Investigate suitability of DGGS indexing

[ksonda]

We need to implement a common geospatial index so we can do SPARQL-based stIntersects and stWithin and stContains queries rather than GeoSPARQL over WKT. Per meeting on Aug 1, 2022, DGGS was decided to be investigated

Candidates include:

• h3 (uber, placekey)
• s2 (google)
• rHEALPix , which has some python tooling, eg by NZ Landcare Research and Surround Australia

Considerations include:

• Utility, storage, and performance issues related to what resolution(s) to use, given that our geometries range from HUC2 to points, and also include linear features ranging from ~4000km to <1km
• tooling that makes it easy to index to the dggs on ingest to triple store