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23 Using Geographical InformationSystems

Michael Batty

SynopsisGeographical information systems (GIS) are organized collections ofdata-processing methods which act on spatial data to enable patternsin that data to be understood and visualized. In fact, GIS is oftenthought of as software which takes numerical data in map form,stores it in the most efficient way in different types of computerenvironment and allows various techniques of analysis to process thedata and then map them. However, GIS is broader than this,synonymous in some contexts with quantitative geography, and theterm is increasingly being used to refer to ‘geographic informationscience’ which embraces a wide range of mathematical and statisticaltechnique (Goodchild, 1992). This chapter first notes the origins of GISand then defines GIS in terms of the way it represents geographicaldata. The various operations which enable spatial data to be analysedand visualized are referred to as ‘functions’, and this ‘functionality’ isillustrated through ways in which GIS can measure, interrogate andmanipulate maps as data. The power of visualizing data through GISis then discussed and, finally, the chapter presents issues concerningchanges in the technology and its software which are driving the field.The chapter concludes by pointing to the great diversity ofapplications which GIS offers and the impact this is having ongeography, geographers and society at large.

The chapter is organized into the following sections:

• What is GIS? Historical antecedents• How a GIS is organized: representing data• Functionality in GIS: geometric operations, spatial queries and

map algebras• GIS as visualization• Technology and software• Conclusion: applications.

WHAT IS GIS? HISTORICAL ANTECEDENTS

GIS emerged slowly from several origins. As computers became evermore powerful, computer graphics came of age and, from early andsomewhat painful beginnings with large and expensive map-plottingdevices, computer memories reached the point where maps could bedisplayed with ease on the screen. Computer cartography was com-plemented by the development of database theory, specifically forspatial data which involved linking geometry to geography, whilequantitative models and spatial statistics gradually began to mergewith the evolving GIS software (Chrisman, 1988). Remote data acqui-sition through various kinds of aerial and satellite sensing came to belinked with GIS, and today we stand at a threshold where thetechnology is being implemented in everything from hand-helddevices and telephones to software for target marketing and climatemodelling.

It is important to separate technology from theory. At one level,GIS is simply visualizing map data in whatever context, and in thissense, it is little different from much of the graphical computationthat we see everyday on the desktop and across the web. But GIS asgeographic information science is of much wider import for geographyand geographical method. Currently, GIS technology has advanced tothe stage where the focus is no longer on graphical representation perse but on integrating visualization with method so that both quanti-tative and qualitative analysis might be enriched (Longley et al., 2001).The next decade is likely to see some remarkable advances as theoryand technology merge. But we are getting ahead of ourselves andbefore we chart the future of GIS, let us step back and illustrate how aGIS is organized and how it is used to visualize and analyse spatialdata.

HOW A GIS IS ORGANISED: REPRESENTING DATA

Two kinds of data are required. As GISs always have the capability ofdisplaying data in map form, there must be data about the way themap is configured – as boundaries and points, for example. This iscalled digital data. Usually there is more than this, for the map hasfeatures or characteristics – called attribute data – and these data areassociated with the map’s configuration. A good example is a map ofpopulation by local authority area. The boundaries of the local author-ities have to be input as digital data and the population associatedwith each authority is attribute data. There is a further twist to this

Key Methods in Geography410

for there are two different ways of representing the map as digital data.The simplest is to assume all areas are the same, such as if you wereto represent population in grid squares. This is called a raster map.Rasters are particularly useful for data produced routinely as fromsatellites, where the easiest way to record it is by equal areas.However, more realistic configurations of maps are based on pointsand lines which are assembled into objects such as polygons. This iscalled a vector map such as our map of local authority boundaries.Both raster and vector maps have attributes, the raster being asso-ciated with grid squares or often pixels on a computer screen, thevector with irregular areas which are defined by assemblages of pointsand lines. Raster data can usually be entered into a GIS directly asnumbers from the keyboard whereas vector data are usually digitizedusing a mouse-like device called a puck, which is centred on each ofthe points and lines defining the map object in question. Thesedistinctions are shown in Figure 23.1.

Much of GIS technology is concerned with visualizing these datain map form and many low-level GIS functions are buried away in thesoftware, no longer of any real significance to geographical analysis. Infact, there is little difference between raster and vector map data, withmany systems enabling users to integrate and move easily betweeneach. However, GIS really comes into its own when more than one setof attributes is associated with a raster or vector map. The centralorganizing concept is based on treating different sets of attributes asmap layers. It is useful to think of geographical systems as beingrepresented by a series of data layers which can be translated into maplayers, and this leads one to consider ways in which the layers mightbe related. For example, in a raster map we might have layers that dealwith topography, vegetation, geology, agricultural use and so on,where it is useful to relate these variables. GIS enables a first shot at

Source: Adapted from the University of Melbourne’s GIS self-learning tool (http://www.sli.unimelb.edu.au/gisweb/)

FIGURE 23.1 Digital data types: (a) raster map with cells/pixels defining map boundaries; and,(b) vector map representation of the same on a digitizing tablet

Using Geographical Information Systems 411

such analysis by simply displaying the map layers and then by‘overlaying’ them to see if there are common patterns.

Another example might be examining the relation between wherepeople live and where they work. If these are mapped as separatelayers, comparing them will reveal that people do not usually live andwork in the same place. If we do this for a large city, it is likely thiswill reveal the classic pattern of people working at the centre andliving at the edge. To illustrate the use of GIS in this chapter, theexample of Greater London is presented, divided into its 33 boroughs.In Figure 23.2, different layers for the year 1991 are shown: totalpopulation, percentage of households who own their own homes andthe percentage who rent from their local council. The maps showingthese data have been created in the desktop software MapInfo, andthe figure shows the typical desktop a user would see. Apart from theability of this software to display such data in many different mapforms, the real power of GIS comes from being able to associate,combine, analyse and model this data, and this involves us in present-ing the kind of tools that are available within GIS which, in turn, formthe core of geographic information science.

FIGURE 23.2 The digital map base and three map layers – attributes – in the GIS MapInfo


FUNCTIONALITY IN GIS: GEOMETRIC OPERATIONS, SPATIALQUERIES AND MAP ALGEBRAS

The most basic operations of a GIS involve measuring various geo-metric features of the digital map data. Once such data are within aGIS, several of these measuring functions are virtually automatic. Forexample, most GISs have rulers which enable you to measure straightline distances, functions to compute areas of polygons and methods tocount the density of points. There are many functions which derivefrom these, such as the ability to draw areas around points and lines –called buffers – which provide ways of computing ‘nearness’. If net-works are represented within a GIS, there is added functionality tofind the shortest routes. Map projection into many different co-ordinate systems is immediate, for all such functions are routine oncethe map’s geometric data have been represented digitally.

The other set of routine functions within a GIS pertains not togeometry but to the data themselves, and these involve various waysof interrogating it. Spatial queries of the simplest form are usuallyachieved by pointing at some area or point on the map and accessingits attributes directly. Much more sophisticated queries are possible,however, based on concatenating different requests. A typical onemight be of the form: ‘Find all areas on the map which have apopulation density greater than 1000 persons per square kilometre,within 5 kilometres of a main highway, and which are located on landwith slopes less than 1 in 20.’ Such queries can also be developed intoways of producing new data from the basic data layers and thisintroduces one of the most important functions of contemporary GISsoftware, which is called ‘map algebra’ (Tomlin, 1990).

The concept of data layers is useful because it is a particularlysimple way of thinking about how different attributes might becombined. Such combinations are a convenient way of representingnew types of derived data. For example, in the London example, wehave population in 1991 – one of the maps in Figure 23.2 – and we caneasily compute the area of each local authority as there is standardfunction in the GIS to do this. Pi is the population in each localauthority i, Liis the area of each authority and we can then calculatethe density Di = Pi/Li. To do this in GIS, we can invoke a standardcalculator which enables us to plot the map of density by combiningthe data according to this formula. We show the result in Figure 23.3with the typical GIS dialogue boxes used to effect the calculationshown alongside. This is, in essence, map algebra, although in a sensewhat we are doing is ordinary arithmetic on the data and presenting itthrough visualizing the result as a map. This is a powerful but simpleway of thinking about geographical relationships, and a further exam-ple impresses the point.


For London, we have population at two dates in time – 1981 and1991 – which we call Pi(t) and Pi(t + 1). We can easily compute thegrowth rate for each local authority area i as λi = Pi(t + 1)/Pi(t) and,using these rates, we can project the population forward one step attime as Pi(t + 2) = λi Pi(t + 1), Pi(t + 3) = λiPi(t + 2) and so on. Thosefamiliar with ordinary algebra will see that this kind of relation isrecursive and that we can project the population forward any numberof time steps with the assumption of constant growth rates, of course.The formula for this would be Pi(t + n) = λn

i Pi(t) which illustrates the‘compounding’ or exponential nature of the growth. We can illustratethis for London in Figure 23.4 where we show the two populations,

FIGURE 23.3 Computing a map of population density for London boroughs within the GISMapInfo


the growth rates and the population 100 years on from 1981, whichinvolves using the growth rate on each newly computed set of popula-tions some 10 times. In essence, what we have done is to show how asimple population forecasting tool can be built into a GIS by thinkingof this as updating a map of population.

The idea of map overlay is even more extensive. One of the originalareas where GIS was developed was for landscape planning where thetypical problem was to find the suitability of land for different uses(McHarg, 1969). This invariably required different factors to be con-sidered which could be represented as maps, each providing a differentand often contradictory impression of where the most suitable landwas located. Methods for reducing conflict between such factors areusually based on overlaying these maps and often weighting eachfactor differentially to provide some sort of combined suitabilitysurface. This is the classic example of map algebra which is illustratedschematically in Figure 23.5, where we show how maps are weightedand added. Of course, the decision to weight and add in this fashion isnot something that is intrinsic to GIS for it depends on the use to

FIGURE 23.4 Projecting the population of London boroughs for 100 years from 1981. Top left:growth rates from 1981 to 1991; top right: population 1981; middle middle:population 1991; middle left: population in 2081 using 1981–91 growth rates.Legends for these maps in other windows are also shown, as well as a fragment ofthe data attributes table in the bottom right window


which the GIS is put by those involved in such problems (Heywood etal., 1998).

GIS AS VISUALIZATION

As we have been at pains to point out, GIS is not computer cartog-raphy although it may be quite justifiable to use the cartographicfunctions in a GIS to produce maps if many variants of the map arerequired and if the overhead of just entering map data is justified.However the visualization capabilities of most GIS are by no meansrestricted to presenting the two-dimensional map. There are extensivefunctions for presenting different types of 2D map with a distinctionhere between vector and raster, vector maps being associated withthematic, perhaps more abstracted mapping, and raster maps beingmore life-like in appearance. Thematic maps with bars, pies, densitydots and so on to represent various attributes are standard, whileraster maps with various types of hill shading giving the appearance of21

2D (2D with the third dimension simply extruded), and oblique viewsare part of many packages. In fact, although GIS has not been tradi-tionally used for presentation in map design, software is beginning toincorporate tools for good design.

There are usually other graphical functions for visualizing datawithin most GIS. For example, there are drawing capabilities which

FIGURE 23.5 Map algebra: adding and weighting sustainability surfaces based on economicemployment, property values and leisure potential in an area of west London


enable maps and any other graphic to be constructed in the mapwindow. There are usually some graphing facilities. For example,MapInfo is organized around four different graphical ‘views’: the mapitself, of course, but also a graphing routine which enables scattergraphs, pie charts and so on to be presented (of the attribute data) innon-spatial form. The other two views are of the data themselves – thenumeric tables and a layout window which allows the user to placemaps, graphs and tables together on a bigger canvas: a minimal formof presentational design.

The greatest advances in visualization, however, are coming withthe extension of GIS to the third dimension. For a long time GISs havedealt with landscape data, and various techniques of developing 3Dlandscape models are included in some packages such as ArcGIS.However, the move to explicit 3D within GIS indicates the weaknessof conventional forms of 3D representation. Computer aided design(CAD) models, for example, do not have anything like the datafunctionality that GIS has but, increasingly, those involved in 3Dmodelling wish to attribute other data to the 3D geometry, and thenuse query, overlay and spatial analysis techniques in their explorationof such models. An example of what is possible in current desktop GISsoftware is shown in Figure 23.6, where a 3D block model of part ofinner London is illustrated, constructed from population densities atsmall area enumeration district level and displayed within the desk-top GIS ArcView. ArcView is typical of many low-cost GISs in that itcan be upgraded by purchasing plug-ins – add-on modules whichextend its functionality. One of these – 3-D Analyst – enables users toextrude 2D areas into the third dimension, to then pan and zoomaround such 3D scenes, and to navigate through the scene, querying

FIGURE 23.6 Representing attribute data in 3D: population density in small census areas in theLondon Borough of Hackney


the data as one goes. The extensive functionality of 2D data is not yetavailable for third dimension but this will come (Batty et al., 2001).

This kind of tool is providing entirely new ways of visualizingcities and their data, and there is every prospect that, with suchsoftware and their relevant data, a new urban geography of the thirddimension will be constructed over the next 20 years. This is as goodan example as any that the digital revolution is forcing us to thinkabout geographies in very different ways. Finally, the extension to 3Dis likely to see a much greater emphasis on realism being incorporatedinto GIS. It is already quite possible to embed photographs and othermultimedia into such systems, but the idea of rendering 3D scenes tothe highest quality possible is likely to feature strongly in future GIS.This, like much of what already exists, will be driven by the market-place as much as by the science – an illustration once again thatgeography and its methods are influenced as much by the wider socialcontext as by any narrower, theoretical quest.

TECHNOLOGY AND SOFTWARE

Although the technology and software of GIS do not dominate thegeographical science that they support, there are remarkable changesstill being worked out with respect to what this technology is able tooffer. The ability to work graphically with data at immense speed,accuracy and the best visual quality is a remarkable enough phenom-enon in the light of how geographers visualized and explored data ageneration or more ago. But the real impact is on how software isbeing distributed across networks – across the Internet – and howmany new users of geographic data and science are being drawn in byGIS. Extending GIS into 3D is only one cutting edge. Another is theability to explore geographic data remotely using Internet GIS whichlinks digital to attribute data and serves it to users in remote loca-tions. The functionality of such Internet map servers is rudimentarycompared to desktop and workstation GIS but the ability to createmaps on-the-fly is becoming an important service in many domains.Web pages are increasingly being linked to such servers as a wholenew set of uses for maps as part of information in general is beingdevised.

An example of this is in the Internet map server constructed atUniversity College London to deliver information about town centresto those interested in their planning. A simple overlay method basedon the logic illustrated in Figure 23.5 above has been developed but,instead of being on the desktop, this is available through web pages toas many users as the network can handle at remote locations. A mapoverlay procedure has been designed which takes different indicators


of town centre sustainability and enables users to combine these. Thisproduces many data layers which are based on very detailed employ-ment, turnover, rents, floorspace, social composition, consumer pro-files and so on which all have different implications for the economicsustainability of different areas. Users can select, combine and differ-entially weight these to produce new surfaces of sustainability. Thissupports the idea that a very wide range of users with differentviewpoints needs to discuss these issues, and this is helped by thedelivery of information and the need to work actively with it in thisfashion. A picture of the interface to this tool is illustrated in Figure23.7.

Web pages are also being used to deliver geographic data, and GISsare now the main software which enables users of this data to capture,unlock and hence visualize its content. Academic users in the UK candownload digital (boundary) data and census attribute data fromvarious web sites in the UK which provide user-friendly interfaces tomake this painless. Such data are invariably delivered in a choice ofGIS formats which means that a GIS is the essential tool in makingsense of this. Education in GIS is also being delivered as distancelearning through websites as in ESRI’s Virtual Campus project wherestudents/users learn by running exercises from software loaded on

FIGURE 23.7 Combining map layers, as in Figure 23.5, to form indices of urban sustainability inGreater London using Internet GIS through a web browser


their local machine but with the control of the teaching and theexercises – the data, etc. – available at the host site where the edu-cational content is stored. The logic of delivering information in thisway and letting students work with data locally and at their leisure isthe way things will be in the near future, and GIS is in thevanguard.

The development of networked GIS is only one part of the story,however, as GIS is now being linked to other kinds of software atmany different levels of sophistication. There is a facility in thespreadsheet Microsoft Excel, to import maps from MapInfo. Just as itis possible to plot charts in Excel, it is now possible to plot maps.Most GISs have scripting languages that allow users to link variouselements to other software, and there are various ways in which thestandard GISs can be linked to statistical software at one extreme andgraphics software such as CAD at the other. Many of the links areloose although, increasingly, software is merging across the desktopand the net and the days are probably numbered for the standalone all-purpose GIS. Software will increasingly come as different modules tobe plugged together and this will probably mean that the current fadwith the technology will lessen.

CONCLUSION: APPLICATIONS

There is virtually no geographical problem that is not touched by GIS:if not by the software or the system then by the science. Whether ornot GIS is applicable will depend on many things, not least the qualityand extensiveness of the data. If all that is required is computermapping, GIS may not be worth while unless the maps are to bereworked many times. But as in all problem-solving, the problemmust be well formulated for GIS to be of any use. As we have implied,the diversity of application areas is staggering and all we can do in thisconclusion is to point to significant ones. Although GIS came fromlandscape planning and automated cartography, the biggest substan-tive areas currently lie in urban planning and in environmentalanalysis (Heywood et al., 1998). GIS began at rather coarse scales but itis gradually being applied at finer and finer scales and there is everyprospect that entire new professional areas in real estate, architectureand urban design will embrace these tools during the next 10 years.

Niche areas of GIS have also emerged, one of which is ‘businessgeographics’ with a focus on marketing and retailing, utilizing newsources of data on consumers. In terms of physical systems, apart fromremote sensing where GIS and remote sensing (RS) packages are oftentightly linked, there has been less development with the exception,perhaps, of geology and terrain analysis (Bonham-Carter, 1994). Much


of the current functionality deals with networks, spatial data struc-tures and, specifically, more human kinds of analysis than physicalalthough this is changing and there is every prospect that GIS willmake substantial inroads in ecology and related sciences in the nearfuture. There are some areas that GIS has not touched and one ismeteorology. This is largely because such areas have always had theirown software and systems. In fact, where there are already wellestablished models and analytical techniques, GIS has been lessevident in terms of its applications. Transport is another case in point,and this illustrates an important limitation of the approach. GIS isinevitably data driven and this is often a precursor to modelling andsimulation. In this sense, GIS is prior to prediction and design and,although many problems require large arrays of diverse data, thosethat are very focused like transportation planning or weather predic-tion tend to use GIS, if at all, purely as a display medium.

What has not been emphasized yet in this chapter is the differencebetween routine and more infrequent, more strategic uses of GIS.Routine usage is really for rather low-level queries and for scheduling,and much of the future use in hand-held systems, for example, will beof this nature. To an extent, although GIS is used in these areas, muchgeographic software is purpose built and often embodied directly intothe control systems used in such ongoing tasks. In the strategiccontext, the kinds of functions illustrated for map algebra are thosethat are likely to be used. This emphasizes the support to decision-making and planning in the widest sense which again is an area ofincreasing interest and application. Finally, to anticipate the future,within a generation many of the techniques within GIS will havechanged beyond recognition as GIS diversifies and fragments. What iscertain, however, is that most human activities will take place in adigital environment and, in this, GIS-like functions will play an everimportant part.

Summary

• GIS emerged slowly from several origins, uniting computercartography, the development of database theory for spatial data,quantitative models, geostatistics and remote sensing.

• GIS is both technology and theory. At one level, GIS is simplyvisualising map data, but GIS as geographic information science isof much wider importance for geography and geographicalmethod.

• Currently, GIS technology has advanced to the stage where thefocus is no longer on graphical representation per se, but on


integrating visualization with method so that both quantitative andqualitative analysis might be enriched.

• Much of GIS technology is concerned with visualizing these datain map form. The central organizing concept is based on treatingdifferent sets of attributes as map layers.

• The most powerful new features of GIS lie in the ability to gobeyond 2D map visualization into the areas of virtual reality, and tolink GIS with other Internet-based applications.

Further reading

• The textbook by Longley et al. (2001) provides a good introduction, while the biggertwo-volume edited reader by Longley et al. (1999) contains 72 articles on manydifferent aspects of GIS.

• Niche areas are worth exploring – for example, Stillwell et al. (1999) in their chapter on‘GIS and urban design’ explore how GIS might influence small-scale site design.

• A good book stressing applications in physical geography is Burrough and McDonnell(1998).

• The flagship journal with the greatest technical flavour is the International Journal ofGeographical Information Science (IJGIS), while there is a host of magazines, whichappear at least monthly, targeted mainly at the industry but which are useful to seehow the field is developing. The main one at present in the UK is the monthly GEO:connexion.

• There are several really good websites where you can learn about GIS. Visit ESRI’s siteand the Virtual Campus (http://campus.esri.com/). The site at Edinburgh is a goodresource (http://www.geo.ed.ac.uk/home/gishome.html). Our own site at UCL (http://www.casa.ucl.ac.uk/) reports a number of GIS projects. Finally, UK census data can bedownloaded from Manchester (http://www.mimas.ac.uk/) and boundary data fromEdinburgh (http://www.edina.ac.uk/) and read directly into various GIS packages andspreadsheets.

Note: Full details of the above can be found in the references list below.

References

Batty, M., Chapman, D., Evans, S., Haklay, M., Kueppers, S., Shiode, N., Smith,A. and Torrens, P. (2001) ‘Visualizing the city: communicating urban design toplanners and decision-makers’, in R. Brail and R. Klosterman (eds) PlanningSupport Systems: Integrating Geographic Information Systems, Models, andVisualization Tools. Redlands, CA: ESRI Press, pp. 405–43.

Batty, M., Dodge, M., Jiang, B. and Smith, A. (1999) ‘Geographical informationsystems and urban design’, in J. Stillwell et al. (eds) Geographical Informationand Planning. Heidelberg: Springer-Verlag, pp. 43–65.


Bonham-Carter, G.F. (1994) Geographic Information Systems for Geoscientists.Oxford: Pergamon Press.

Burrough, P.J. and McDonnell, R.A. (1998) Principles of Geographical Informa-tion Systems. Oxford: Oxford University Press.

Chrisman, N.R. (1988) ‘The rise of software: a cases study of the Harvard Lab’,American Cartographer, 15: 291–300.

Goodchild, M.F. (1992) ‘Geographical information science’, International Journalof Geographical Information Systems, 6: 31–45.

Heywood, I., Cornelius, S., and Carver, S. (1998) An Introduction to GeographicalInformation Systems. Harlow: Prentice Hall.

Longley, P.A., Goodchild, M.F., Maguire, D.J. and Rhind, D.W. (2001) Geo-graphical Information Systems and Science. New York: Wiley.

Longley, P.A., Goodchild, M.F., Maguire, D.J. and Rhind, D.W. (eds) (1999)Geographical Information Systems. New York: Wiley.

McHarg, I. (1969) Design with Nature. New York: Doubleday-Anchor.Stillwell, J., Geertman, S. and Openshaw, S. (eds) (1999) Geographical Informa-

tion and Planning. Heidelberg: Springer-Verlag.Tomlin, C.D. (1990) Geographic Information Systems and Cartographic Model-

ing. Englewood Cliffs, NJ: Prentice Hall.


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