If you’ve used H3 the semantics should be familiar. The biggest differentiator is the fact that cells have exactly the same area globally, for why this matters see: https://a5geo.org/docs/recipes/a5-vs-h3

Since starting the project last year and providing implementations in TypeScript, Python and Rust it’s been great to see a community grow, porting or integrating into DuckDB, QGIS and many more: https://a5geo.org/docs/ecosystem

Central to the flag are 12 five-pointed stars. Take these stars, align them point to point, and you’ll get a dodecahedron - one of the 5 Platonic solids that have fascinated humanity since Ancient Greece.

It's a remarkable coincidence. Many designs were proposed before 1955, including variants with 1 or 15 stars. But only 12 stars create this hidden geometric harmony.

This was built using THREE.js and runs with WebGPU, including on mobile. The code is here: https://github.com/felixpalmer/starsalign

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Getting these backwards is a common frustration, so my vote would be for Lon/lat ordering.

Regardless of which you choose, I find DD to be quite cryptic and it would be nicer to spell out the order, eg parseToLonLat - then the order is clear to the user

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See the following visualizations for an illustration:

https://a5geo.org/examples/area

https://a5geo.org/examples/airbnb

I’m working on my own DGGS, A5, the first (and only) to use pentagons. It offers true equal area cells and a much higher cell fidelity (below 1cm compared to 1m for H3).

I’m looking for contributors to get involved and you seem to have the perfect skill set. It would be amazing to have you join the project :) https://a5geo.org/ https://github.com/felixpalmer/a5

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I actually made a Ask HN about it just today https://news.ycombinator.com/item?id=45091607 but for some reason the HN algorithm never even showed it on the Ask page :/

My strategy going forward is one of "Polyglot Mirroring", namely having the codebase in multiple languages in parallel where changes are mirrored using LLMs. I've brainstormed several ways to describe this, and the term I've come up for this is "Polyglot Mirroring". I'm wondering how that sounds to people?

Does anyone have experience with a similar pattern of development?

I've written more about the technique here: https://a5geo.org/docs/ecosystem/polyglot-mirroring

While it might not be for every project, with the cheap availability and quality of LLMs these days, I think it could be a viable technique going forward.

Comments URL: https://news.ycombinator.com/item?id=45091607

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Not only is this an implementation of the library in a language that is better suited to data science, but there are also many improvements to the underlying A5 grid since the original launch, in particular a true equal area projection, which even accounts for the ellipsoidal shape of the earth. https://a5geo.org/examples/area

To get started, take a look at https://a5geo.org/docs/quickstart/python

Comments URL: https://news.ycombinator.com/item?id=44743461

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As a result, when A5 is used as a spatial index, it will generally not have jumps in the cell index values when querying nearby locations on land

The octahedron has a much higher angular defect (https://en.wikipedia.org/wiki/Angular_defect) than the dodecahedron, and thus when it is projected onto the sphere the cells are warped a lot. So while their areas may be the same, the shapes vary.

This article explains the geometric construction, and how it leads to the cells being a similar size and shape: https://a5geo.org/docs/technical/platonic-solids

Also from a data visualization point of view, the rectangular cells of Healpix (like S2) are arguably less pleasing to look at than hexagons/pentagons: https://h3geo.org/docs/comparisons/s2#visualization

The plan is certainly to release versions in other languages, if you would like to be involved, please get in touch. I agree the porting shouldn't be too difficult, as by design the library has just one simple dependency and the code should translate nicely to other C-style languages

The primary benefit is indeed the ability to treat cells as if they are equal areas. This is something people do currently with H3, but it introduces a bias. Contrary to popular belief, this is not only an issue near the poles or in the ocean.

The other difference is aesthetics, people generally find H3 more pleasing to look at than S2, which is why it gets used in visualization more. You can make the same argument for A5, although of course it is a matter of taste!

Finally, you are correct that H3 was originally developed at Uber for their specific use case, however it has since been used in many other contexts and I think it doesn’t hurt to have some alternatives as conceptually S2/H3/A5 are similar