In GIS, what does the interval category of attributes show?

In GIS, the interval category of attributes is specifically concerned with the magnitude of differences between measurements. This means that when data is assigned to an interval attribute, it reflects numerical differences that are meaningful and consistent across a scale. For example, temperature readings or elevation levels are often represented using interval attributes; the gap between values is significant, allowing for meaningful comparisons and calculations of differences.

The concept of interval data makes it clear that not only can you measure how much more one value is than another, but these measurements have a consistent scale. Thus, statements about the data can be made in terms of how far apart values are from one another, which can provide insights into patterns and distributions.

This is in contrast to other types of attributes, such as categorical data, which simply identifies characteristics without conveying magnitude, or ordinal data, which ranks items without specifying the size of the differences. Understanding interval attributes helps GIS professionals analyze and interpret spatial data in a more nuanced and quantitative manner.