Which attribute category in GIS is used to differentiate one item from another?

The attribute category in GIS that is used to differentiate one item from another is nominal. Nominal data is categorical and used for labeling variables without any quantitative value. It includes distinct categories that do not have a specific order or ranking; for example, types of land use (such as residential, commercial, and industrial), colors on a map, or different species in a biological survey.

Nominal attributes are vital in GIS because they allow users to categorize and identify features based on names or labels rather than numeric descriptions. This differentiation is essential for organizing data, performing analyses based on category, and visualizing data layers in mapping software.

In contrast, ordinal, interval, and ratio data involve numerical values or rankings, where ordinal represents ordered categories, interval signifies measurements with defined distances but without a true zero, and ratio includes measurements with a true zero point. These attribute types serve different purposes in analysis but are not specifically geared toward simple differentiation as nominal data is.