Space, time, and dynamics modeling in historical GIS databases: a fuzzy logic approach (original) (raw)

2001, Environment and Planning B

Context and objectives Space and time are apparently well-known notions but, in order to explain them, they must be connected to other fundamental concepts such as change or process (Hazelton et al, 1992). As stated by Blaut (1961), since relative space is inseparably fused to relative time, nothing in the physical world is purely spatial or temporal; everything is process. Change must be seen as a composite of processes that occur on a wide band of timescale in space. Therefore, the link between space and time is through the process itself, where specific processes determine specific temporal and spatial conceptualization (Chrisman, 1998; Frank, 1998). With the powerful growth of computer capabilities, geographical information systems (GIS) are becoming a new geographical tool capable of dealing with processes by using space and time components of geographical dynamic data. The issue of time in GIS usually involves the question of how to store and manipulate temporal information with spatial information in a digital database (Vasiliev, 1998). The incorporation of the time component in GIS and the ability to reason about change are strongly influenced by three major factors. The first factor is the cartographic influence on the GIS representation of geographic data. Cartographers usually maintain the representation of the continually changing world by making static maps. This practice has been transferred from the analog to the digital world, and the data structures in use today are designed for, and limited to, the static GIS representation of dynamic geographic phenomena (Langran and Chrisman, 1988; Peuquet, 1994). Therefore, the time component in a GIS database remains just an attribute of space. The second factor stems from the nature of historical data. The available data are typically nonideal because data volumes may be large, coming from different sources, expressed using different spatial and temporal scales, and finally determined by circumstances that are, possibly beyond the analysts' control (Openshaw, 1994; Vrana, 1989).