How to identify objects related to KD Tree data?
A typical KD tree node contains a reference to the data point.
A KD tree that only keeps the coordinates is much less useful.
This way, you can easily identify them.
I've been studying KD Trees and KNN searching in 2D & 3D space. The thing I cannot seem to find a good explanation of is how to identify which objects are being referenced by each node of the tree. 
Example would be an image comparison database. If you generated descriptors for all the images, would you push all the descriptor data on to one tree? If so, how do you know which nodes are related to which original images? If not, would you generate a tree for each image, and then do some type of KD-Tree Random Forest nearest neighbor queries to determine which trees are closest to each other in 3-D space?
The image example might not be a good use case for KD-Trees since it's highly dimensional space, but I'm more using it to help explain the question I'm asking.
Any guidance on practical applications of KD-Tree KNN queries for comparing objects is greatly appreciated. 
Thanks!