[pheelicks]

A pentagonal geospatial indexing system: https://a5geo.org/

If you’ve used H3 or S2 it should be familiar, the major difference (apart from the fact it uses pentagons) is that the cell areas are practically uniform, whereas alternative systems have a variance of around 2 between the largest and smallest cells, making them less useful for aggregation. The site has many visual demos, e.g. https://a5geo.org/examples/area

The code is open source: https://github.com/felixpalmer/a5

[stevage]

Wow, that's a really fascinating problem to work on. I work in mapping but haven't actually come across this field of what you call DGGS's.

Is it essential that the cells be the same shape?

Also where does the name "A5" come from exactly? I get that 5 is because it has five sides, but why A?

[pheelicks]

The cells being the same shape is useful in some use cases and irrelevant in others. For example, see the Airbnb demo: https://a5geo.org/examples/airbnb. The H3 tiles are very different sizes in the two cities, and make it appear that there is a much higher density of listings in Malta, even though that is not the case.

However the symmetry of H3’s hexagonal cells lends itself well to flow analysis, or routing - which is no surprise as it was developed at Uber.

As for the name, it follows the convention of S2 and H3, which come from group theory and refer (loosely) to the symmetry groups of the various systems

[westcoast49]

Is it based upon repeated subdivision of an icosahedron?

[pheelicks]

No, it is based on applying a lattice onto the faces of a dodecahedron (technically a pentakis dodecahedron). Take a look at https://a5geo.org/examples/teohedron-dodecahedron and other examples on the website.

H3 is based on a dodecahedron it is it the reason the cell areas range so much, the same is true of S2 - but this is based on a cube.

[westcoast49]

It seems to have merit as a subdivision scheme.

The shapes look a bit wonky when projected onto a map, though, and it may not be as intuitive to reason about as the hexagons that would (mostly) result from subdividing an icosahedron. With a subdivided icosahedron you end up with a regular lattice of shapes that is easier to reason about. I think an icosahedron might be a better fit for an indexing scheme for that reason, despite it's higher mathematical error in approximating the sphere at a given resolution.

I explored a similar idea four or five years ago, without being aware of H3. My goal was to find a compact multi-resolution geospatial height map format. My idea was closer to H3 than to yours, it seems.