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Food security and the need for GIS models

Wednesday, September 9th, 2009

As expected, the recent paper ‘Can Totnes and district feed itself?’ (see earlier posts) has started stirring things up. An intriguing response comes from Colin Tudge, a director of LandShare CIC (co-funders of the research) and leader of the Campaign for Real Farming.

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.

Town Centre Intelligence stocks more shop vacancy insight

Thursday, August 6th, 2009

Our friends at The Local Data Company have been busy analysing the data in Town Centre Intelligence (TCI), the all-singing all-dancing urban information tool we helped them develop.

As shops close around the UK, The Local Data Company keeps track with Town Centre Intelligence, built by GeofuturesYou 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.

Foodsheds, the mashup

Thursday, July 23rd, 2009

Fresh off the Geofutures GIS mashup assembly line is an interactive version of the maps we produced for the ‘foodshed’ surrounding Totnes and its neighbouring towns in Devon. This is a static image – please link through to see the functioning mashup.

A static image from the Totnes and district foodshed mashup by GeofuturesThese 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.

Hotspots leave a warm glow

Friday, July 10th, 2009

Mark Thurstain-Goodwin enjoys seeing Ipsos MORI put spatial data in front of local authorities

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

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.

Retail vacancies soar, TCI reveals

Friday, July 10th, 2009

Town Centre Intelligence (TCI), the new urban data management tool we developed for The Local Data Company, reveals that UK retail vacancy rates rose from 4% to 12% in the 6 months to March.

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

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).

Food footprints: re-localising UK food supply

Wednesday, July 8th, 2009

What happens when oil is too expensive to transport food around the world?

To avoid famine and food conflicts‚ we need to plan to re-localise our food economy. This map is part of that process – showing the food requirement ’footprints’ around settlements in SW England.

Use the pan and zoom controls to view your chosen area‚ and read more about how Geofutures is mapping our food future below.

 Overlapping town footprints  Add major towns
 Non-overlapping town footprints  

The UK’s future food security depends upon domestic farmers‚ the market network and some clever use of data. Planning for our food future needs to start now.

In December 2008, Geofutures founder Mark Thurstain-Goodwin told the National Food Markets Conference in Blackpool that the UK’s food security is more precarious now than before we faced the WW2 U-boat blockade.

We are heavily dependent on the global food economy. When oil supplies diminish and prices inevitably rise in future‚ we will no longer be able to afford to import our foods. The answer must lie in re-localising our production of food‚ fibre and fuel‚ but as Mark argues‚ there are ways in which we can use data to hugely improve how efficiently this is done. The map here is part of that analysis.

Peak Oil and food security

Many argue that Peak Oil (the time when extraction from the world’s oilfields hits its physical maximum‚ beyond which it can only diminish with corresponding increases in price) is imminent‚ or even past. The time when oil prices start to affect food supplies doesn’t begin when oil runs out completely‚ but long before that‚ when oil-fuelled global distribution becomes increasingly uneconomic.

This is a central concern of the Transition Network‚ the fast-growing movement enabling communities to plan for increasing their resilience for a post-oil economy now‚ including re-localising food production.

Calculating food footprints

A food footprint is only a very basic representation of the land required around a town to feed its population‚ based on the calculation below.

The map above illustrates circles around communities with a population of over 800, and we can view them as ‘overlapping’ i.e. the absolute size of the land required by that community irrespective of whether this overlaps another footprint, or ‘non-overlapping’ i.e. a footprint size reflecting the size a footprint needs to be according to availability of ’free’ land not occupied by another footprint. In both cases, the size of the circles reflects land which is currently occupied by farmland and gardens‚ i.e. technically available for food production.

The map also allows the footprints of the major towns in the region (Bournemouth, Bristol, Cheltenham, Exeter, Gloucester, Plymouth, Poole and Swindon) to be switched on and off to see the demand that these centres create, although the non-overlapping footprint sizes always reflect the footprint of major towns even when they are not visualised.

Food footprints illustrate simply‚ but powerfully‚ how large an area is needed to fulfil the basic needs of an urban population. It’s a good example of the use of geographic information (GI) science – putting data onto a computerised map‚ in order to create a picture of what’s going on in a way anyone can understand – in which Mark’s company Geofutures specialises.

Can the UK feed itself?

Permaculture expert Simon Fairlie performed a series of calculations on the potential for land to produce enough food‚ fibre and fuel under a series of agricultural regimes. Taking one which Fairlie calls ’Livestock Permaculture’‚ 1 hectare of combined agricultural and forestry land supplies 4.4 people.

Crudely on this basis‚ the whole UK landmass could feed 98 million people – many more than our current population of about 61m – but of course the population is not evenly distributed‚ nor is all land equally productive.

A supporter of the Transition movement‚ for these reasons Mark nonetheless warns against individual communities becoming insular as they plan to re-localise. They may have plenty of surrounding productive land‚ but if it falls within the food footprint of a larger settlement‚ there will be competition for its resources.

How do we plan for the food future?

So how do we plan for a future without cheap food imports‚ without oil-fuelled central distribution depots? Mark argues that the data and technology we have available now can point the way to a domestic food economy in which food can still be moved from areas of lower population to the nearest areas of food deficit‚ having been produced in those areas which best suit farming of grain‚ fruit‚ dairy or vegetables.

GI maps and analysis show us where the population hotspots are‚ and where certain farming types predominate. They also highlight additional future issues for the mix‚ like areas at risk from sea level rise and changes in rainfall and temperature.

Advanced spatial analysis can provide the key to planning how centres of agricultural production can supply their regional hinterlands‚ how the footprint of London and the home counties can co-exist with the footprints of the towns it encompasses‚ and how we can avoid serious food shortages in future.

The scale of a study of this kind and the investment required would not be large – especially compared with the risk of heading into a food crisis blindfold – and Geofutures is seeking research partners and funding to continue this work.

For more information about the Geofutures food footprint analysis, or how GI can help you achieve spatial insight in this or another field, please contact us.

More information about the Transition Network can be found here.

How clean is your data?

Thursday, July 2nd, 2009

Geofutures’ Simon Lewis explains that the success of a major new information resource demands a thorough approach to cleaning up the underlying data

For the last six months the Geofutures development team have been working on a stimulating project in partnership with The Local Data Company (LDC). Town Centre Intelligence is a web-based application designed to provide insight and information on the economic health of town centres.

LDC collects a huge wealth of data on retail premises, obtained and updated directly by their own team through street surveys. Until now the company has had a thriving business supplying clients such as Yell with data in the form of database extracts, but they rightly identified the opportunity to create even more value from this enormous resource.

Town Centre Intelligence provides subscribers – town planners, town centre managers, retailers, property investors and master planners among others – with all the retail data on 1,300 town centres and the means to sort, search and visualise it via a user-friendly map based interface. Delivered over the web, TCI delivers context-specific information on town centre performance at successively fine scales at the click of a button.

TCI offers instant online retail data, including the independent / multiple mix, shown here for Edinburgh

TCI offers instant online retail data, including the independent / multiple mix, shown here for Edinburgh

Geofutures’ part of the game has been the development of this online data platform. In building it, some of the thornier challenges we’ve faced have involved the database structures which underpin the application. Dealing with spatial data is our stock in trade, but it’s certainly not for the fainthearted, as some of the issues set out below will illustrate.

Creating locations

TCI is based on The Local Data Company’s data, but it also incorporates town centre boundary data from the Dept for Communities and Local Govt (CLG), and floorspace information from the Valuation Office (VOA). Look at any three organisations’ data and you’ll see that there is no such thing as a universally accepted address standard in the UK, notwithstanding BS7666, PAF and Address Point. None are wrong, they are just all slightly different, and this is the issue we addressed (no pun intended) with bringing these three sources together.

The key thing they have in common is that they refer to a place on the ground (with a few exceptions for things like house boats).  Instead of trying to match between the sets, we allow a point on the ground to have multiple addresses and we match to the point. With the volumes of data involved (some 300,000 business premises records in total) we needed to build a specialised ‘data cleanser’ application to perform these matches, which also allowed us to add non-address attributes such as floorspace to these points.

You can’t provide a picture of UK town centre retailing without dealing with shopping centres, of course. In each shiny mall lurks an addressing hornets’ nest all of its own. Multi-level, multi-concession shopping centre addresses bear little relation to normal addressing, and being privately-owned estates, collecting data and taking photos is often restricted.

Beyond this, we have to deal with the granularity of different types of address. A department store and a shopping centre may both contain multiple businesses but these are treated differently in different databases: the VOA may match on one level and the Ordnance Survey on another level. TCI offers unique added-value information such as churn rates of retail premises. This calculation is deceptively complex anyway, and to achieve this within acceptable bounds of accuracy, TCI has to recognise different addressing schemas and calculate churn rates accordingly.

Creating ‘towns’

There’s lots more elsewhere on this site about the Geofutures project to define town centres for what’s now CLG (previously ODPM, DETR and DoE; it was a long project). The need for it arose because the definition of a town centre – precisely where it begins and ends – depends upon whom you ask, so no consistent and comparable boundaries could be drawn.

This was significant when the health of town centres appeared to be under threat from out-of-town retail parks, and the success of planning changes to improve this had to be evaluated against standardised boundaries. These were created by tying multiple relevant datasets to town centre locations, creating an Index of Town Centre Activity based upon economic activity, property and diversity measures, and deciding a nationally consistent threshold value which would delineate every boundary.

The boundaries are used in TCI to allow like for like comparisons between town centres (London and other major cities comprise many smaller centres, for example, and only retail data within the government boundaries are included in the application). This too requires a lengthy data matching process, using what us GISers call ‘point in poly’[gon] to link locations to towns.

Generating statistics

Town centres are vibrant, dynamic things, and to be useful to those assessing and planning them, TCI has to allow for changes over time. Towns change size, both due to physical changes in their fabric, and due to shifting town centre boundaries based on their changing index of activity (see above). As the boundary moves, a retail location may move into or out of the town centre.

The size of individual retail premises may also change due to extensions or merging / de-merging with adjacent premises. Independents and multiples are analysed and compared within TCI, including data on independents which become multiples the moment they open a second shop. All of these flexibility requirements can be met with the right data structure, but reaching this point has sometimes been an interesting journey.

In human thought processes, we move between wide helicopter views and fine-scale information all the time. For a tool to aid this process, we need it to aggregate data for us and then break them down again. The magic is in how we expand out into huge arrays of data which lend themselves to statistical modelling, and then aggregate the data back into more manageable volumes that are quick enough for downloads and interactive analysis through the web interface.

There’s more about TCI here, or please comment on this article below.

Mapping our food future

Tuesday, June 30th, 2009

Mark Thurstain-Goodwin welcomes publication of a landmark food security study

This week sees the publication of an important paper about future food security. It seeks answers to fundamental questions about how our communities will feed themselves when most food imports from around the world are no longer affordable. Geofutures contributed GIS research and mapping to the project paper, and we’re hoping to move the model onto a national scale.

I first heard Rob Hopkins, founder of the Transition movement, speak to an audience in Bristol in 2007.

He isn’t a big ego, and it wasn’t a glitzy occasion, but the message of the Transition communities is so obviously right. This is where it begins, I thought.

We need to make a transition away from a global economy which is dependent on cheap fossil fuels, because we have reached the peak of their extraction. Indeed, we will make that transition whether we like it or not, because fuel prices will inexorably rise, putting oil and gas beyond our reach well before they run out altogether.

The only question is whether we can effectively plan for it now, understanding what we need to do to make our communities resilient against the changes to come. Alternatively, we’ll experience this transformation through utter chaos – topped up with the impacts of climate change.

Cue the Transition Network, a charity supporting grassroots groups in cities, towns and villages, researching how they can plan and implement their energy descent, calling on expertise from established campaigners, older generations, farmers, craftspeople and other experts to help re-localise some or all of their supply of food, fuel, medicines, building materials, textiles, skills and more.

It’s a strong personal interest for me, but it’s also a professional one. As anyone worth their GIS salt could tell you, this kind of planning is crying out for spatial analysis. We have populations, we have topography, climate and agricultural land types, we have transport networks. To understand what’s happening now and plan for energy descent in future, we need maps.

A map of Totnes and district showing where foodshed analysis suggests re-localised food production could best be located

A map of Totnes and district showing where foodshed analysis suggests re-localised food production could best be located

So on many levels I’m delighted to have the opportunity to work with Rob and his team, putting GIS techniques and mapping to work in a test project for Transition Totnes (the first Transition Town and home to the Network). This builds on our earlier analysis of community food footprints, of which more and a mashup here.

Can we feed ourselves?

The aims of this pilot analysis were first to answer the question ‘Can Totnes and District Feed Itself?’, and second to create the basis for an online model which any community could readily use to answer the same question for its own population.

The answer to the first – plus of course the many other questions which answering it raises – can be found in the project paper. But I thought I’d highlight here a few of the analysis issues which we dealt with, and how we hope the next phase of the project can help.

Data issues

Data availability was a challenge. This isn’t unusual in any study, but the particular issue here is fine-scale information on soil types and land use. In the absence of anything better, we used Defra agricultural land type data to classify where different kinds of food might best be produced around Totnes.

When Cuba encountered its ‘Special Period’ after the collapse of the Soviet Union cut its fuel imports by 80% and local production of food increased many times over, significant within this was micro-production in gardens and balconies, and bringing new space into cultivation such as airfields. Cuba is an extreme example, but it illustrates that our model is only a work in progress, needing much more fine-scale knowledge on potentially productive land, especially urban and woodland, than we now have.

Not out of the woods

Woodland creates its own special questions. This analysis shows that as a source of managed coppice fuel for space heating, the woodland currently available is far too small to meet the needs of every household in the district. Woodland is included in the model as a source of wild meat and biodiversity; the fuel question is not yet adequately answered, and the even more interesting productive potential for woods in the shape of agroforestry also remains to be fully explored.

The fairly coarse categorisation of land types created the potential anomaly within these results that sheep grazing (using the poorest quality land) would take place many miles from Totnes on the edge of Dartmoor. Again, it’s more than likely that pockets of suitable land exist much closer to the town, and we need fine-scale local knowledge to identify them.

Competing foodsheds

The results of the model also highlight the importance of interplay between the foodsheds of neighbouring communities, especially larger centres of population. It will be vital for resources to be shared equitably between cities, towns and villages while production takes place in the most efficient possible locations. In the paper we also point up the need for radical changes in the planning system allowing re-occupation of rural land by local workers.

All of these questions and more will move towards answers if individual Transition communities can get their hands on the Totnes model. This is a network rammed with local, expert knowledge and we need to provide a systematic means to gather, store and share it, while putting the best available technology to work in planning their own communities’ future food production.

Those are the key aims of the next phase of the project: a national roll-out of a refined version of the model, with the means for people to upload land use, productive capacity, soil, microclimate and other data for inclusion in the analysis. I can’t think of a better use of our technology or a more timely call on funding resources.

Transition is well named; we know where we are, and we can start to envisage where we need to get to, but the bit in between is the real problem. Local food networks which will make money for producers in 20-30 years will struggle to compete with supermarkets now. They are not designed for the here and now, but if we don’t bring them into being now it will be too late.

Tools which can help every kind of stakeholder visualise the markets and systems we’ll very soon need will help them come into existence now.

See our mashup of the Totnes foodshed

See Rob Hopkins’ blog, Transition Culture

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