The following examples of vector and raster data demonstrate some of the many forms the data can take.
Vector data in mapping generally appears either as points, lines, or polygons. In this example of polygons as raster data, spatial information tied to the data defines the shape's boundaries while further information (such as a title and image) is included as additional attributes. Attributes can include any type of additional information that is useful for a viewer to know about a particular location appearing in your dataset.
A basemap is a georeferenced raster image. They help give a larger context to vector data sets, which would otherwise simply appear as points, lines, or polygons on a blank space. Satellite imagery and other top-down images (orthophotos) are the most common raster data of this kind, seen, for example, when using satellite imagery from GoogleMaps as seen below.
Raster surface maps contain attributes that mark change over a particular landscape instead of representing the visual world as basemaps do. Common attributes indicated on surface maps include elevation (which is specifically termed a digital elevation map, or DEM), rainfall, or temperature. Once these types of surface maps are imported into a GIS platform like ArcGIS or QGIS, they can be analyzed in a myriad of ways.
Raster thematic maps are similar to surface maps as they use attributes of a particular landscape, be they physical or cultural. Combining several types of data to create what are called thematic data sets, thematic maps group together certain specified attributes from vector or raster data into specific categories, and then mapping out the categories.
The example below shows vegetation types from a dataset that breaks land-cover types into categories. The data is multispectral, meaning it is the acquisition of reflected wavelength data in the visible, near infrared, and short-wave infrared spectrums.
