Geodemographic analysis and Mapinfo

By Debra Jefferies

Module: Geographical InformationSystems

Programme: BSc Computing Portfolio

Lecturer: Beverley Holland

26 February 2014

Contents

Graphical Information Systems....................................1Introduction....................................................1Visual perception...............................................1Geographical Information........................................2Why use Graphical Information Systems...........................3

Acquisition of data..............................................5Interpretation and Analysis of MapInfo results...................6First year MMR uptake...........................................7Second year MMR uptake..........................................8Townsend Index for Swansea and Gower............................9Analysis of results............................................11Targeting public awareness and education.......................11

Conclusion......................................................11References......................................................14

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Graphical Information SystemsIntroductionThe objective of this paper is to develop a case study whichhighlights the use of graphical information systems as a tool forsimplifying large numeric datasets into a pictorial format whichthe human brain is more adapted to understand. In particular thiscase study will be based on data obtained from the UK Data Serviceand the Wales NHS Statistics website, which will be used toestablish if there is a link between deprivation and low MMRuptake.

Before examining how the datasets are transformed into pictorialformat we need to understand some of the basic concepts of how thehuman brain perceives and interpret information.

Visual perceptionThe manner in which humans perceive the surrounding environment isthrough the five primary senses of sight, hearing, taste, smelland touch. Of these five senses, sight is the sense which we usethe most when examining our surroundings. Vision can be thoughtof as providing a series of static pictures which are delivered toour brains and could be thought of as being equivalent to theframe rate which we associate with television.

A picture on its own does not convey any useful information.Rather, it is how our brains process it.

“Our eyes and brains work as a team to discover meaningfulpatterns that help us make sense of the world.”

[109]

Few [109] states that the process of visual perception consists ofthe following stages

Stage 1: Parallel processing to extract low-level properties of the visual scene

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Stage 2: Pattern perception Stage 3: Sequential goal-directed processing

A simple example which we can use to highlight the perceptualdifferences in how we perceive information can be found bycomparing the same set of percentages both as a table of figuresand as a graphical pie chart. We are more likely to recognise therelationships between the values by examining the pie chart asopposed to looking at a set of numeric values.

As the amount of numerical data increases it becomes increasinglydifficult for our brains to make any meaningful sense of theinformation when expressed as purely numeric data. By translatingthese large datasets into pictorial format we are better able tomake sense of them.

It is not enough to simply represent large data sets in pictorialformat, we also need to select the most suitable pictorial format.Longley et al [110] highlights this with respect to infection byWest Nile virus by stating

“GIS is a key component of the virus-spread monitoring processbecause it allows data to be analysed and visualised geographically.This is a new capability that has allowed medical staff to understandand mitigate the spread of the virus”

Geographical InformationGraphical Information Systems (GIS) is a subset of the muchbroader domain known as Geoinformatics. Another popularised areaof this domain is known as Geospatial Intelligence which isutilised to a very large extent by the military and governmentsall over the World. For those who have never heard of these terms,they are more likely to recognise through the use of suchdisciplines when using technologies as Goole Earth. From a morebusiness centric viewpoint there are professional level servicessuch as Google Earth and Maps Enterprise [101] and Google EarthPro [102].

The key concept of these services provided by Google isillustrated below [101].

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Whilst on the Google Earth Pro site they state:

“Google Earth Pro is a 3D interactive globe that can be used to aid planning,analysis and decision making. Businesses, governments and professional usersfrom around the world use Google Earth Pro data visualisation, site planningand information sharing tools.”

[102]

Whilst Google possess this vast repository of information,businesses which look to use geospatial data use professionalservice by well-established specialist companies in this fieldsuch as Mapinfo.

The introduction and use of computer GIS stems from the late 1960sthrough to approximately 1975 which is considered by some [103] toencompass the pioneering age of this technology. The authorssuggest that the scarcity of anecdotal evidence to support this isdue to

“… few organizations have given have given any thought to formalizing thehistory of their involvement in GIS ...”

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Closely followed by

“… at least one major player (Ordnance Survey) has refused to let its detailedrecords be examined by external researchers.”

The same is stated with regards to businesses specialising in thisfield.

Why use Graphical Information SystemsThe manner in which we as humans view the world around us isprincipally through the use of sight. We have excellent cognitiveabilities when viewing information presented not as a large volumeof numeric data but rather when it is presented in graphical orpictorial format. This perspective is supported by

“Patterns recognition is the fundamental human cognition or intelligence,which stands heavily in various human activities.”

[104]

A simplified example of this can be extended to what is sometimesdescribed as the simple act of reading.

National Geographic describe GIS as:

“GIS can show many different kinds of data on one map. This enables people tomore easily see, analyse, and understand patterns and relationships.”

[105]

Whilst the esri website states the following

“A geographic information system (GIS) integrates hardware, software, anddata for capturing, managing, analysing, and displaying all forms ofgeographically referenced information.”

[106]And of modelling and simulation in geographic information scienceBatty [107] states that successful modelling depends

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“… on our theoretical understanding of the system of interest and theirimplementation in software which links their digital representation to availabledata.”

[107]

The manner in which geographically referenced data displayed andcorrelated change achieved through the use of multiple layers asshown by the following example.

[105]

Such layered representation which utilises the concept of layereddata representation will aid in the process of identifyinginfluencing factors but only insomuch that we possess innerknowledge regarding the nature of the primary factors ofimportance. The identification of similar or suggested

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correlation between data sets allow us to postulate potentiallinks, which then have to be ratified and justified. For exampleit could be suggested that because the local football team has apredominantly red strip, this does not means that supporters wouldbe far more likely to buy red cars. What would probably be trueis decision making factors would be more down to advertisingcampaigns used to promote purchases.

Goodchild [108] highlights the use of polygon overlays stating

“… Polygon overlay is much more than simply drawing the two maps on top ofeach other and allowing the user’s eye and brain to combine them, anoperation variously known as a form of mashup or more traditionally visualoverlay.”

[108]

Acquisition of data The information which has been used within this case study hasbeen obtained from official government sources.

The maps were obtained from UK Data Service [113] and the datatables for Year one and year two MMR uptakes was obtained fromHealth maps Wales [114]

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Interpretation and Analysis of MapInfo resultsWhen looking at large sets of data in tables as numbers it is verydifficult to recognise trends and patterns. As previouslydiscussed, we are better suited to understanding information whendisplayed as a graph or picture. MapInfo allow us to displaythese large numeric data tables as a picture. To help us to moreclearly understand how these numbers relate to geographicallocations, MapInfo allows us to overlay the pictorial data withindefined boundaries on the map. In the case of the following maps,these boundaries indicate different Wards in and around Swanseaand Gower.

The following maps show information relating to the uptake of theMMR vaccine during the first year which is when the vaccine wasfirst taken up by the population. The second map is used toindicate the levels of MMR uptake in the second year. The thirdmap shows the calculated Townsend Index for the same areas.

Whilst the figures showing the level of MMR uptake in both thefirst and second years are shown independent of one another, theTownsend index only needs to be calculated once not only becausethe two MMR uptakes are only separated by a year, but also becausethe Townsend Index is a calculation which represents the level ofdepravation. In order for the Townsend index to show any realchanges then large proportions of the population would either haveto lose most of their jobs or suddenly obtain jobs or morefinancially awarding jobs which would significantly alter theirincome and level of disposable income which helps indicate thestandards of living for the residents.

The following maps will show the three separate sets of data usingdifferent shapes which are overlaid. To indicate different levelsof the data, different colours have been used where each colourrepresents a small range of values. The ranges of these valuescan be seen in the legend for each set of data.

When entering data into MapInfo, each set of data is placed on itsown layer whilst the map is also placed on its own layer. This

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allows us to simply turn on any layers that we want to examinewhile the rest of the layers can be turned off so as to minimisevisual confusion. By changing the state of these layers betweenoff and on we can more easily recognise any similarities in thepattern of the data.

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First year MMR uptake The following map of Swansea and Gower shows the boundaries of theconstituent wards which make up the region. These boundaries havebeen used to bring together MMR first year uptake as published byHealth Maps Wales. Ward boundaries provide a convenient means ofgrouping this information.

Figure 1MMR first uptake legend

Figure 2MMR first uptake map overlay

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The perceived standard of living within the wards is not onlyreflected by people’s perception of an area but also by the costof purchasing a property, which in itself is a non-formalisedstatement of level of depravation. By looking at the legend and comparing the coloured stars we areable to see the level of uptake of the first MMR vaccine organisedgeographically by boundary lines. The highest level of uptake isindicated by the green stars and the lowest uptake is shown by thered stars.

Second year MMR uptakeFrom this second map we can see a very similar distribution of thesecond year MMR uptake using the same geographical boundaries asthe first map. Even though the same colours are used within boththese maps to represent uptake of the MMR vaccine, it should benoted that these second year group values are significantly lowerthan the group values from the first map.

Figure 3Year 2 MMR uptake

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Figure 4MMR second uptake map overlay

The reduced group values for the second year uptake of the MMRvaccine might be explained as being the normalised uptakestatistics whilst the first year uptake results are likely to havebeen skewed due to the recently released reports of the measlesepidemic which arose in and around Swansea and Gower at a timeprior to these results being compiled. This large uptake couldtherefore represent a blip or spike which lie above what wouldnormally be expected due to extensive coverage by the media whichwas responsible for raising public awareness and potentiallycreating an air of worry and panic within the population.

Townsend Index for Swansea and GowerThe Townsend Index which was developed by Peter Townsend whichuses up to 60 indicators relating to the populations style of

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living which is used as a measure of social and financialdeprivation.

“Individuals, families and groups in the population can besaid to be in poverty when they lack the resources to obtainthe types of diet, participate in the activities, and have theliving conditions and amenities which are customary, or atleast widely encouraged or approved, in the societies to whichthey belong. Their resources are so seriously below thosecommanded by the average individual or family that they are, ineffect, excluded from ordinary patterns, customs andactivities.”

[111]

The Townsend deprivation index is constructed from the followingcensus information [112]

Households without a car

Overcrowded households

Households not owner-occupied

Persons unemployed

The index is calculated using the following procedure:

Raw values of unemployment and overcrowding percentages are normalised throughthe use of a log transformation. This is done because the values tend to behighly skewed.

The variables are then standardized using a Z-score which is calculated bysubtracting the mean value and dividing by the standard deviation.

The Townsend deprivation index is now calculated by adding together thestandardised scores.

Normally we would associate negative values as being bad, this however is not trueof the Townsend Index where negative values indicate social wealth and goodstandards of living. The larger the negative index number the higher the standardof living. This means that the higher the positive index value the greater thedeprivation. Positive values of the index will indicate areas with high materialdeprivation, whereas those with negative values will indicate relative affluence. Ascore of 0 represents an area with overall mean values.

From figure 6 on the next page we can see that with regard to the Townsenddeprivation index that there appears to be a higher level of poverty centred on the

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more densely populated area of Swansea and there is generally a higher level ofwealth in and around the more rural areas of Gower.

It is true to say that the majority of people within the areas covered by the maplive more central to Swansea and that the larger Gower areas have a lower populationdensity. The large differences in population are smoothed out by the calculation ofthe Townsend index.

Figure 5Townsend Deprivation Index

Figure 6Townsend deprivation index map overlay

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Analysis of resultsComparing the first and second year MMR uptake maps against theTownsend index map we can see that the more affluent areasgenerally have a higher uptake than the more deprived areas in andaround Swansea. The exception appears to be centred on south andsouthwest Gower which can be seen to have a much lower uptake ofthe MMR vaccine despite a higher standard of living compared tothe more central areas of Swansea.

Lower uptake of the vaccine in South Gower might be because thepopulation density is much lower as would be expected in ruralareas. Looking at North Gower there is a greater density ofpopulation as would be expected for areas such as Gowerton andGorsienon both of which appear to be more affluent as indicated bythe Townsend index.

Located in the urban areas in and around Swansea the TownsendIndex reveals relatively high levels of deprivation as shown bythe red and orange shaded areas on the map. Looking at the firstand second year MMR uptake we can generally see a similarity ofpoor uptake to the deprived areas. It can also be seen whencomparing these three maps that there are small wealthier areasshown in green.

It could be argued that the Townsend Index can be used to projectthe level of uptake of the MMR vaccine based on the wealth of thearea. This appears to hold true for the urban areas but does notnecessarily hold the same meaning for urban areas.

Targeting public awareness and educationBased on the demographic information in conjunction with the MMRvaccine uptake results the health authority and Swansea CountyCouncil would be well advised to formulate their public awarenessand education strategy along two different tracks. Thesestrategies would differ between urban and rural areas.

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With regards to urban areas with relatively high populationdensity the thematic maps of vaccine uptake when compared with thethematic Townsend deprivation index map strongly suggest a closecorrelation between the level of deprivation and the uptake of theMMR vaccine.

It might have been expected in light of urban results that thelevel of deprivation might be the major contributor with regardsto vaccine uptake. However, the thematic MMR vaccine mapsindicate that there was poor uptake of the vaccine in rural areaswhich have much lower levels of deprivation. The most likelyreason for this poor uptake is that whilst these areas aregenerally more affluent they are geographically separated intosmall clusters of population. It might be seen from this thatpeoples decision to receive the vaccine might be linked to thedistances that they would have to travel combined with socialsegregation.

Conclusion The findings of this investigation suggest that despite thestandard of living being indicated by the Townsend index that wealso have to take into account whether or not the area which isbeing looked at is urban or rural. Rural areas which have smallerpopulation densities appear to be slower in the uptake of the MMRvaccine. This in turn suggests that the health authority placegreater emphasis of creating public awareness has to set a higherpriority and publicity which specifically targets not only thedeprived urban areas but also the more wealthy rural areas.

Having potentially identified a split of uptake of the MMR vaccineinto two broad categories; urban and rural, as well as a subcategory based on the Townsend deprivation index within the moredensely populated urban areas. It should be noted at this pointthat extreme care should be undertaken when identifying potentialunderlying causes such as been suggested in this report. Thecomplexity of relationships between cause and effect, usually is aresult of a great number of underlying variables of which theTownsend deprivation index uses only four.

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Based on these findings whilst making the distinction between notonly deprived areas as shown by the Townsend index

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References101 Google Earth and Maps Enterprise, Enterprise ready technology

for your geospatial date; accessed: 02-02-2014; available from http://www.google.com/enterprise/earthmaps/enterprise-technical.html

102 Google Earth Pro; accessed 02-02-2014; available from http://www.google.com/intl/en_uk/enterprise/mapsearth/products/earthpro.html?utm_source=google&utm_medium=cpc&utm_campaign=EMEA-LCS-2013-Geo-Products-EarthPro-HouseAds&utm_term=%2Bgoogle%20%2Bearth%20%2Bpro&utm_content=SearchAd&gclid=CNKn75itrrwCFRDLtAod8W4A4w

103 The History of GIS, by JT Coppock and DW Hind; accessed 02-02-2014; available from http://www.grossmont.edu/judd.curran/History_of_GIS.pdf

104 Theory of Cognitive Pattern Recognition, by Youguo Pi, WenzhiLiao et. al. ; accessed 02-02-2014; available from http://www.intechopen.com/download/get/type/pdfs/id/5795

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106 What is GIS? Esri; accessed 02-02-2014; available from http://www.esri.com/what-is-gis/overview

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108 Spatial Thinking and the GIS User Interface, International Conference: Spatial Thinking and Geographic Information Sciences 2001, Department of Geography and Center for SpatialStudies, University of California; by Michael F Goodchild; Published by Science Direct; accessed 02-02-2014; available from http://ac.els-cdn.com/S1877042811013255/1-s2.0-S1877042811013255-main.pdf?_tid=1f7059bc-8c66-11e3-8567-00000aacb35f&acdnat=1391385779_8303ba0aff21bd35d8f5ea4540ab293a

109 Visual Pattern Recognition, Meaningful Patterns in Quantitative Business Information, by Stephen Few, published by Perceptual Edge, 25 November 2006, Accessed 18/02/2014, available from http://www.perceptualedge.com/articles/Whitepapers/Visual_Pattern_Rec.pdf

110 Table 17.1; examples of tangible and intangible benefit typesfor public and private organisations; Geographic Information Systems and Science, Third edition, 2011, p.433, written by Longley, Paul A, Goodchild, Michael F, et al, Published by John Wiley and Sons,

111 Deprivation and Poverty, Poverty and Social Exclusion; Available from http://www.poverty.ac.uk/definitions-poverty/deprivation-and-poverty ; Accessed 25/02/2014

112 Townsend Deprivation Index, Geographical Referencing Learning; Published by School of Geography, University of Southamton, Published in 2008; available from http://www.geog.soton.ac.uk/geo-refer/go3_142_c15p19819999snsw.html ; Accessed 25/02/2014

[113] UK Data Service; available from: http://borders.edina.ac.uk/html/boundary.html, Accessed 25/02/2014

[114] Health Maps Wales, Immunisations; available from https://www.healthmapswales.wales.nhs.uk/IAS/dataviews/view?viewId=76 , Accessed 25/02/2014

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