A raster is a gridded field: a value sampled on a regular array of pixels covering some extent, rather than a discrete shape with a boundary. This makes rasters structurally different from every other family in this catalogue — there is no polygon to polyfill, only a continuous surface that must be resampled onto the H3 grid, and the two grids (fixed-size square pixels, roughly-equal-area hexagonal cells) never align exactly. Every raster-to-H3 conversion is therefore a resampling problem before it is anything else, and the resampling method chosen changes the answer as much as the source data does.
- Cardinality
- A continuous surface sampled on a fixed pixel grid, not a discrete shape
- Governed by
- Whichever agency or model produced the surface (WorldPop, NOAA, a vendor model)
- Not a geometry
- A band index or land-cover class code — the surface is the pixel grid itself
- Converts via
- Resampling (nearest, bilinear, or area-weighted) per cell, not polyfilling
Members
| Member | What the surface represents | Typical format |
|---|---|---|
| Population | Gridded population count or density | GeoTIFF (e.g. WorldPop) |
| Elevation | Digital elevation model | GeoTIFF (DEM) |
| Weather | Temperature, precipitation, wind fields | NetCDF, GRIB |
| Pollution | Air-quality index or pollutant concentration | GeoTIFF, NetCDF |
| Land use / land cover | Classified land-cover category per pixel | GeoTIFF (categorical) |
| Flood depth | Modeled inundation depth | GeoTIFF |
| Satellite imagery | Multispectral or RGB reflectance | GeoTIFF, COG |
| Signal strength | Cellular or wireless coverage estimate | GeoTIFF, proprietary grid |
| Audience-density surfaces | Modeled population or audience concentration | GeoTIFF, proprietary grid |
Required metadata
| Field | Why it's required |
|---|---|
| CRS | Rasters are frequently delivered in a projected CRS (UTM, Albers) and must be reprojected before cell alignment |
| Native pixel resolution | Determines whether the raster is finer or coarser than the target H3 resolution, which dictates the correct aggregation method |
| Declared no-data sentinel | A raster's "no data" value (commonly -9999 or similar) must be masked, not averaged in as if it were a real reading |
| Band semantics | What each band represents and its units — a raster with unlabeled bands cannot be aggregated correctly regardless of resolution |
Common risks
Resolution mismatch cuts both ways: a coarse raster (say, 1 km
population pixels) sampled onto fine H3 cells (res 9, ~0.1 km²) produces
false precision — many adjacent cells reporting different values that are
really the same interpolated or repeated pixel value, implying an accuracy
the source data never had. A fine raster (10 m imagery) aggregated onto
coarse cells (res 6) needs area-weighted aggregation across every pixel the
cell covers; averaging without area weighting biases the result toward
whichever pixels happen to be enumerated first. Unmasked no-data
pixels: if the sentinel value isn't filtered before aggregation, it gets
averaged in as if it were a real reading, dragging every statistic (mean,
sum, density) in the sentinel's direction — a -9999 no-data pixel
included in a mean computation produces a wildly wrong, silently plausible
number. Coastal and mixed pixels: pixels straddling land and water, or
straddling two land-cover classes, cannot be cleanly labeled at the pixel
level; forcing a single per-cell category onto a boundary cell instead of
reporting a land-fraction or class-mixture confidence discards real
uncertainty as false certainty. False precision generally: any raster
aggregate reported without a coverage-fraction or valid-pixel-count
alongside it invites readers to trust a number more than the underlying
grid supports.
How it converts to H3
Rasters convert by sampling or aggregating pixel values per cell — nearest, bilinear, or area-weighted-mean depending on the resolution relationship between pixel and cell — documented on raster to H3, including the specific area-weighting algorithm and how to carry a coverage-fraction and valid-pixel-count forward per cell so downstream consumers can see how much of a raster aggregate is real signal versus interpolation. A raster is never converted by extracting contours and polyfilling them as an arbitrary polygon unless the goal is specifically a categorical boundary (e.g. a flood-extent polygon) derived from a threshold on the surface — that is a distinct, lossier operation from full-surface resampling and should be labeled as such.