Time in GIS and geographical databases

Representations used historically within GIS assume a world that exists only in the present. Information contained within a spatial database may be added to or modified over time, but a sense of change or dynamics through time is not maintained. This limitation of current GIS capabilities has been receiving substantial attention recently, and the impetus for this attention has occurred on both a theoretical and a practical level. On a theoretical level GIS are intended to provide an integrated and flexible tool for investigating geographical phenomena. The world never stands still. This means that GIS should be able to represent these phenomena in both space and time (see also Veregin, Chapter 12). If GIS are to fulfil their envisioned role as decision-making tools, they will need to represent information in a manner that more closely approximates human representation of geographical space. An important element of human representation of the world around us is the retention of information relating to past events. Cognitive science has shown that the retention and accumulation of such information is essential to deriving more generalised concepts, and of learning in general (Mark, Chapter 7). On a practical level, as a result of widespread use of GIS over the past 15 years and increasing reliance on GIS in everyday applications, users are increasingly encountering the issue of how to keep a geographical database current without overwriting outdated information. This problem has come to be known as ‘the agony of delete’ (Copeland 1982; Langran 1992). The rapidly decreasing cost of memory and the availability of larger memory capacities of all types is also eliminating the need to throw away information as a practical necessity. In addition, the need within governmental policymaking organisations (and subsequently in science) to understand the effects of human activities better on the natural environment at all geographical scales is now viewed with increasing urgency. The emphasis is shifting in natural resource management within the developed world from inventory and exploitation toward maintaining the long-term productivity of the environment. This task requires integrated and broad-scale process analysis in order to understand natural and human processes better and how they are interrelated. Global Circulation Models (GCMs) are currently being used to study climate dynamics, ocean dynamics, and global warming (Simmons and Bengtsson 1988). The need for a more detailed examination and understanding of the dynamics of human–environment interactions at urban and regional scales is also a continuing priority (Hunter and Williamson 1990; Vrana 1989). Diffusion theory (Hägerstrand 1970) has been applied to a diverse range of topics including agricultural innovation,