Which statement correctly contrasts raster and vector data models?

Which statement correctly contrasts raster and vector data models?

• A. Raster uses a grid of cells to represent space, while vector uses points and lines to represent features.
• B. Vector uses a grid of cells to represent space, while raster uses points and lines.
• C. Both use the same data structure.
• D. Vector is faster to render than raster in all cases.

Answer: (C)

Space is represented differently in raster and vector models. In raster, the world is divided into a grid of cells, and each cell holds a value that represents the attribute for that area. This makes raster ideal for imagery and continuous surfaces, where all points within a cell share the same value, but it fixes resolution by the cell size and can blur precise boundaries. In vector, space is described by discrete geometries—points, lines, and polygons—defined by coordinates. Features can have precise boundaries and relationships (topology) preserved, with attributes stored in a separate table linked to each feature. This approach is great for representing discrete features and exact extents, and it scales differently because there’s no fixed grid. Because these representations are fundamentally different, they do not use the same data structure. The idea that they share an identical structure isn’t accurate, and rendering performance isn’t universally better for one model in all situations; it depends on data type, size, and the operations performed.

Space is represented differently in raster and vector models. In raster, the world is divided into a grid of cells, and each cell holds a value that represents the attribute for that area. This makes raster ideal for imagery and continuous surfaces, where all points within a cell share the same value, but it fixes resolution by the cell size and can blur precise boundaries.

In vector, space is described by discrete geometries—points, lines, and polygons—defined by coordinates. Features can have precise boundaries and relationships (topology) preserved, with attributes stored in a separate table linked to each feature. This approach is great for representing discrete features and exact extents, and it scales differently because there’s no fixed grid.

Because these representations are fundamentally different, they do not use the same data structure. The idea that they share an identical structure isn’t accurate, and rendering performance isn’t universally better for one model in all situations; it depends on data type, size, and the operations performed.