What type of data represents features as a grid of cells with values?

Raster data represents features as a grid of cells, also known as pixels, where each cell has a value that reflects a measurement or attribute of that feature. This grid structure allows raster data to efficiently represent continuous data, such as elevation, temperature, or land cover, where values can change gradually across space. Raster data is particularly useful in applications such as remote sensing, environmental modeling, and spatial analysis, where capturing variations across a landscape is essential.

In contrast, vector data represents geographic features using discrete geometric shapes like points, lines, and polygons, which are defined by coordinates on a plane. Nominal and interval data refer to different types of statistical classifications and measurement scales rather than forms of spatial representation. Nominal data categorizes items without a meaningful order, while interval data measures values where the difference between items is meaningful but lacks a true zero point. Thus, raster data is the correct choice for representing features as grids of values.