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Spatial indices simply partition your data in N-dimensional space the same way a binary tree does it in 1-dimensional space.

The whole advantage over a static partition is that it will allow you to properly deal with data that is irregularly distributed.

Those data structures can definitely be merged if that's what you're asking.

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This data is indeed not irregularly distributed, in fact the fun thing about geospatial data is that you always know the maximum extent of it.

About your binary tree comment: yes this is absolutely valid, but consider then that binary trees also are a bad fit for distributed computing, where data is often partitioned at the top level (making it no longer a binary tree but a set of binary trees) and cross-node joins are expensive.

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