If you wanted to create one dataset containing roads within a certain distance of hospitals, and another containing roads beyond a certain distance of hospitals, what technique would you use?

• A. Spatial joining
• B. Spatial filtering
• C. Buffering
• D. Dissolving

Answer: (B)

This question tests how to partition features based on their distance to another dataset using a spatial filter. To get roads within a chosen distance of hospitals and roads beyond that distance, you first create the distance boundary by buffering the hospital locations. That buffer defines the area inside which roads qualify as “within the distance.” Then run a spatial filter using the roads as the input and the buffered area as the reference geometry. The spatial filter can produce two outputs: roads that fall inside the buffer (within the distance) and roads that lie outside the buffer (beyond the distance). This approach directly yields two datasets from a single workflow. The buffering step defines the distance, while the spatial filter performs the split; buffering alone doesn’t create the split, and the other operations serve different purposes (joining attributes or dissolving features) rather than partitioning by distance.