In remote sensing, which type of data characterizes gradual changes such as temperature?

The correct choice is continuous raster data, which is specifically designed to represent phenomena that change gradually over space, such as temperature, elevation, and other environmental variables. Continuous raster data consists of a grid of cells, where each cell holds a value that reflects a measurement or observation at that location. This allows for smooth transitions and gradients between values, effectively capturing the variability in temperature across different areas.

In contrast, discrete data is made up of distinct and separate values, such as categories or counts, and does not account for gradual changes. Nominal data relates to qualitative categories without any inherent order or ranking, making it unsuitable for representing variable spatial phenomena like temperature. Administrative data typically refers to information collected for regulatory or management purposes, which does not align with the scientific representation of environmental gradients. The capability of continuous raster data to display a gradient makes it the most appropriate choice for modeling gradual changes such as temperature in remote sensing.