Explain what geographic phenomena are, their spatial and temporal aspects and the relationship between the type of phenomena and their computer representation (level 1 and 2 according to Bloom’s taxonomy).
Where shape or size of areas matter, the notion of a boundary comes into play. This concerns geographic objects but also the constituents of a discrete geographic field. Location, shape and size are fully determined if we know an area’s boundary, and thus the boundary is a good candidate for its representation. This especially applies to areas with naturally crisp boundaries. A crisp boundary is one that can be determined at an almost arbitrary level of precision, dependent only on the data-acquisition technique applied. Fuzzy boundaries contrast with crisp boundaries in that a fuzzy boundary is not a precise line, but is rather, itself an area of transition.
Discrete fields divide the study space in mutually exclusive, bounded parts, with all locations in one part having the same field value. Discrete fields are intermediate between continuous fields and geographic objects: discrete fields and objects both use “bounded” features.
When a geographic phenomenon is not present everywhere in the study area, but somehow “sparsely” populates it, we look at it as a collection of geographic objects. Such objects are usually easily distinguished and named, and their position in space is determined by a combination of one or more of the following parameters:
As time is the central concept of the temporal dimension, a brief examination of the nature of time may clarify our thinking when we work with this dimension:
In a continuous field, the underlying function is assumed to be “mathematically smooth”, meaning that the field values along any path through the study area do not change abruptly, but only gradually. Good examples of continuous fields are air temperature, barometric pressure, soil salinity and elevation. A continuous field can even be differentiable, meaning that we can determine a measure of change in the field value per unit of distance anywhere and in any direction. For example, if the field is elevation, this measure would be slope, i.e. the change of elevation per metre distance; if the field is soil salinity, it would be salinity gradient, i.e. the change of salinity per metre distance.
A geographic field is a geographic phenomenon that has a value “everywhere” in the study area. We can therefore think of a field as a mathematical function f that associates a specific value with any position in the study area. Hence if (x, y) is a position in the study area, then f(x, y) expresses the value of f at location (x, y). Fields can be discrete or continuous.
In a discrete field, the study area is divided in mutually exclusive, bounded parts, with all locations in one part having the same field value.
In a continuous field, the underlying function is assumed to be “mathematically smooth”, meaning that the field values along any path through the study area do not change abruptly, but only gradually.
A GIS operates under the assumption that the spatial phenomena involved occur in a two- or three-dimensional Euclidean space. Euclidean space can be informally defined as a model of space in which locations are represented by coordinates—(x, y) in 2D and (x, y, z) in 3D space—and distance and direction can defined with geometric formulas. In 2D, this is known as the Euclidean plane. To represent relevant aspects of real-world phenomena inside a GIS, we first need to define what it is we are referring to. We might define a geographic phenomenon as a manifestation of an entity or process of interest that:
item can be named or described;
item can be georeferenced; and
item can be assigned a time (interval) at which it is/was present.