geoprimsField-grade geospatial math

H3 cell for a point

The cell containing a latitude and longitude at resolution 0 to 15 (latLngToCell), with the cell's center and area.

Go the other way: H3 cell inspector →

892a8471487ffff

The H3 cell is 892a8471487ffff, about 0.1053 km².

Center latitude
Center longitude
Cell area
Pentagon
Provenance
Computed by
indexing.h3.lat-lng-to-cell 1.0.0, core 0.1.0
Model
H3 v4 (h3o 0.11): gnomonic projection onto icosahedron faces, aperture-7 hexagon hierarchy
Accuracy
Identical indexes to H3 C; coordinates within 1e-12° below 88° latitude, 5e-11° nearer the poles
Notes
None
Cites
Uber Technologies and the H3 contributors, H3: A Hexagonal Hierarchical Geospatial Indexing System (API reference v4); Hydronium Labs, h3o: a Rust implementation of H3

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

Model: H3 v4 (h3o 0.11): gnomonic projection onto icosahedron faces, aperture-7 hexagon hierarchy

Show your work

  1. Resolution

    the cell size the resolution picks, 0 coarsest to 15 finest

    resolution 9 = 0.105332 km² per cell

  2. Cell centre

    the centre of the cell the point falls in

    40.446111°, -79.982222° = 40.444866°, -79.981847°

  3. Cell

    the index of that cell, in hexadecimal

    resolution 9 at 40.446111°, -79.982222° = 892a8471487ffff

The same steps an agent gets from the MCP server with explain: true.

Accuracy: Identical indexes to H3 C; coordinates within 1e-12° below 88° latitude, 5e-11° nearer the poles

When to use this: Use this to put a point on the H3 grid: the cell containing a latitude and longitude at the resolution you choose, with the cell's center and area. It is the entry point for aggregating points into hexagons, joining datasets on a common grid, or keying rows by cell. It is also the join key between datasets that have nothing else in common: two sets of points indexed to the same resolution can be aggregated and compared cell by cell.

Limitations: The cell is an area and the point is somewhere inside it, so aggregation at too coarse a resolution hides real structure and too fine a one scatters it; the resolution chooser helps pick. H3 cells are not equal-area, so counts per cell are not strictly comparable without dividing by each cell's own area. Points on a cell boundary fall into exactly one cell by the library's rule, so a dataset binned at one resolution cannot be re-binned by string manipulation; it has to be indexed again.

Worked example: Pittsburgh at resolution 9. Source: add-spatial-indexing-and-raster scenario: 892a8471487ffff. It is golden test vector v001, and every build checks the tool still gives its answer within its tolerance.

You enter

Latitude
40.446111 deg
Longitude
-79.982222 deg
Resolution
9

You get

Cell
892a8471487ffff
Center latitude
40.444865978°
Center longitude
-79.981846904°
Cell area
0.1053 km²
Pentagon
no

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

Sources

Terms

H3: H3 hexagonal hierarchical index
A global grid of hexagons (and 12 pentagons) at 16 resolutions, each cell about one-seventh the area of its parent, named by a 15-character index. Source: H3 hexagonal index

H3 — H3 hexagonal hierarchical index

A global grid of hexagons (and 12 pentagons) at 16 resolutions, each cell about one-seventh the area of its parent, named by a 15-character index.

Source: H3 hexagonal index