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Now that this information has been recorded in the database, it is possible to pose questions about connectivity and location. For example:
What polygons adjoin polygon A? To find the solution, we first look to see what arcs define polygon A, then we check to see what other polygons are defined by these arcs in their negative orientation.
What is the shortest route from node 3 to node 2? Trace all arc paths that lead from node 3 to node 2, sum their lengths by calculating distances from node list. Choose path with shortest total length.
What polygon is directly across from polygon B along arc D? Search for the polygon that is defined by the inverse (negative) of arc D.
Arc-node topology, as this is called, was developed several decades ago as a convenient way of store information of this sort. It is used to encode information used in the US Bureau of Census TIGER boundary files and is the basis of the spatial modeling system used by the Arc/Info software system.
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6. Object-oriented Databases
The methods of file organization discussed above depend upon the careful description of real-world phenomena in terms of their attributes, such as height, weight, or age. It is these attributes that are stored in the database and together they provide a sort of abstracted depiction of the real-world feature. Much recent attention has focused on how to organize this information in ways that more readily represent the way users gather and use information about the world around them. That is, humans recognize "objects" immediately in terms of their totality or "wholeness." Houses and skyscrapers are recognized immediately by form and function. The differences can be described in terms of the underlying attributes, but people recognize these from experience.
The idea of "object-oriented" database is to organize information (that is group attributes) into the sorts of "wholes" that people recognize. Instead of "decomposing" each feature a distinctive list of attributes, emphasis is placed on "grouping" the attributes of a given object into a unit or template that can be stored or retrieved by its natural name.
Consider the following situation involving two ways of organizing information about buildings zoned for different uses.
This information can be broken down into attributes, as follows:
Parcel Use Height Minimum Lot Size Maximum Number of Dwelling Units
01-4567 Residential 35 ft 10,000 SF 1
01-5632 Residential 35 ft 7,000 SF 2
04-6781 Residential 40 ft 43,560 SF 23
05-3759 Residential 60 ft 43,560 SF 54
06-3962 Office 40 ft 5,750 SF 0
06-9977 Office 60 ft 5,750 SF 0
To organize this information differently, let us first define some "templates" that reflect the different "objects" we wish to include in the database.
SF Single Family Token 1=Large Lot Token 3=Duplex
MF Multi-family Token 1=Low Density Token 5=High Density
LO Limited Office Must Specify Predominate Use Maximum Height=40 ft Minimum Lot Size=5,750 SF
GO General Office Must Specify Predominate Use Maximum Height=60 feet Minimum Lot Size=5,750 SF
Once these are created, information can be added to our database by referring to the template. The template maintains in one place all attributes held in common by a certain class of object. It may be the case that slight differences exist between objects of a given category. These differences can be stored as "tokens" or additional attributes.
Feature Number Token Description
SF-1 1 Single Family
Height=35 ft
Large Lot
SF-1 3 Family Residence
Height=35 ft
Duplex
MF-2 2 Multi-family
Height=40ft
Low Density
MF-5 5 Multi-family
Height=60 ft
High Density
LO 40 Limited Office
Neighborhood Needs
GO 50 Offices
City-wide Needs
Although templates and tokens may be stored in two different files, it is easy to see how this method of organization changes the database. It is not merely a process of simplication. By using templates, users can enter and retrieve data in terms of "real" items. A query might ask for all "Single Family Houses."
Object-oriented databases thus have the advantage of organizing information in ways that users often find easier to use. The database has as an intuitive feel because it employs that categories that users employ naturally in day-to-day life. For this reason, object-oriented databases are gaining increased attention in GIS.
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7. The Idea of the Expert Systems
If a database has been designed to store information about spatial, functional, and logical relationships, the user can pose more complex questions of the data. That is, the user can program the system to consider a variety of spatial, functional, and logical conditions during query or analysis. Such efforts result in what are termed expert systems or, if carried further, artificially intelligent systems. At there simplest, expert systems allow the user to set "rules" that must be followed as data is analyzed. These rules are written to mirror the way an experienced user would compare or judge data. As more and more rules are written, the system becomes more adept or "expert" at finding solutions with less directed guidance by users.
The point of expert systems is to build sets of rules that reflect the sorts of comparisons and judgments that experienced users would make. By programming these rules into the system, more and more of the work of decision making can be passed on to the computer system--including complex comparisons that may be difficult or time consuming for even experienced users to undertake.
Such systems are of interest to GIS practioners in many fields including urban planning and resource analysis. Complex issues involving zoning and land use can often be written in terms of rules that need to be followed.
At the same time, following rules in only a step toward "intelligence." The difference between expert systems and artificial intelligence is much in debate. But to be truly "intelligent" a system must be able to "learn," "think," or "reason," perhaps really to write its own rules from experience. The definition of artificial intelligence is, in fact, still a contentious issue. So far, it has been very difficult to program computer systems to provide a semblance of human thought processes. Yet, the potential of such systems makes the effort irresistible. The idea that computer systems might one day be able to reason about real- world environmental and geographical problems and issues is a reason why GIS theorists maintain an interest in developments in the area of artificial intelligence.
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8. References and Supplemental Reading
Chapter 2 in Bolstad, Paul. 2005. GIS Fundamentals: A First Text on Geographic Information Systems, 2nd. ed. White Bear Lake, MN: Eider Press.
Burrough, P.A. 1986. Principles of Geographical Information Systems for Land Resource Assessment. New York: Oxford University Press.
Chapters 3-5 in Chang, Kang-tsung. 2006. Introduction to Geographic Information Systems, 3rd. ed. Boston: McGraw Hill.
Chapter 3 in Clarke, Keith C. 2003. Getting Started with Geographic Information Systems, 4th ed. Upper Saddle River, NJ: Prentice Hall.
DeMers, Michael N. 2005. Fundamentals of Geographic Information Systems, 3rd ed. Wiley.
Huxhold, W.E. 1991. An Introduction of Urban Geographic Information Systems. New York and Oxford: Oxford University Press.
Koeln, G.T., Cowardin, L.M., Strong, L.L. 1994. Geographic information systems. in T.A. Bookhout, ed. Research and Management Techniques for Wildlife and Habitats. Fifth Edition. Bethesda: The Wildlife Society Pages. pp. 540-566.
Chapters 3, 5 and 6 in Lo, C.P. and Albert K.W. Yeung. 2002. Concepts and Techniques of Geographic Information Systems. Upper Saddle River, NJ: Prentice Hall.
Chapter 8 in Longley, Paul A., Michael F. Goodchild, David J. Maguire, and David W. Rhind. 2005. Geographic Informaiton Systems and Science, 2nd ed. Hoboken, NJ: Wiley.Antennucci, J.C., Brown, K., Croswell, P.L., Kevany, M.J. 1991. Geographic Information Systems. New York and London: Chapman & Hall.
Walker, J.D., Black, R.A., Linn, J.K., Thomas, A.J., Wiseman, R., and D''Attilio, M.G. 1996. Development of Geographic Information Systems-Oriented Database for Integrated Geological and Geophysical Applications. GSA Today: A Publication of the Geological Society of America 6(3):2-7.
