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CHARACTERIZING GEOGRAPHIC FEATURES

All geographic features on the earth's surface can be characterized and defined as one of three basic feature types. These are points, lines, and areas.

Point data exists when a feature is associated with a single location in space. Examples of point features include a fire lookout tower, an oil well or gas activity site, and a weather station.
Linear data exists when a feature's location is described by a string of spatial coordinates. Examples of linear data include rivers, roads, pipelines, etc.
Areal data exists when a feature is described by a closed string of spatial coordinates. An area feature is commonly referred to as a polygon. Polygonal data is the most common type of data in natural resource applications. Examples of polygonal data include forest stands, soil classification areas, administrative boundaries, and climate zones. Most polygon data is considered to be homogeneous in nature and thus is consistent throughout.


Every geograpic phenomenon can in principle be represented by either a point, line, and/or an area.

GIS Data Structures illustrating the difference between Vector and Raster formats (Adapted from Berry)

Commonly, an identifier accompanies all types of geographic features. This description or identifier is referred to as a label. Labels distinguish geographic features of the same type, e.g. forest stands, from one another. Labels can be in the form of a name, e.g. "Lake Louise", a description, e.g. "WELL" or a unique number, e.g. "123". Forest stand numbers are examples of polygon labels. Each label is unique and provides the mechanism for linking the feature to a set of descriptive characteristics, referred to as attribute data.

It is important to note that geographic features and the symbology used to represent them, e.g. point, line, or polygon, are dependant on the graphic scale (map scale) of the data. Some features can be represented by point symbology at a small scale, e.g. villages on a 1:1,000,000 map, and by areal symbology at a larger scale, e.g. villages on a 1:10 ,000 map. Accordingly, the accuracy of the feature's location is often fuzzier at a smaller scale than a larger scale. The generalization of features is an inherent characteristic of data presented at a smaller scale.

Data can always be generalized to a smaller scale, but detail CANNOT be created !

Remember, as the scale of a map increases, e.g. 1:15,000 to 1:100,000, the relative size of the features decrease and the following may occur:

Some features may disappear, e.g. features such as ponds, hamlets, and lakes, become indistinguishable as a feature and are eliminated.;
Features change from areas to lines or to points, e.g. a village or town represented by a polygon at 1:15,000 may change to point symbology at a 1:100,000 scale.;
Features change in shape, e.g. boundaries become less detailed and more generalized.; and
Some features may appear, e.g. features such as climate zones may be indistinguishable at a large scale (1:15,000) but the full extent of the zone becomes evident at a smaller scale (1:1,000,000).


Accordingly, the use of data from vastly different scales will result in many inconsistencies between the number of features and their type.

The use and comparison of geographic data from vastly different source scales is totally inappropriate and can lead to significant error in geographic data processing.