Which of the following best describes vector data in GIS?

Vector data in GIS is characterized by its representation of discrete features in the real world, using geometric shapes such as points, lines, and polygons. Points can represent specific locations, such as a city or a tree; lines can depict features like rivers or roads; and polygons can illustrate areas, such as lakes, land parcels, or any bounded region. This structure allows for a highly detailed and precise representation of geographic elements and their relationships.

The structure of vector data is particularly advantageous for analyses that require an understanding of the spatial relationships between different features. For example, one could analyze how close different schools are to each other or determine the area of land used for agriculture. The ability to attribute data to each feature within this framework further enhances the analytical capabilities, enabling users to query and manipulate the data effectively.

Other options describe aspects of GIS that do not align with the definition of vector data. Continuous data, like temperature, is better represented by raster data rather than vector. Additionally, raster images pertain exclusively to grid-based data formats and do not fall under the vector category. Lastly, the statement about vector data not representing spatial relationships is incorrect, as a primary strength of vector data lies in its ability to depict and analyze such relationships.