geoprimsField-grade geospatial math

One place in every index, at a matched cell size

A point written as an H3 cell, an S2 cell, a geohash, a Plus Code, a map tile, a Maidenhead locator, and an MGRS reference, each at the resolution whose cell is closest to the size you name, with the size it actually has there.

A published result changed on 2026-09-22: The cross-index tool now includes S2, which sits between Maidenhead and MGRS in its list, so the rows after it shift by one. The cell each system reports is unchanged; only the positions in the list moved, and the golden vectors that addressed rows by position were superseded. Changelog

S2

At about 150 m, the closest match is S2.

This place in each system
SystemReferenceResolutionCell size
H38a2a1072b59ffffresolution 10122.7 m
Geohashdr5r7p4precision 7133.1 m
Plus Code87G7MXQ4+8 characters242.2 m
Map tile18/77154/98583 (quadkey 032010110301120232)zoom 18115.9 m
MaidenheadFN20xq458 characters570.9 m
S289c25088dlevel 16140.7 m
MGRS18TWL8070463 digits, 100 m squares100.0 m
Provenance
Computed by
indexing.convert.cross-index 1.0.0, core 0.1.0
Model
For each system, the resolution whose cell size is closest to the target by ratio (log distance), since sizes step by factors; cell size is the side of a square of the same area, computed at this latitude for the systems whose cells are measured in degrees or in Web Mercator
Accuracy
Exact encodings. Cell sizes are that system's own cell at this point, except H3, whose figure is the resolution's average area over the globe.
Notes
None
Cites
Uber Technologies and the H3 contributors, H3: A Hexagonal Hierarchical Geospatial Indexing System (API reference v4); Niemeyer, G., geohash.org, Geohash (public domain algorithm); Google, open-location-code project, Open Location Code: Specification; OpenStreetMap Wiki, Slippy map tilenames

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How we got thisFormula, worked example, sources, and proof

Model: For each system, the resolution whose cell size is closest to the target by ratio (log distance), since sizes step by factors; cell size is the side of a square of the same area, computed at this latitude for the systems whose cells are measured in degrees or in Web Mercator

Accuracy: Exact encodings. Cell sizes are that system's own cell at this point, except H3, whose figure is the resolution's average area over the globe.

When to use this: Use this when data arrives keyed by one index and has to be joined to data keyed by another, or when choosing which system to key by: the same ground is a resolution 10 hexagon, a seven-character geohash, and a zoom 18 tile, and they are not the same size. It also answers what a resolution in one system is worth in another, which is the question behind most cross-dataset joins.

Limitations: No two systems tile the ground the same way, so these are the nearest resolutions rather than equivalents, and the sizes differ by tens of percent. Cells in degrees narrow toward the poles and Web Mercator tiles shrink with the cosine of the latitude, so the same resolutions compare differently at other latitudes. The H3 and S2 figures are their level's average over the globe rather than this cell's own area, since neither grid is equal-area.

Worked example: A place at about 150 m in every system. Source: add-spatial-indexing-and-raster hierarchical-cells scenario: a 150 m target gives geohash precision 7 and H3 resolution 10. It is golden test vector v006, and every build checks the tool still gives its answer within its tolerance.

You enter

Latitude
40.6892 deg
Longitude
-74.0445 deg
Target cell size
150 m

You get

Closest to the target
S2

Review: Not yet independently reviewed by a GIS professional.

Last verified: 2026-09-18, when a maintainer last confirmed this tool's sources at the issuer. See the sources ledger.

Status: version 1.0.0, core 0.1.0. See this tool in the verification report.

Changes

Checked against: 21 golden test vectors (download the test vectors, each with its source and tolerance). See how results are checked and every source.

Sources