacturing for the German market rapidly shifted.

Two other twists intrigue me: what’s occurring in West Wales at the end of the decade? And how come Oxford and Cambridge have such constant high levels of registration? I’d expect high levels of overseas arrivals in both cities, but are there no other university towns where the rate is so high relative to their resident populations?

I studied in Cambridge myself (a few years ago now) and we were required by university rules to register with a doctor – they didn’t leave it to the choice of feckless teenagers – was this so for students arriving over the last ten years but not in other institutions? And can a rule like this really be behind an observable national data pattern?

Companies, government bodies and charities use our work to reveal insights like these and make strategic decisions based on them. And the comments, questions and local knowledge prompted by mapping data are all captured via easy to use tools.

We don’t just make animating maps – but sometimes they are exactly what you need.

Mark Thurstain-Goodwin

Spot hard data pattern, add soft knowledge

Thursday, February 2nd, 2012

All the development work we’re currently doing is designed to allow users to share data and map visualisations with colleagues and stakeholders. We’re automating that process by which you call someone over to look at something on your screen – together with the process of gathering the comments they make. A hotspot (or coolspot) on a map often prompts someone with local knowledge to say, “Oh, I know that road, it’s different from the next street because…”

This qualitative knowledge makes sense of the quantitative evidence and often contains the insights you need to make a decision based on the findings. The more people you involve, the more reliable the consensus findings become.

Here’s an example of a visually distinct correlation between two datasets for Great Manchester which needs some local qualitative knowledge. We were thinking about this week’s debate over the status of some qualifications being downgraded in school league tables, and whether employment data could indicate any relationship between school attainment and the value delivered back to the surrounding community.

In an exploratory way, we looked at data for the city for residents with level 4 qualifications and above (level 4 is one higher than A levels, e.g. diplomas, professional certificates, on up to HNDs, degrees, masters and so on). Almost accidentally, we compared this city-scale data pattern with residents employed in manufacturing. The two maps are below:

Percent residents with level 4 qualifications & above (darkest shades = 30%+)

Percent residents employed in manufacturing (darkest shades 20%+)

If we image a slice of pie extending south from the centre of the city, the lack of manufacturing employment and the relatively high level of qualification is visually evident (and yes, Moss Side is a blob in the middle of the pie slice – but the inverse relationship between the two phenomena seems consistent even here). The tools we’re building allow you to add markers and annotations to illustrate something exactly like this, but we’ll have to make do with pie for now.

So does manufacturing still offer relatively high levels of employment to those workers with qualifications below level 4, as we might have expected 30 years ago perhaps? Or is it more significant that higher-qualified people are disproportionately likely to live south of the centre and be employed in the service sector?

With more and better data, could we test the hypothesis that qualifications relevant to manufacturing and other local employers would add even greater value to the community than traditional academic exams – perhaps in the shape of a reduced benefits budget and related regeneration effects?

The truthful answer here and now is that I don’t know, but I bet among the residents of Manchester and equivalent cities the ‘soft’ knowledge exists to make perfect sense of these patterns, once we know they’re there, and to shape policy accordingly.

Any insight to share? Let us know below. Meanwhile it’s back to the coding coalface…

Geofutures - GIS Web Maps Data Sustainability Research - (+44) (0)1225 788870 - Contact us - Sitemap - Online GIS products - © Copyright 2012