The perception of space can be represented using vector or raster representation models. Both models represent reality differently.
Vector representation model: In this model, a geographic region is represented as points, lines and polygons. Each point has a specific coordinate. This model is very effective for representing objects and features. Vector model uses vector data.
Raster representation model: In this model, a geographic region is perceived as being composed of square cells arranged as a 2-D array or grid (raster data). Each cell is known as a picture element or a ‘pixel’. Each pixel has coordinates and an attribute. The size of the pixel determines the level of spatial detail. The portion of the Earth's surface that the single pixel represents may not be homogeneous, but the pixel will record one single value and all details within a pixel get lost. A raster model is more effective in representing continuous fields than discrete objects.
Vector versus raster models: As mentioned earlier vector and raster models represent reality differently. Vector is better for representing objects and features while raster is better for representing continuous fields.
There is also a basic difference in how vector and raster data are generated. Generally field measurements are vector while images from aircrafts and satellites are raster. Vector is storage effective while raster results in great data volumes. The processing strategies to manipulate vector and raster data, and the tools (software packages) to handle vector and raster data differ.
Overall, the vector model is closer to the way in which the human mind perceives the Earth.