spatial decision support systems introduction - Management ...

Keenan, P. B. (2003) “Spatial Decision Support Systems,” in M. Mora, G. Forgionne, and J. N. D. Gupta (Eds.) Decision Making Support Systems: Achievements and challenges for the New Decade: Idea Group, pp. 28-39.

SPATIAL DECISION SUPPORT SYSTEMS Peter B. Keenan University College Dublin Keywords Decision Support Systems, Geographic Information Systems, Spatial Decision Support Systems.

INTRODUCTION Spatial decision support systems (SDSS) provide computerized support for decision-making where there is a geographic or spatial component to the decision. Computer support for spatial applications is provided by systems based around a Geographic (or Geographical) Information System (GIS) (Keenan, 2002). Spatial applications represent an area of Information Technology (IT) application with a significantly different history from the other decision-making systems discussed in this book. There are a variety of definitions of GIS (Maguire, 1991), these generally identify a GIS as a computer system that facilitates the display and storage of geographically or spatially related data that allows the integration of this data with non-spatial (attribute) data. A GIS has a sophisticated data manager that allows queries based on spatial location. The GIS interface facilitates interaction with this database. A GIS can be distinguished from a simple map display program that lacks these query features. The acronym GIS has also been used as an abbreviation for Geographical Information Science, referring to a body of research on techniques for processing geographic information. A Geographic Information System employs these techniques. In common usage the expression GIS refers to a computer system, and this convention will be used in this text.


The distinct contribution of GIS to decision-making lies in the ability of these systems to store and manipulate data based on its spatial location. Spatial data is of interest in a wide range of government and business activities. Early areas of GIS application included primary industries such as forestry and mining. An important area of GIS application is the transportation field; both in the design of transport infrastructure and in the routing of vehicles that use this infrastructure. More recent developments have included the use of GIS for location analysis and related problems. These include a variety of business and government applications, such as the siting of public facilities (Maniezzo, Mendes, & Paruccini, 1998) or large retail outlets (Clarke & Rowley, 1995). GIS continues to grow in importance, playing a central role in the provision of new services such as mobile telephony. Mobile commerce is an emerging field, largely distinguished from electronic commerce by the presence of a locational element (MacKintosh, Keen, & Heikkonen, 2001). In this environment the importance of GIS and spatial decision-making systems can only increase.

ORIGINS OF SDSS GIS was first used in the 1950’s in North America, largely for the automated production of maps. The 1960’s saw the introduction of many of the basic concepts in GIS, although their widespread implementation awaited further developments in computer technology. Consequently, more powerful computers were needed, as relatively large volumes of data characterize spatial applications when compared to conventional business data processing. Therefore, the development of sophisticated GIS applications required the introduction of computer systems that had the necessary speed and storage capacity to process queries on the larger quantities of data involved. In the early years of GIS use, these systems required the use of powerful and expensive mainframe computers and could not be easily used in a flexible way.


In the 1970’s the concept of decision support systems (DSS) began to develop in the Information Systems (IS) community, notably with the work undertaken at the Massachusetts Institute of Technology (Gorry & Scott-Morton, 1971; Little, 1971). By the early 1980’s there were many books and papers published in the DSS field (Sprague, 1980) (Alter, 1980) (Bonczek, Holsapple, & Whinston, 1981) and DSS had become a recognized part of IS. DSS had evolved out of the business data processing tradition and usually dealt with the financial and operating data associated with business use. The volumes of data involved with such systems were relatively small compared with those in the geographic domain. As computer systems became more powerful, some DSS type applications evolved that used map display or employed spatial information. A good example is the Geodata Analysis and Display System (GADS) (Grace, 1977) which was used for routing applications. Nevertheless, the technology it used had limited graphics and inadequate processing power to exploit the full potential of spatial applications. While these developments in DSS were taking place in the IS community in the 1970s, a largely separate trend of development took place in GIS, with developments largely concentrated on geographic data processing applications (Nagy & Wagle, 1979). Spatial applications had placed heavy demands on the technology, and this slowed the progression from data processing to decision support applications. However, over time improving computer performance led to increasing interest in spatial what-if analysis and modeling applications. The idea of a spatial decision support system (SDSS) evolved in the mid 1980’s (Armstrong, Densham, & Rushton, 1986), and by the end of the decade SDSS was included in an authoritative review of the GIS field (Densham, 1991). This trend was evident in the launch of research initiative on SDSS in 1990 by the US National Center for Geographic Information and Analysis (Goodchild & Densham, 1993).


Consequently, by the early 1990’s SDSS had achieved a recognized place in the GIS community and was identified by Muller (1993) as a growth area in the application of GIS technology. The delay in the recognition of SDSS, compared to other DSS in other domains reflects the greater demands of spatial processing on IT. Nevertheless, despite these developments SDSS does not occupy a central place in the GIS field; and many introductory GIS textbooks do not mention SDSS at all (Bernhardsen, 1999; Clarke, 1997). This may reflect a feeling among many in the geographic disciplines that SDSS applications involve a diversity of techniques from different fields largely outside the geography domain. Less attention was paid to SDSS within the DSS research community, until the mid 1990’s when some work in this area began to appear (Wilson, 1994). One of the first papers in an IS related publication illustrated the effectiveness of SDSS technology (Crossland, Wynne, & Perkins, 1995). Recently the benefits of SDSS for both inexperienced and experienced decision-makers (Mennecke, Crossland, & Killingsworth, 2000) were discussed in MIS Quarterly.

DEFINITION OF SDSS While an increasing number of GIS based applications are described as SDSS, there is no agreement on what a SDSS exactly constitutes. Partly this reflects the varying definitions of DSS in the DSS research community. However, disagreement on the definition of SDSS also arises from the separation of GIS research from other DSS related research. To a large extent the term SDSS is used in the GIS research community with little reference to the DSS field generally, and this is reflected in the diversity of applications that describe themselves as SDSS. Many widely accepted definitions of DSS identify the need for a combination of database, interface and model components directed at a specific problem (Sprague, 1980). However there is ongoing debate


about the proper definition of DSS, with continuing ambiguity in the use of this term by academics and practitioners. Surveys have shown that many systems described as being DSS generally do not fully meet the definition, while other systems meet the definition of DSS without being described as such (Eom, Lee, Kim, & Somarajan, 1998). In a similar way the term SDSS may be used to describe DSS applications with a simple mapping component where little or no GIS technology is used. The simplest perspective on the definition of SDSS is that a GIS is implicitly a DSS, as a GIS can be used to support decision-making. This type of informal definition is also used in other fields; Keen (1986) identified a trend for the use of any computer system, by people who make decisions, to be defined as a DSS. Many GIS based systems are described as being DSS on the basis that the GIS assisted in the collection or organization of data used by the decision-maker. In this context GIS may have contributed to these decisions, but it is questionable if it can be viewed as a system for supporting decisions. The view of GIS as a DSS derives from the perspective of the limited set of users in geography and related field. For this group, the standard functions of GIS provide the bulk of the information for their decision-making needs. A critical limitation of this point of view is that the ultimate potential for SDSS use greatly exceeds this set of traditional users. The wide range of techniques from operations research, accounting, marketing, etc., needed for this broader set of users is unlikely ever to be included in standard GIS software. A more academic approach is to seek to justify GIS as DSS in terms of the definition of DSS. From this perspective it is possible to argue that a GIS already meets the requirement of being a DSS, as GIS contains an interface, a database and some spatial modeling components. The view of GIS as a DSS has some support in the well-established definitions of DSS. Alter (1980) proposed a framework for DSS that includes data driven DSS that do not have a substantial


model component. GIS could be regarded as an Analysis Information System in Alter’s framework, as the database component, rather than a modeling component, is central to standard GIS software. Mennecke (1997) sees SDSS as an easy to use subset of GIS, which incorporates facilities for manipulating and analyzing spatial data. The view that SDSS is a subset of GIS reflects the need for decision-makers to focus on their specific problem, and their lack of interest in GIS features outside this domain. This view suggests that the techniques needed for SDSS are already within the GIS domain and that a subset of these techniques can be applied to a particular problem. As the features of a standard GIS are directed at the needs of its traditional users, it is this group that is most likely to subscribe to the view of SDSS being merely a subset of the larger GIS field. Some authors in the GIS field have looked to the classic definitions of DSS (Keen & Scott Morton, 1978; Sprague, 1980) and found that GIS lacks the modeling component needed to be accepted as a DSS (Armstrong & Densham, 1990). From this viewpoint SDSS requires the addition of modeling techniques not found in basic GIS software. This position sees SDSS in general, not as a subset of GIS, but as a superset formed by the intersection of GIS and other techniques. This point of view seems to this author to be the most flexible one, where GIS is regarded as a form of DSS generator (Sprague, 1980) to which models can be added to made a specific DSS (Keenan, 1996).

ALTERNATIVE PERSEPECTIVES ON SDSS The different perspectives that exist in relation to SDSS definition can be illustrated by the problem represented in Figure 1. A decision-maker might use the basic functionality of a GIS to identify areas liable to flooding along the banks of a river. This would provide information such


as the area affected by a given rise in the water level or the new width of the river. This information could be the main input required for some types of decision and for this type of decision-maker the GIS software might be said to be acting directly as a SDSS. Another user might wish to identify the sections of road affected by areas liable to flooding along the banks of a river. In turn, this could be used to identify the buildings affected by the flood. The area liable to flood and the relevant road sections could be identified by an appropriate sequence of GIS operations. If this type of decision were made frequently it would be useful to employ a macro to automate the sequence of spatial operations required. Reports could be produced listing the streets in the affected area and quantifying the number of people at risk. One example of the use of a subset of GIS commands to build a specific SDSS might be the inclusion of appropriate reports and customized commands in a set of specific macros. Such a system would employ a database, would use spatial models and an appropriate interface and might be considered to be a DSS in terms of the traditional definitions. This approach has considerable value, but is limited to the functions represented in the macro languages of the GIS software. A more complex problem is to identify an appropriate evacuation sequence and emergency vehicle routing plan for districts that might be affected by flooding (Figure 2). This would require quite complex modeling techniques; the spatial tools of the GIS would provide the input to this analysis. In this case additional modeling software is needed and it must be integrated with the GIS. This additional software might be a separate modeling package or might make use of custom programs written in a third generation programming language. This is an example of extending the GIS by using it as a generator for a SDSS. Emergency evacuation (Cova & Church, 1997; de Silva & Eglese, 2000) is one important example of such a problem, where this type of synthesis is needed and where complicated modeling is required.


A DSS is a specific system designed for a user familiar with the information and modeling aspects of the specific problem. A DSS is not a black box, it should provide the user with control over the models and interface representations used (Barbosa & Hirko, 1980). SDSS users come from different backgrounds and this has implications for the type of system that they use. Those from a geography background have a good knowledge of the data and models underlying the GIS and are generally concerned with activities which predominately use these types of models. Such users will expect to be able to exert effective control over the specialized spatial models in the GIS. This user is most likely to see a GIS, perhaps with some customized macros, as constituting a SDSS. Where GIS is only one component of a more complex decision-making system, the users may have less interest in the purely geographic issues in the system. For this class of decision-maker, the aim of the system builder must be to cater for the problem representation of the user, the logical view of the problem, rather than provide a system too closely related to the physical geographic data. Different users should have different system representations and operations, in a similar way to the concept of subschemas providing a distinctive presentation of a database to a user. This class of user will not be interested in all of the data in a GIS and the full range of GIS operations need not be made available. Different users of a given type of information may be accustomed to quite different presentation formats for the information. This diversity of user requirement places important demands on the design of the components of the SDSS, not only the interface but also the database and modeling components (Grimshaw, Mott, & Roberts, 1997). Flexibility is a key requirement of the GIS software used to build a specific system of this type, as interaction with other software is needed to extend the GIS for the specific problem. A successful


SDSS must provide system builders with the flexibility to accommodate user preferences and allow users employ the form of interaction that they are most comfortable with.

FUTURE PROSPECTS FOR SDSS A number of potential directions can be identified when looking at the future prospects for SDSS development. Improvements in standard GIS software might increase the range of people who could easily use it directly for decision-making. Superior customization features in GIS software might allow easier modification of GIS for specific decisions. Enhanced features for interaction with other software might allow GIS be readily extended to form a large variety of SDSS applications. Future developments are likely to encompass all of these trends, with different groups of users taking advantage of these changes. A number of different categories of GIS software exist. At the top end large powerful packages exist capable of dealing with large amounts of data, for example the ESRI ArcInfo software. This powerful software is not always easy to use for decision-making purposes, but has the capacity to model large geographic areas. Below this level there are a number of user-friendly desktop software applications, for instance ESRI Arcview (ESRI) or Mapinfo (Mapinfo), which are more often associated with decision-making applications. Each new version of these products has additional features and improved interface design, allowing these applications to assist in the decision-making needs of an increasing set of users. Those users who find GIS directly useable will typically use only a few of the many additional features offered, reflecting the viewpoint of SDSS as a subset of GIS. Further development is likely to take place in the design of techniques to make this functionality accessible to less experienced users. This might include the addition of artificial intelligence features to allow the software better implement typical user operations. As


these systems become more capable, more users will find them directly useful for decisionmaking. GIS vendors have recognized the importance of making their software flexible and customizable. Many of the off-the-shelf products are simply one of many possible configurations of the underlying tools with which the software is built. Those wishing to build SDSS, either third parties or users themselves, can provide alternative configurations directed at supporting specific decisions. In a similar way, interfaces are provided for other programs and a variety of third party add-ons exist for specialized purposes. The GIS vendors are moving their products towards commonly recognized standards, for example ESRI, the largest GIS vendor, has moved its products to a Visual Basic for Applications (VBA) based scripting language. All vendors provide products that support popular software interchange standards such as Object Linking and Embedding (OLE). Adherence to these standards has facilitated the development by third party developers of a large range of specialist add-ons for GIS products. For instance add-ons for ESRI products include tools for mapping crime, for managing electricity grids, for planning new road developments and for dispatching fire engines. Another technical development of interest is the extension of GIS techniques to the Internet. Internet standards have some limitations for use in spatial applications, but new software and plugins continue to be developed. Current applications offer map display, but frequently fall short of providing comprehensive GIS functionality. Future developments offer the possibility of a distributed SDSS that could connect with datasets held at distant locations on the Internet. In this scenario multiple specific SDSS applications might use the Internet to share the geographic data that they have in common.


This author suggests, therefore, that SDSS development in the future will predominately use relatively complex combinations of GIS and other forms of DSS tools. SDSS will support a wide range of problems and users, with quite different systems being used in each situation. Spatial applications have largely been used in the past for problems where the manipulation of spatial data was the key or only information component of the decision to be taken. This type of decision required a system that provided users with full control over the spatial operations in the system. This group of users will continue to use these systems and will be able to exploit technology driven enhancements in the capability of GIS. In the future, traditional SDSS applications will be extended to the large number of potential applications where the spatial information is only an interim stage or a subset of the information required for the decision. This will require the construction of systems where users can concentrate on the variables of interest in their decision while other processing is performed without the need for extensive user interaction. These systems will incorporate research and techniques from fields quite separate from the traditional geography based disciplines that initially used SDSS. This may lead to some fragmentation of the SDSS field, a trend long noted in the DSS field generally. This trend will increase the sense of separation between SDSS and the GIS field on which it is based. This reflects similar trends in other decision-making systems where systems draw from fields such as database management or operations research. Decisionmaking applications exploit a synthesis of techniques, without necessarily representing a new breakthrough in the fundamental reference disciplines. Research work continues in new models for these reference disciplines that may in the future be incorporated into decision-making systems. The separation of fundamental principles from applications, Geographic Information


Science for spatial applications, allows a focus on user oriented applications. This will allow new types of user and a wider range of decisions be effectively supported. As the market grows, GIS software will become less expensive and easier to use and will continue to be used directly for decision-making by those in the traditional geo-spatial disciplines. Better integration of models and GIS will extend SDSS applications to a range of applications where GIS has not played a full role in the past. Examples of this would include routing and location problems, which have a long tradition of the use of mathematical techniques. It has long been recognized that these techniques can be greatly enhanced when coupled with the spatial interface and database processing found in GIS software, but this integration still has some way to go. The increased availability of user-friendly SDSS will allow other less technical business disciplines such as marketing to start to exploit spatial modeling for the first time. This will allow exploration of the spatial component of business relationships, which rarely takes place at present.

CONCLUSION Spatial decision support systems represent an important and growing class of decision-making system. SDSS has its origins in disciplines related to geography and will continue to play an important role in these areas. However a wide range of potential applications exist outside the traditional geographic domains. Support can be provided to a much larger range of decisionmakers in these new fields if GIS software can be better integrated with other modeling software. Standard business computers are now powerful enough to run these more complex applications. As the market for spatial information grows, spatial data is becoming more widely available and less expensive. This is providing a critical mass for new applications, in response to these


opportunities GIS vendors are enhancing both the direct capabilities of their software and the potential to integrate that software with other types of software and applications. This will benefit those potential users who currently lack comprehensive computer support for examination of the spatial dimension of their decision-making and who as a result often largely neglect this component of their decisions. This untapped body of potential SDSS users promises a bright future for this class of system.


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Figure 1 : Areas liable to flooding along a riverbank


Figure 2 : Identification of route to visit roads affected by flooding