s2geometry VS h3

I experimented with geospatial Hilbert Curves as a Postgres extension [0] for PostGIS using the S2 [1] spherical geometry library. S2 uses a scale free cell coverage pattern that is numbered using six interlocking space filling Hilbert Curves [2].

By having both high level (cell) and low level (cell id) geometries it was a very powerful library which allowed projection from the hilbert space into a Postgres spatial index (spgist) including various trees, like noted in this article. It appears to be still quite active in development.

[0] https://github.com/michelp/pgs2

[1] https://s2geometry.io/

[2] https://s2geometry.io/devguide/s2cell_hierarchy

If you check the h3geo comparison page, you should see plenty of alternatives to geohash, such as s2 or even h3 itself.

See some discussion I started at https://github.com/google/s2geometry/issues/190

> It was quite hard for me to find open-source implementations of linear quadtrees.

You probably know this, but the S2 library has one: https://github.com/google/s2geometry

https://s2geometry.io shows how this works

If your points are distributed globally, however, I'd suggest using something like s2geometry (calculates over a sphere instead of an ellipsoid which is much faster + already has something called S2ClosestPointQuery).

Some alternative solutions are S2 from Google and H3 from Uber. These don't have the same issues as geohash because they work on a 3-d model of the geoid and not a 2-d cylindrical projection like Geohash.

It looks like the base Kontur dataset uses H3 resolution 8, and there’s a lookup table here. “400m” seems to refer to the edge length (which averages to 461m).

I can speak to quadtrees, but the primary reason for using this is that you need a geographic "dictionary" (not using the word map to avoid confusion with charts), and you're perhaps already using the H3 hexagonal grid system.

HexSet: is a way of storing a set of H3 cells in a tree, and doing fast (2-20 ns on my 2013 trashcan Mac Pro) membership tests. You must first convert the input data (e.g. GeoJSoN polygon) into H3 cells.

> What an amazing tool that can completely change function names when it converts from C to Go.

How can one read the code of the benchmark, then switch into virulent sarcasm mode without trying to understand the code? And seeing "+1" comments without any effort to understand is also disheartening.

The blog post had a link about the Go helper functions the author used. It lands on https://github.com/akhenakh/goh3/blob/main/h3.go This shows that the `FromGeo()` function used by the Go benchmark is a helper that calls transpiled functions. The benchmark code itself was of course not transpiled, so the sarcasm was unneeded and wrong.

If anyone wants to dig in deeper, the C function `latLngToCell()` calls 2 functions, see https://github.com/uber/h3/blob/master/src/h3lib/lib/h3Index...

Uber just released their library to perform geospatial indexing - https://h3geo.org/. This might be an useful building block for you.