Integrating Fields and Objects in Geographic Information Science

Describing the world in terms of objects comes naturally to us because our language and our technical analytical tools are highly object-oriented. This works well so long as we confine ourselves to describing situations in which there are well-defined, discrete individuals with clear criteria of identity, but in most real-life situations we are faced with a world of graded transitions and constant flux, in which the picking out of discrete individuals to be the objects of our discourse becomes clearly problematic—and is often acknowledged to be such. This is particularly the case in the geographical domain, where in addition to more or less well-defined objects such as people, buildings, cities, countries, lakes, rivers, roads, and railways (all of which, admittedly, also present identity-related problems), we have to handle numerous fi lds, i.e., functions assigning values of some sort to locations, as exemplified, for example, in maps showing elevation, soil types, land cover, or land use. It has long been recognised that both the field-based and the object-based approaches to describing geographical phenomena are necessary in different circumstances. At one time the dichotomy between the approaches was presented in confrontational terms: i.e., the designer or user of a GIS had to decide which approach to adopt, and having made the decision, was then faced with the task of coercing all geographical phenomena into the descriptive framework provided by the chosen approach. One result of this was that considerable importance was attached to the development of algorithms for converting field data into object data and vice versa. In its simplest form this is essentially an issue of raster-to-vector and vector-to-raster conversion. An example of the former would be, given a field of elevation values, to derive contour lines as objects; and of the latter, given a set of contour lines to assign to each point in the underlying spatial grid an elevation value (either taken from a discrete sequence of elevation ranges, or, using some form of interpolation procedure, to estimate the actual elevation at each point). More recently, it has been recognised that the two approaches must co-exist, and it is generally regarded as an important requirement for a geographical information system to provide the means to handle both field data and object data. There remain, however, important problems concerning the relationships between these two types of data, and there does not at present exist an adequate general theory to handle these. A number of observations are pertinent here. First, it would be incorrect to view the relationship between fields and objects as an equal partnership, with both ways of viewing the world sitting alongside one another, as it were, at the same level. Rather, the field view is in a certain sense more fundamental, existing at a lower level of abstraction; the object view lies above rather than alongside this. Any notion of an object is in some degree an abstraction, requiring the imposition of identity criteria on the underlying (field-type) flux. Some objects may seem to us to be more naturally abstracted from the underlying continua, but this may in part be because they are defined in terms of inhomogeneities that for us are especially salient— whereas for creatures with very different sensory modalities and different ways of life, different sets of inhomogeneities may become salient, leading to the abstraction of different kinds of objects (“carving up the world in different ways”, as it is often said). 1 A simple example is a wall covered with red and green stripes which might appear uniformly coloured to a colour-blind person—but we are all “colour-blind” with