FME can join features based on attribute values or spatial relationships.

FME can join features based on attribute values or spatial relationships.

• A. Sometimes
• B. Not sure
• C. False
• D. True

Answer: (D)

FME can combine features using two main approaches: matching by attribute values or matching by spatial relationships. When you join by attribute values, features from two datasets are paired when a chosen key or set of keys (like an ID field) match, and attributes from the secondary input are merged into the primary. This is the common, straightforward way to join when there’s a reliable common identifier. When you join by spatial relationships, features are paired based on how their geometries relate to each other—such as intersecting, being within, containing, touching, or overlapping. This lets you bring in attributes from one dataset to another even if there isn’t a shared key, as long as the spatial relationship holds. Because FME supports both attribute-based joins and spatial-based joins, the statement is true.

FME can combine features using two main approaches: matching by attribute values or matching by spatial relationships. When you join by attribute values, features from two datasets are paired when a chosen key or set of keys (like an ID field) match, and attributes from the secondary input are merged into the primary. This is the common, straightforward way to join when there’s a reliable common identifier.

When you join by spatial relationships, features are paired based on how their geometries relate to each other—such as intersecting, being within, containing, touching, or overlapping. This lets you bring in attributes from one dataset to another even if there isn’t a shared key, as long as the spatial relationship holds.

Because FME supports both attribute-based joins and spatial-based joins, the statement is true.