However, a map in a GIS can be shrunk or enlarged at will on the screen or on paper. You can zoom in until the screen displays a square metre or less, or zoom out until the screen displays all of BC. This means that geographic data in a GIS doesn't really have a 'map scale'.
The display scale influences two things about a map :
A GIS map's annotation (ie text and symbols) must be designed with a display scale, just like a paper map. There is a range of scale in which it will 'look right', even though it is possible to display it at other scales with the GIS software.
A rigorous statement of accuracy will include statistical measures of uncertainty and variation, as well as how and when the information was collected. Spatial data accuracy is independent of map scale and display scale, and should be stated in ground measurement units.
Generally, a line cannot be drawn much narrower than about 1/2 a millimetre. Therefore, on a 1:20,000 scale paper map, the minimum distance which can be represented (resolution) is about 10 metres. On a 1:250,000 scale paper map, the resolution is 125 metres.
However, most GIS store locations in ground units (eg UTM coordinates, or Longitude/Latitude) with a resolution of a centimetre or less. This resolution is far greater than the uncertainty of any of BC Environment's data.
If a raster coverage is derived from vector linework, its pixels should not be smaller than the uncertainty in the linework. If it comes from an air-photo or satellite image, its pixels should not be smaller than the resolution of the camera that recorded it.
The density of paper map's data is limited by its scale (and therefore its resolution). Areas (polygons) cannot be shown if they are smaller than the lines which draw them. For example, a polygon less than 250 metres wide cannot be drawn on a 1:250,000 scale map. This minimum size also limits the number of polygons that can be represented in a given area of a paper map.
A GIS stores its data digitally, so the minimum size of a feature is limited only by the resolution, which is effectively infinitesimal. Where the degree of detail in a coverage is arbitrary (eg soil polygons), a data definition or convention should specify the minimum size of features, and therefore their density. Without this, different parts of the same coverage may have widely varying degrees of detail, influencing analysis results.
A GIS stores lines (eg, a lake shoreline) as a sequence of point locations, and draws it with the edges that join them. There is no limit to how many points can be stored, or how close together they may be.
The amount of detail on line features should be limited just like data density. It does not make sense to store points at intervals which are shorter than the accuracy of their locations.
Some operations may result in features which are smaller than the data uncertainty. For example, overlaying rivers and forest polygons may create 'slivers' along the riverbanks which are 10 metres wide, when the uncertainty of the data is 20 metres. These slivers should be ignored, or included with their neighbours before the results of the overlay are used for further analysis.
For example, management unit boundaries could be stored in one provincial coverage, and annotation layers could be developed for labelling them at display scales of 1:20,000, 1:250,000, and 1:2,000,000.
If done carefully, this avoids duplication of the same data for display at different scales.
For example, a detailed forest cover map may be generalized by combining polygons with similar characteristics. This reduces the number of objects in the coverage.
Conversely, a detailed ecosystem classification map may be generalized by reducing the amount of detail in the boundaries between regions, without reducing the number of regions.
Generalizing a raster image usually reduces both the number of objects, and the amount of detail.
A GIS coverage should be identified by its accuracy (or uncertainty) and data density (or minimum feature size).