What does data normalization do in GIS?

Data normalization in GIS involves adjusting data to bring it to a common standard, which is crucial for ensuring accurate comparison and analysis across different datasets. This process may include standardizing formats, units of measurement, and categorical values so that disparate sources of data can be effectively integrated and analyzed together.

When data from various sources are brought together in a GIS environment, they may be recorded in different formats or might use varying terminologies for the same phenomena. Normalization helps to create consistency, making it easier to conduct analyses that depend on uniformity, such as spatial analysis, statistical assessments, or comparison of attributes.

The other options present different concepts that do not accurately describe the function of data normalization. For example, increasing data size refers to enhancing detail, which can lead to storage and processing challenges rather than facilitating a common standard. Creating visual representations is associated with cartography and visualization techniques rather than the normalization process itself. Finally, storing data in multiple formats pertains to data accessibility, which is an entirely different aspect of data management focused on how data is stored and retrieved rather than how it is standardized for comparison and analysis.