GIS Data: Spatial vs Attributes

GIS Data is the key component of a GIS and has two general types: Spatial and Attribute data.

Spatial data are used to provide the visual representation of a geographic space and is stored as raster and vector types. Hence, this data is a combination of location data and a value data to render a map, for example.

Attribute data are descriptions, measurements, and/or classifications of geographic features in a map. Attribute data can be classified into 4 levels of measurement: nominal, ordinal, interval and ratio. The nominal level is the lowest level of measurement for distinguishing features quantitatively using type or class (e.g. tree species). Ordinal data are ranked into hierarchies but does not show any magnitude of difference (e.g. city hierarchy). The interval measurement indicates the distance between the ranks of measured elements, but a starting point is arbitrarily assigned (e.g. Celsius Temperature). Ratio measurements, the highest level of measurements, includes an absolute starting point. Data of this category include property value and distance.

Attribute data is the detailed data used in combination with spatial data to create a GIS. The more available and appropriate attribute data used with spatial data, the more complete a GIS is as a management reporting and analysis tool.

Sources of Spatial & Attribute Data

Spatial data can be obtained from satellite images or scanned maps and similar resources. This data can then be digitised into vector data or maintained as raster graphic data. Essentially, any format of a geographical image with location or co-ordinate points can be used as spatial data.

Attribute data can be obtained from a number of sources or data can be captured specifically for you application. Some popular sources of attribute data are from town planning and management departments, policing and fire departments, environmental groups, online media.