Doesn the “compression” method described above for representing areas, complicate the text-based spatial searching method?
It does, slightly: in other words, searching for (say) “1000:100” (1 degree square) has to be able to match any of the three cases “1000:***”, “1000:1**” and “1000:100”; searching for “1000:100:1” (0.5 degree square) has to match any of the four cases “1000:***:*”, “1000:1**:*”, “1000:100:*” and “1000:100:1”. Whether such searches can be performed more efficiently than just testing for these four strings individually, has yet to be investigated fully, although it would seem (in principle) amenable to some logic similar to traversing a tree-like structure (suggestions from experienced developers are welcome).
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