In the practice of spatial data handling, one often comes across questions like “What is the resolution of the data?” or “At what scale is your data set?” Now that we have moved firmly into the digital age, these questions sometimes defy an easy answer. Map scale can be defined as the ratio between the distance on a printed map and the distance of the same stretch in the terrain.
A 1:50,000 scale map means that 1 cm on the map represents 50,000 cm (i.e. 500 m) in the terrain. “Large-scale” means that the ratio is relatively large, so typically it means there is much detail to see, as on a 1:1000 printed map. “Small-scale”, in contrast, means a small ratio, hence less detail, as on a 1:2,500,000 printed map.
Digital spatial data, as stored in a GIS, are essentially without scale: scale is a ratio notion associated with visual output, such as a map or on-screen display, not with the data that was used to produce the map or display. When digital spatial data sets have been collected with a specific map-making purpose in mind, and all maps have been designed to use one single map scale, for instance 1:25,000, we may assume that the data carries the characteristic of “a 1:25,000 digital data set.”
There is a relationship between the effectiveness of a map for a given purpose and the map’s scale. The Public Works department of a city council cannot use a 1:250,000 map for replacing broken sewer pipes, and the map of Figure 1 cannot be reproduced at scale 1:10,000.
Maps that show much detail of a small area are called large-scale maps. Scale indications on maps can be given verbally, such as “one-inch-to the- mile”, or as a representative fraction like 1:200,000,000 (1 cm on the map equals 200,000,000 cm (or 2000 km) in reality), or by a graphic representation such as the scale bar. The advantage of using scale bars in digital environments is that its length also changes when the map is zoomed in, or enlarged, before printing. Sometimes it is necessary to convert maps from one scale to another, which may lead to problems of cartographic generalization.
Spatial and temporal scales can not only be attached to processes, but also to observations. An example is given below, which summarizes the spatial and temporal scales of a few well-known Earth observation systems.
Scales of RS observations
Sensor Spatial scale Temporal scale
Meteosat Hemisphere 15 minutes
NOAA-AVHRR 3000 km daily
Landsat TM 180 km 16 days
Spot 60 km 26 days (pointable)