It’s a great example of data made accessible and meaningful, no doubt the reason why so much of the UK’s media ran the story today. The Local Data Company have launched a report for the 2009 year end, Dawn of a Better Market, including a Geofutures retail vacancy rate contour map for Q4 2009, updating the one used by the FT looking at the first quarter of the year.

Side by side, the maps show a contraction in the area of highest vacancy rates in north east England and southern Scotland, though vacancies are still running high, with north Wales/Merseyside and the south Midlands also performing slightly better. The North Midlands and East Kent are still hotspots of high vacancies.

These results are based on over 149,000 shop premises in 700 town and city centres across Great Britain surveyed by LDC. More information about Town Centre Intelligence.

High street retail vacancies, Q1, 2009

High Street retail vacancies, Q4 2009

The analysis takes the number of individual shop premises in the town centres surveyed every six months by The Local Data Company, then visualises these numbers in three dimensions over a map of London’s West End and surrounds.

(Note that a similar analysis could also be done for total floorspace, but this one is for the number of retail units – giving rise to interesting peaks like the one for Brixton in the right-hand foreground).

We can see the highest peaks around Oxford Street and Knightsbridge, with notable neighbours going East to the City, north to Camden and Islington and a clear mountain range along the length of the King’s Road. Through the semi-transparent data layer we see the importance of the road network to peak retail locations, even in a city with a well-developed public transport infrastructure.

Also significant is the clear peak of retail density at the new Westfield shopping centre at White City, as new a feature as an Icelandic volcano emerging from the sea.

Not only are these peaks immediately identifiable by location, but the 3-D treatment makes a map legend almost unnecessary, and makes comparison of relative heights (i.e. retail densities) at different locations immediate and straightforward. The simple visual metaphor of ‘highs’ and ‘lows’ across a landscape perfectly complements our understanding.

The underlying data here, mapped and available online with vacancy rates, churn, multiple / independent mix, floorspace and more for 1,300 UK town centres via LDC’s Town Centre Intelligence (powered by Geofutures), is acknowledged to be the most up to date available.

But actually I like this map for what it shows us about all data – that if we put information on a map we reveal its highs, lows and hidden insights.

An exciting new project is underway for Geofutures: working with the Centre for Sustainable Energy, we’re modelling and mapping residential heat demand for Regen SW, the renewable energy agency for the south-west of England.

The aim is region-wide insight into the potential for renewable and low-carbon heat generation and distribution, with outputs at sufficiently fine scales to allow users to identify individual buildings and groups of buildings which could benefit from heat distribution installations.

It’s set to be the most advanced heat mapping exercise undertaken in the UK to date, building on CSE’s proven expertise in modelling heat demand in London, Bristol and West Sussex, with the addition of Geofutures’ experience in using GIS to analyse fine-resolution data, as well as simply visualising results.

An important benefit of starting with data at building level is the ability to aggregate results upwards without losing accuracy, still maintaining the ability to drill down to fine scales at chosen locations. Other studies have started with data generalised for hundreds of addresses, which can only output heat demand results for broad areas. For local heat distribution to become a reality, we need data for highly localised decision making.

See the website of the Centre for Sustainable Energy.

Yet here I am thinking about companies using geographic information science (GIS) and I can’t avoid those clichés. Our industry is certainly becoming more mature – maybe even mainstream – but talking to clients across every sector, it’s clear that many organisations could do much more with their data using GIS. Many could still take it to the max, as it were. Their data is just not feeling the burn.

So I’m going to take on the role of personal trainer (not an everyday experience) and explore why this is so, what most public, private and third sector enterprises are doing with GIS now, and how much more they can achieve.

It’s not generally a want of investment. Considerable sums are spent on people, data, hardware and software that make up an in-house GIS function. Companies who make this investment often do so because they need to perform fairly rigidly defined tasks, based around routine data-management tasks. This makes perfect sense, but in these circumstances it’s easy to ignore the full potential in both the data and technology.

So, like a personal trainer, the point of a specialist adviser like Geofutures is that we are able to keep our eyes on the prize. It’s no disrespect to an in-house GIS officer who is head down keeping the wheels turning if we come along and offer new ways to push the software, hardware and data of GIS to deliver much more than is conventionally possible.

And often it’s the data, rather than the technology itself, which holds the key to unlock hidden value, identify new revenue streams and streamline processes.

Is your business in this position? Here’s a little test. The paragraphs which follow describe the most common GIS functions within an organisation. Is yours doing any or all of them?

Want to read more of Simon Lewis’ article? Please register here and we’ll email you the rest of this article. We never share your data and you can unsubscribe to Geofutures updates at any time.

Oracle occupies an interesting position in the GI world: at once a significant challenge to established GIS vendors, and also challenged themselves by online mapping and data platforms. Would Release 2 of Oracle 11g make clear how they will move forward, I wondered?

The new spatial features in Oracle 11gR2 are certainly impressive. New functionality includes more complex network analysis including hierarchical shortest path analysis and a travelling salesman algorithm. It all felt good to me, perhaps because it makes the database technology seem more, well, GIS-like.

Enhancing usability

Speakers touched on some intriguing ways Oracle databases are powering applications with enhanced usability. Olivier Bucaille from Autodesk advocated using wizards and preset analytical environments to increase accessibility for every user, which I wholeheartedly agree with, and also 3D mapping and graphics at the building scale, which I’m less sure I support.

(I’m not a visualisation Luddite, but 3D bar charts have questionable legibility just used in a document – overlaid on a 3D map they can ask even more of the reader. In addition to this, there are significant statistical issues with taking aggregate data and assigning it to back down to the scale individual buildings in 2D or 3D, pretty as they may look.)

Evolution or revolution?

Anirban Acharya from Infotech Enterprises predicted that use of Oracle databases would increasingly become a key differentiator, and signal the end of proprietary database engines supplied by the main GIS suppliers. His suggestion that spatial databases were an evolutionary, not disruptive technology (like Google Maps was) got me thinking though.

My own talk had also recalled the transformative moment in 2005 when Google took web mapping mainstream. Disruptive indeed, though a highly positive development for our industry. But why did the development of Oracle Spatial (which we first used at much the same time) not feel similarly revolutionary?

Was it because database technologies were better known and understood than mapping platforms among IT professionals? Did Oracle in effect slide in spatial functionality when we weren’t looking? I think this is an illusion, and that Oracle Spatial was disruptive too. The monopoly of enterprise GIS vendors was broken when it arrived on the scene, ready to power online, desktop GIS applications.

And the spatial elements still present a knowledge gap for many highly savvy database developers. My own developers and GIS analysts continue to educate each other to span the divide between the database and the spatial model. Another speaker, Andy Spears from South Gloucestershire council, agreed; his central ICT team have had to learn spatial skills from scratch to support the technology.

So is Oracle Spatial the quiet, persuasive advocate prepared to play the long game from the inside to establish itself at the heart of GIS, to Google Earth’s loud, media-hungry revolutionary, delighted to stir things up as it (literally) takes on the world? And which one do we back in the race?

Mark Thurstain-Goodwin

Colin’s thesis is that the food security issue is a simple matter of feeding the population as far as practical from local sources, recognising that some trade between specialist production areas will always be necessary. He argues that we simply need macronutrients (energy foods and protein), mainly in the shape of grains, and micronutrients – vitamins and minerals – and that by growing lots of wheat and encouraging more urban horticulture we can feed ourselves. I’m brutally over-summarising, of course, but he is keen to keep things simple.

This desire for simplicity makes him question the value of analyses like the land use mapping Geofutures did for this piece of research: “Elaborate models analyzing overall ecological footprints of particular communities in fine detail are not necessary. So long as we do the best we can within the guidelines we can’t really go wrong,” he writes.

However, at the end of his commentary he includes a postscript in a different mood. “This and all the other questions raised in this essay could and should have been addressed decades ago, and would have been addressed by any government that was truly alert to world trends. There are many other questions, too – scientific, economic, sociological, moral, practical. Since the government is unlikely to act this side of food riots (which it will treat at “terrorism” and call out the riot police) people who give a damn need to ask the questions for ourselves.”

I believe in these sentences Colin contradicts his own conclusion that research – even elaborate models – are unnecessary. The Transition movement has been successful because it responds positively to this fear. People who have never been engaged in environmental questions are getting involved and feeling empowered to help plan their communities’ futures.

And government (here I include many local authorities, which have embraced Transition planning in local strategic plans) is witnessing this community feeling and slowly starting to respond. To encourage this and make energy-descent planning truly meaningful, major resources and policy shifts are needed. My experience of this kind of government is that is moves slowly and demands evidence before committing taxpayer’s money. The farming community needs evidence before it will change any current practices too.

Food security is not a stand-alone issue, of course. The land use analysis and mapping undertaken for this study was not as detailed as we would like – it needs local data from across the country to move to next level – but even so it revealed absolutely fundamental issues which will impact food relocalisation and our life experience after Peak Oil.

There is not enough woodfuel for space heating. If we need to relocalise food production, people will need to live in rural areas, including building houses on protected rural land. And major conurbations overwhelm the foodsheds of surrounding communities. Even if we could be steadfastly common-sense in our approach to planning future food supply, I’d say joined-up planning encompassing these kinds of issue is going to need a wee bit more research to get it right.

Colin describes his own analysis of food security as ‘radical’, and his faith that common sense will prevail without major shifts in political and economic priority is certainly that. In using phrases starting “What all cities can do is…” he is not acknowledging the gap between technical possibility (yes, we can all plant tomatoes on our balconies) and reality (but we won’t while we can still get them dirt cheap at Lidl, and by the time we realise we’re really in an energy crisis it will be too late).

The Transition movement is precisely about how we move from here to a more attractive version of the future, and for me that’s where there’s plenty more meaningful research still to be done.

Mark Thurstain-Goodwin

Read Colin’s full commentary here.

You couldn’t move for stories about retail vacancies derived from TCI data last week, and no wonder – our high streets have a gap-toothed look about them just now, and the information from TCI is really too good to ignore. See how the BBC covered the story here.

TCI allows easy (and statistically robust) comparisons between town centres – defined consistently across Great Britain by the government boundaries defined by a Geofutures methodology.

This reveals significant regional variations in the vacancy rate – southern towns and cities are still faring much better than their northern counterparts, where vacancy rates have doubled since mid-2008, while Wales and the West are performing better than average with only a 25% increase in the same period.

A similar pattern was revealed when LDC researched what has happened to empty Woolworths premises. About 70% of all the stores are still empty, but within this national picture, fewer than 50% of Greater London Woolworths premises have not been re-let, while 90% of those in north-east England are still vacant.

Of those Woolworths stores which have been re-let or are in negotiation, LDC found 30% becoming supermarkets and 42% opening as discount stores including 99p Stores, Poundland and Bargain Madness – an interesting trend which will have long-lasting impact on the profile of town centre street scapes.

We’re continuing to work with The Local Data Company to mine more insight from the data. A special area of interest is the difference in performance between traditional high streets and shopping centres, where trends like the tide of discount stores in lower-rent locations may prove to be highly relevant. We’ll have an update soon.

These maps are the results of our food security analysis published together with the Transition Network this month – you’ll find details of our methodology and a link to the full report in our earlier post.

The analysis is based on Defra land classifications, a permaculture model and a ‘food zoning’ model based on perishability and labour intensity, which places fruit and vegetable growing areas closest to the town, followed outwards by cereals and other food crops, dairy and beef, and finally sheep farming on the poorest soils furthest from the town.

Have a play and see how you can zoom in to see the component parts of the foodshed. Doing so against an aerial photography background brings home how a relocalised food economy might look around this classic market town.

Of course, the analysis raises many more questions: about the overlap between towns’ foodsheds, the lack of sufficient woodfuel and the urgent need for more fine-scale land use data among other issues. As Transition founder Rob Hopkins wrote in his blog, food scarcity is how wars start – unless, we hope, we’ve done much more analysis of this kind to plan for it effectively in advance.

It’s a good example of how GIS, spatial analysis and mapping data can bring possible future scenarios to life, igniting debate and making results widely accessible to experts and non-experts alike. For us, it’s satisfying applied to any sector, organisation or data type, but food security analysis probably has the widest implications of anything we do.

It’s nice to have your career choice reaffirmed from time to time. I did feel a bit of that special warm glow this month at a great event organised by our clients Ipsos MORI to launch their National Indicators Mapping Application (NIMA), developed by Geofutures.

What set me glowing? Being reminded that a picture is worth a thousand words (the bumper-sticker of GIS professionals everywhere). In fact it was two pictures, so maybe that’s two thousand words. Here they are:

Twin images of perception data in North London from Ipsos MORI's NIMA app show strong correlation

The audience, a who’s who of local authority research heads and their suppliers, got a whistle-stop tour of all Ipsos MORI’s work in this important market, and NIMA was centre stage. All authorities now have to poll their electors on 198 National Indicators of satisfaction and the factors affecting it, and NIMA provides instant online insight into the results. Side-by-side ‘double view’ comparisons of maps like these are a key part of the application.

What these two visualisations show are three key reasons why mapping these kinds of data is such a compellingly good idea: the correlation of the two hotspots, the fact that both are visible despite the ward boundaries, and the geographical context that the map offers.

So firstly, the two maps describe responses to two different survey questions: overall satisfaction/dissatisfaction with the area as a place to live on the left, and perception of social cohesion on the right. Only by locating these respondents on the map in a statistically smoothed data landscape can we so immediately see the close spatial correlation of the low-perception hotspots. For a local authority looking for ways to focus resources in hotspots of this kind, to deal with specific issues where they are being experienced and to maximise policy effectiveness, the benefits are obvious.

And if your local authority is only offering National Indicator results by ward, IMHO you want to be asking how efficiently they are spending your council tax. If the same results had been aggregated by ward, the hotspots would disappear altogether. It certainly wouldn’t be evident that dissatisfaction and issues of social cohesion were concentrated in one area which impacts sections of four separate wards. Tying data to actual location, rather than some arbitrary zonal boundary, is a key benefit of GIS analysis. Cue warm glow.

And a map does another simple but fundamental thing: it shows what’s on the ground in the hotspot locations. These two hotspots have a major roads running through them. Does this mean we’re looking at a pocket of high-density roadside dwellings choked with exhaust fumes, whose residents are struggling with low incomes, transient neighbours and the social issues that go with them? The sort of neighbourhood where local authorities really need to send their outreach workers?

Intriguingly, no. Zoom into an aerial image of Hendon Wood Lane and you’ll find leafy open spaces, substantial detached houses, gardens and even a smattering of swimming pools. This is where the hotspots of community dissatisfaction and perception of poor social cohesion are undoubtedly to be found, but not I suspect because of social deprivation.

Again, a map visualisation proves its worth, hinting at a fascinating little area for further exploration.

We were chuffed to see that the Financial Times used this information as a source for a headline story on 16 May 2009, also using the data to highlight the worst-affected sectors – predictably perhaps, these are fashion, electrical, furniture DIY and jewellery retailers.

The application delivers constantly-updated data on 675 town centres across Great Britain, giving instant insights to planners, developers and investors into the retail mix and the health of the high street.

TCI highlights that the last two quarters have seen fast growth in the rate of shop vacancies, with particularly high levels in the north east of England and the West Midlands, as the contour map created by Geofutures for the FT illustrates.

Map of retail vacancies Q4 08-Q1 09 prepared by Geofutures for the Financial Times

The specific effects of the credit crunch can be seen in the nature of these vacancies: the overall closure rate has not increased significantly, but the numbers of new openings – often reliant upon bank finance – have shown a sharp reduction.

The main idea behind TCI is the ability to manage vast volumes of data seamlessly, drilling down through these kinds of numbers, comparing town centres like for like and at successively fine scales. For more information about the product, please visit The Local Data Company website.

See the news story on ft.com (registration required).