Which operation combines overlapping features and merges their attributes?

The operation that combines overlapping features and merges their attributes is known as a Union. In geospatial analysis, a Union operation takes two or more spatial datasets that share common areas and creates a new dataset that includes all features from the original datasets. It combines both the spatial geometries and the attributes of the features, ensuring that all overlapping areas are represented in the output. This allows for a comprehensive view of the combined data, integrating information from all input layers.

This operation is particularly useful when analyzing complex spatial relationships where features may overlap, allowing for richer datasets that include combined information. In contrast, joining typically relates to combining attribute data based on a common key but does not alter the spatial geometries involved. Merging usually refers to combining similar features into a single feature without necessarily treating overlapping areas distinctly. Clipping, on the other hand, extracts features based on the shape of another dataset but does not combine or merge attributes from overlapping areas.