What term describes the simplification of detailed data for broader understanding?

The term that describes the simplification of detailed data for broader understanding is known as spatial data generalization. This process involves reducing the complexity of geographic information while retaining the essential characteristics of the original data. It allows users to comprehend and interpret spatial patterns and relationships without being overwhelmed by excessive detail.

Spatial data generalization can take various forms, such as reducing the number of features, simplifying geometries, and aggregating data. It is especially important in mapping and cartography, where higher-level representations are needed for effective communication and analysis at broader scales. This technique ensures that vital information is conveyed efficiently while minimizing clutter, thus facilitating better decision-making based on the essential data characteristics.

The other terms have different meanings and applications within the realm of GIS. Data integration pertains to the combining of data from different sources to create a coherent dataset. Data transformation involves changing the format or structure of data but does not directly imply simplification for understanding. Georeferencing refers to the process of associating spatial data with a specific location in the real world, which is separate from the conceptual simplification of information.