Scale in GIS: An overview

Scale has many meanings, but in GIS two are of greatest significance: resolution and extent. Ideally models of physical process would be defined and tested on scale-free data. In practice spatial resolution will always be limited by cost, data volume, and other factors. Raster data are shown to be preferable to vector data for scientific research because they make spatial resolution explicit. The effects of resolution are discussed for two simple GIS functions. Three theoretical frameworks for discussing spatial resolution are introduced and explored. The problems of cross-scale inference, including the modifiable areal unit problem and the ecological fallacy, are described and illustrated.