The PYXIS spatial indexing scheme takes a similar approach, with a few interesting advantages (and undoubtedly some consequent disadvantages to go with them).

The PYXIS spatial indexing scheme takes a similar approach, with a few interesting advantages (and undoubtedly some consequent disadvantages to go with them). http://www.pyxisinnovation.com/pyxwiki/index.php?title=How_PYXIS_Works http://www.pyxisinnovation.com/pyxwiki/index.php?title=How_P... Once you get past the inexplicably florid and fervent language (it's a spatial indexing scheme, guys—not a holy revelation!) there are a couple of cool qualities that stand out to me: - The distribution of indices is very even over the globe. Yes, this scheme is specifically suited to indexing space on a globe, and not much else. - You can be arbitrarily precise by specifying a longer index. Truncating that index just makes it less precise. A major benefit that springs to mind here is the ease with which you could then query for overlapping indices. - Subdividing space by placing child indices at both cell vertices and centroids means there is always overlap between cells at neighbouring resolutions. Whilst this does make the scheme a tad inefficient in terms of storage (which may or may not be the most important detail depending on your application) it has the really neat consequence that any area smaller than a continent is guaranteed to fit wholly within a single index at some resolution. Schemes that avoid overlapping indices or coordinates for the sake of efficiency can never have this property. (I stumbled upon PYXIS while looking for an addressing scheme to rip off for a game project I was working on years ago. Ultimately I decided that PYXIS was not well-suited to my needs and took a much simpler approach, but its novelty stuck it firmly in my mind anyway.)