What defines spatial data?

Spatial data is defined as data that incorporates the location of a feature or phenomenon. This type of data not only provides information about the characteristics or attributes of an object but also includes its specific geographic coordinates or geographic relationships to other objects. By integrating location into the data, spatial data allows for mapping and analyzing patterns, relationships, and trends in a way that is not possible with non-spatial datasets. For example, a database containing the location of schools and their respective populations is utilizing spatial data, where each school’s position is critical for geographic analysis.

The other options lack this crucial element of location. Numerical data alone does not convey any spatial relationship, and textual information may describe features but does not inherently provide location context. When data is said to be unrelated to real-world features, it means that the data lacks any geographic relevance, making it non-spatial by definition. Thus, understanding that spatial data is fundamentally characterized by its connection to geographic locations clarifies its importance in fields such as geography, urban planning, and environmental science.