Continuous rasters are characterized by what type of data points?

Continuous rasters are characterized primarily by floating-point data. This type of data allows for a range of real numbers, which is essential for representing continuous phenomena, such as temperature, elevation, or precipitation levels across a geographic area.

When working with continuous rasters, the values can represent measurements that vary smoothly across space, providing a more accurate representation of real-world variations than discrete data types. Floating-point data supports decimal values, enabling the representation of intermediate values, which are often crucial for analyses that require precision in measurement.

The other types of data listed—integer, binary, and nominal—do not adequately capture the nuances of continuous data. Integer data is typically used for discrete rasters where values are whole numbers, binary data represents only two states (such as presence-absence), and nominal data classifies information into categories without a quantitative value. Therefore, floating-point data is particularly suited for the nature of continuous rasters in a GIS context.