Implementing Spatial Analysis and GIS Applications for Business and Service Planning


Over the past few years there has been a remarkable increase in interest is GIS. Many of the earliest users were in universities, government departments and environmental agencies. Activity in these traditional core areas is now being supplemented by vigorous growth in several emerging markets, the most important one being business and service planning. For many of these new users, the GIS focus to date has been basic mapping and asset management. Other, more advanced, users are modelling data held in integrated databases. This modelling activity is frequently referred to as spatial analysis.



β€œSpatial analysis” is one of those terms that are so widely used in so many different contexts that it is difficult to define succinctly. Good child (1988, p; 68) offers a good general definition of spatial analysis as β€œthat set of analytical methods which require access both to the attributes of the objects under study and to their locational information”. Openshaw (1991b, p. 18) suggests that what geographers refer to as β€œspatial statistics”. Anselin (1989) and Goodchild et. Al (1992) prefer to use the term β€œspatial data analysis” although there seems to be no substantial difference.

Openshaw (1991a, 1991b) argues that the generally accepted origins of spatial analysis lie in the development of quantitative and statistical geography in the 1950s. At this time, the focus in academia was on nomothetic (general) approaches to scientific endeavour. Kubo (1991), however, suggests that Japanese geographers were pioneering the use of spatial analysis in the 1930s. The late 1960s and early 1970s saw a decade of great interest and widespread use of spatial analytical methods by geographers and, to a lesser extent, other environmental and social scientists. During this period, the earlier work on statistical methods was widened to include mathematical model-building with an emphasis on theoretical development rather than on application. In sharp contrast, during the 1980s spatial analysis was largely forgotten by geographers as Marxist and humanistic interests came to the fore. Fortunately, however, there was still considerable interest outside geography. From the low point of the mid-1980s interest in spatial analysis has increased remarkably in the 1990s, largely on the back of the great upsurge in interest in GIS.

All this activity has even cause some commentators to proclaim that spatial analysis has been reinvented by GIS (Openshaw 1991b). The reasons why GIS has contributed to the rediscovery of spatial analysis are many and varied; some of the more significant from the standpoint of proprietary GIS usage by business are as follows.

  1. The last few years have witnessed huge improvements in the price, performance ratio of computer hardware, such that it is now possible to package very high-performance processors in the form of desktop personal computers. This has substantially removed the processing bottleneck restricting spatial analysis which was evident even just a few years ago.
  2. Recently, there has substantially removed the processing bottleneck environment and society brought about largely by advances in data collection methods and technology (e.g. satellite remote sensing, Global Positioning Systems and Electronic Point of Sales in retailing). This has required a major shift in spatial analysis from ideas based on a situation which is data poor to one which is data rich.
  3. GIS also provides spatial analysis two sets of very important tools that allow excellent data management and visualization. It is now inconceivable for spatial analysts to work without access to good tools for data management (e.g. some type of Database Management Systems – DMBS – software) and visualization (e.g. graphical and cartographic drawing software).


These technological developments have led both to a great general increase in using geography as an organizing framework and to the commercialization of GIS.



The focus on data capture, database automation and basic inventory operations in business and service applications of GIS is not altogether surprising, given its relative youthfulness as an application area. Over time it might be expected that business and service planning applications will become more analysis, modelling, and management – oriented. Such trends are commonplace, as the work of Crain and MacDonald (1984) and Maguire (1991) shows. This work suggests that the initial reason for establishing most information systems and, therefore, the main activity in the initial development phase is assembling, organizing and undertaking an inventory of features of interest (e.g. customers, transport networks, population or schools).

The second phase in the evolution of information systems arises from the desire to undertake more complex analytical operations. Frequently these require access to data from several disparate sources and the use of statistical and spatial-analytical techniques to integrate the data.

The third and most developed phase sees the evolution of an information system from a transaction-processing to a decision-support system capable of sophisticated analysis and modelling operations. During this phase there is considerable emphasis on spatial analysis and modelling. Typical applications in a business and service planning context include: determining which hospital or school is to close, given information about patients/pupils, the location of others hospitals/schools, an assessment of likely demand derived from population information, etc.; estimating the optimum route and warehouse location for a trucking company on the basis of information about the volume of goods to be transported, the location of customers and the characteristics of the transportation network; and evaluation of alternative land-use patterns for a new city development, given access to information about the geology and soils, existing land use, transportation routes and planning consents.

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