The world of geospatial indexing has a new entrant that's generating significant interest among developers and data scientists. A5, a recently released global equal-area geospatial indexing system, offers millimeter-accurate precision and promises to address some limitations of existing systems like Google's S2 and Uber's H3.
A Unique Approach to Spatial Indexing
A5 distinguishes itself through its pentagonal tiling approach based on a dodecahedron, unlike the more common approaches used by its competitors. While H3 uses hexagons and S2 uses squares, A5's developers opted for equilateral (but not regular) pentagons. This design choice stems from the dodecahedron being the platonic solid with the lowest vertex curvature, making it the most spherical of all platonic solids and minimizing cell distortion during projection onto a sphere.
The system's primary strength lies in its uniform cell sizes, which maintain equal areas to within 2% across the entire globe. This uniformity eliminates bias when grouping spatial features or analyzing data distribution, a limitation acknowledged in competing systems. The community has noted this is particularly valuable for density analysis applications, as demonstrated in A5's Airbnb distribution example.
Comparative Advantages and Current Limitations
A5 offers extremely high resolution capabilities, with its smallest cells covering less than 30mm² at the final resolution level, all while maintaining a 64-bit integer encoding. This precision exceeds what's available in some existing systems by approximately four orders of magnitude.
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.
However, the system is still in its early stages of development. While established systems like H3 and S2 have robust implementations across multiple programming languages and are integrated into platforms like ClickHouse, A5 currently only offers a TypeScript implementation. The developers have acknowledged this limitation and indicated plans to expand language support, with community members already expressing interest in porting the code to other languages.
Comparison of Major Geospatial Indexing Systems
| System | Base Shape | Key Strength | Current Implementation |
|---|---|---|---|
| A5 | Pentagons (dodecahedron) | Equal-area cells (within 2%), 30mm² precision | TypeScript |
| H3 | Hexagons | Flow analysis, uniform neighbor relationships | Multiple languages, ClickHouse integration |
| S2 | Squares | Exact cell subdivision, geometry simplification | Multiple languages, BigQuery integration |
Finding Its Place in the Ecosystem
The developers of A5 have been clear that their goal isn't to replace existing solutions but rather to provide an alternative with different strengths and trade-offs. While H3 excels at flow analysis due to its single neighbor type, and S2 shines with exact cell subdivision for geometry simplification, A5 positions itself as superior for applications requiring equal-area cells and extremely high precision.
For many visualization applications, the choice between these systems may come down to aesthetic preferences. Some community members have noted that hexagonal systems like H3 are often considered more visually pleasing than square-based systems like S2, and A5's pentagonal approach offers yet another visual alternative.
As A5 continues to mature and expand its language support beyond TypeScript, it will be interesting to see which specific use cases and industries gravitate toward this new approach to geospatial indexing. For now, developers interested in exploring A5 can visit A5Geo.org to access interactive examples and the open-source library, which is available under the Apache 2.0 License.
Reference: A5 - Global, equal-area, millimeter-accurate geospatial index