# Geographic Interoperability Knowledge Base

> Open, versioned, tested documentation for converting geographic geometry to and from H3 and executable ad-platform geography: source -> normalized -> canonical H3 -> executed -> reported. Distances are spherical (haversine); areas in m2; CRS EPSG:4326.

This file follows the llmstxt.org convention. For the whole corpus in one request, fetch https://etherdata.ai/geo-interop-kb/llms-full.txt (markdown) or https://etherdata.ai/geo-interop-kb/kb.json (structured). Each page below is also available as clean markdown at https://etherdata.ai/geo-interop-kb/docs/<slug>.md.

## geometries

- [Administrative Boundaries](https://etherdata.ai/geo-interop-kb/docs/administrative-boundaries.md): The family of governmentally or institutionally defined partitions — country down to school district — and why the id you're handed is never the boundary itself.
- [Arbitrary Polygons](https://etherdata.ai/geo-interop-kb/docs/arbitrary-polygons.md): Operator-drawn or model-generated shapes with no external authority governing their boundary — trade areas, geofences, parcels, and the risks that come from having no ground truth to check against.
- [Bounding Boxes](https://etherdata.ai/geo-interop-kb/docs/bounding-boxes.md): A [west, south, east, north] envelope — a map viewport or query bound, not a shape describing any real-world extent — and the ordering and antimeridian bugs that follow from treating it as one anyway.
- [Geometry Catalogue](https://etherdata.ai/geo-interop-kb/docs/geometry-catalogue.md): An index of every geometry type this knowledge base converts, grouped by category, with the metadata each needs and the single rule that an identifier is never itself a geometry.
- [Lines And Trajectories](https://etherdata.ai/geo-interop-kb/docs/lines-and-trajectories.md): Unordered polylines versus ordered, timestamped position sequences — roads and rivers on one side, device journeys on the other, with very different exposure profiles.
- [Multipoints](https://etherdata.ai/geo-interop-kb/docs/multipoints.md): A collection of independent point observations rather than one coherent shape — bid requests, visits, and conversions aggregated to cells, where duplication and sparsity are the dominant failure modes.
- [Platform Identifiers](https://etherdata.ai/geo-interop-kb/docs/platform-identifiers.md): Opaque or standardized ids — FIPS, ISO, DMA, publisher market codes — that reference a geometry through a versioned crosswalk but are never a geometry themselves. The central case for this catalogue's one recurring warning.
- [Point-Radius Geometries](https://etherdata.ai/geo-interop-kb/docs/point-radius-geometries.md): A center coordinate plus a radius — the native execution unit for most DSPs and proximity products, and the geometry where the buffer method matters as much as the containment rule after it.
- [Points](https://etherdata.ai/geo-interop-kb/docs/points.md): A single coordinate that references a place rather than describing an extent — POIs, addresses, devices, and the uncertainty each one silently carries.
- [Rasters](https://etherdata.ai/geo-interop-kb/docs/rasters.md): Gridded fields — population, elevation, weather, land use, imagery, audience-density surfaces — and the resolution-mismatch problems that surface the moment a fixed pixel grid meets a hexagonal cell grid.

## source-to-h3

- [Administrative Polygon To H3](https://etherdata.ai/geo-interop-kb/docs/administrative-polygon-to-h3.md): Converting counties, states, DMAs, census geographies, and postal areas into H3 cells while preserving the partition property those units are supposed to have.
- [Arbitrary Polygon To H3](https://etherdata.ai/geo-interop-kb/docs/arbitrary-polygon-to-h3.md): The four containment modes for polyfilling any polygon into H3 cells, when to use each, and how to retain overlap for downstream weighting.
- [Bounding Box To H3](https://etherdata.ai/geo-interop-kb/docs/bounding-box-to-h3.md): Normalizing a west/south/east/north bounding box into a valid polygon before polyfilling, and the ordering and wraparound bugs that skip this step invites.
- [Line And Corridor To H3](https://etherdata.ai/geo-interop-kb/docs/line-and-corridor-to-h3.md): Four distinct ways to turn a road segment or device trajectory into H3 cells, and why GPS noise makes the choice consequential.
- [Point To H3](https://etherdata.ai/geo-interop-kb/docs/point-to-h3.md): Point-to-cell containment is exact given a coordinate; the real subject of this page is how uncertain that coordinate usually is.
- [Point-Radius To H3](https://etherdata.ai/geo-interop-kb/docs/point-radius-to-h3.md): Buffering a point into a geodesic disk before polyfilling, and why the buffer method matters as much as the containment rule that follows it.
- [Raster To H3](https://etherdata.ai/geo-interop-kb/docs/raster-to-h3.md): Choosing the correct aggregation statistic when resampling a gridded raster into H3 cells, and why the wrong choice manufactures false precision.

## advertising

- [Advertising Geographic Matching Semantics](https://etherdata.ai/geo-interop-kb/docs/advertising-geographic-matching-semantics.md): Geometry alone does not define who gets targeted; the matching semantic, location source, and lookback window determine the audience as much as the shape does.

## systems

- [Antimeridian Handling](https://etherdata.ai/geo-interop-kb/docs/antimeridian-handling.md): Geometries and circles that cross the ±180° meridian wrap incorrectly under planar longitude math and must be split or unwrapped before any H3 or area operation.
- [Cell System Comparison](https://etherdata.ai/geo-interop-kb/docs/cell-system-comparison.md): A matrix comparison of H3, S2, and Geohash across shape, hierarchy, equal-area, and containment behavior, and why cross-system conversion always goes through polygon union and re-fill.
- [Coordinate And CRS Failures](https://etherdata.ai/geo-interop-kb/docs/coordinate-and-crs-failures.md): Nine recurring data-quality failures in supplied coordinates and boundaries, each with a concrete detection test and mitigation, that must be cleared before any geometry enters the conversion pipeline.
- [Geohash Overview](https://etherdata.ai/geo-interop-kb/docs/geohash-overview.md): Geohash as a system: base-32 prefix strings over a recursively bisected lat/lng rectangle, exact prefix containment, 1-12 character lengths, non-equal-area cells, and no native polygon fill.
- [H3 Overview](https://etherdata.ai/geo-interop-kb/docs/h3-overview.md): H3 as a system: icosahedron projection, aperture-7 hierarchy, 16 resolutions, hexagon-dominant cells with 12 unavoidable pentagons, and logical (not exact) parent-child containment.
- [H3 Pentagons](https://etherdata.ai/geo-interop-kb/docs/h3-pentagons.md): Twelve pentagon cells per H3 resolution sit at the icosahedron vertices and break the six-neighbour, regular-shape assumptions that most H3 code implicitly relies on.
- [S2 Overview](https://etherdata.ai/geo-interop-kb/docs/s2-overview.md): S2 as a system: cube-to-sphere projection, exact quad hierarchy (4 children exactly tile every parent), 31 levels, Hilbert-curve cell IDs, and quadrilateral cells that are not equal-area.

## quality

- [Conversion Conformance Testing](https://etherdata.ai/geo-interop-kb/docs/conversion-conformance-testing.md): Machine-readable fixtures and property-based tests catch the conversions that only fail on pentagons, antimeridian cells, or near-polar geometry rather than on the common case.
- [Conversion Quality Metrics](https://etherdata.ai/geo-interop-kb/docs/conversion-quality-metrics.md): Coverage, overreach, underreach, and Jaccard share the same numerator family but different denominators, so a geometry can score high on one and poorly on another simultaneously.

## concepts

- [Conversion Profiles](https://etherdata.ai/geo-interop-kb/docs/conversion-profiles.md): Seven named profiles bundle a containment rule, resolution policy, circle mode, and weighting into a reusable recipe for a stated intent — they are defaults, not universal answers.
- [Geographic Interoperability Model](https://etherdata.ai/geo-interop-kb/docs/geographic-interoperability-model.md): The six geographies that a single campaign passes through, why they must stay distinct, and why provenance has to survive every conversion.
- [Geometry Normalization](https://etherdata.ai/geo-interop-kb/docs/geometry-normalization.md): Every downstream H3 conversion assumes closed, correctly wound, EPSG 4326 rings with no self-intersections, and normalization is the single gate that must guarantee it.
- [Requested Vs Executed Geography](https://etherdata.ai/geo-interop-kb/docs/requested-vs-executed-geography.md): A campaign geography passes through six distinct forms between the ask and the outcome, and most reporting disputes trace back to two of those forms being silently conflated.
- [Resolution Selection](https://etherdata.ai/geo-interop-kb/docs/resolution-selection.md): Choosing an H3 resolution trades boundary fidelity against inventory size, computation cost, and privacy risk, and the right tradeoff depends on the intent, not on a fixed rule.

## h3-to-execution

- [Google-Style Point-Radius Execution](https://etherdata.ai/geo-interop-kb/docs/google-style-point-radius-execution.md): Executing an H3 cell set on a platform that only accepts many independent point-and-radius targets, one circle per cell
- [H3 Cell Set to Optimized Circle Cover](https://etherdata.ai/geo-interop-kb/docs/optimized-circle-cover.md): A heuristic greedy cover that replaces a target H3 set with fewer point+radius circles under a bounded overreach — experimental, not an optimal solver.
- [H3 To Circumscribed Circle](https://etherdata.ai/geo-interop-kb/docs/h3-to-circumscribed-circle.md): Approximating an H3 cell with the smallest centered disk that fully contains it, guaranteeing coverage at the cost of overlap with neighboring cells
- [H3 To Equal Area Circle](https://etherdata.ai/geo-interop-kb/docs/h3-to-equal-area-circle.md): Approximating an H3 cell with a disk of the same area for reach and planning estimates, with no containment guarantee in either direction
- [H3 To Exact Polygon](https://etherdata.ai/geo-interop-kb/docs/h3-to-exact-polygon.md): Rendering an H3 cell set as its true GeoJSON boundary, with no radius approximation and no area lost or gained
- [H3 To Inscribed Circle](https://etherdata.ai/geo-interop-kb/docs/h3-to-inscribed-circle.md): Approximating an H3 cell with the largest centered disk that stays fully inside it, for platforms that only take a point and a radius

## semantics

- [H3 Compaction And Uncompaction](https://etherdata.ai/geo-interop-kb/docs/h3-compaction-and-uncompaction.md): Losslessly replacing a complete set of sibling cells with their parent, and the exact round-trip property that makes it safe to use for storage and target-count optimization.
- [Inclusion And Exclusion Semantics](https://etherdata.ai/geo-interop-kb/docs/inclusion-and-exclusion-semantics.md): How include and exclude geographies combine into one effective target, and why the combination has to happen in a single normalized cell space before anything else runs.
- [Mixed H3 Resolutions](https://etherdata.ai/geo-interop-kb/docs/mixed-h3-resolutions.md): Why a set containing H3 cells from more than one resolution cannot be compared or subtracted until every cell is normalized to a single resolution.

## crosswalks

- [H3 To Administrative Crosswalk](https://etherdata.ai/geo-interop-kb/docs/h3-to-administrative-crosswalk.md): Preserving every cell-to-region relationship a boundary crossing creates, instead of collapsing a straddling H3 cell to a single administrative owner.
- [H3 To Platform Native Geography](https://etherdata.ai/geo-interop-kb/docs/h3-to-platform-native-geography.md): Mapping H3 cells to the opaque geo IDs a platform actually accepts, and recording the confidence and gaps that mapping introduces.

## platforms

- [Platform Target Count Constraints](https://etherdata.ai/geo-interop-kb/docs/platform-target-count-constraints.md): Every execution platform imposes its own radius floors, target-count ceilings, and unsupported-geometry limits, and an H3 result set must be fitted to them, not assumed compatible.

## privacy

- [Privacy And Minimum Aggregation](https://etherdata.ai/geo-interop-kb/docs/privacy-and-minimum-aggregation.md): Small-cell re-identification and device-trajectory exposure are geometry problems as much as policy problems, and the mitigations are enforceable at the conversion layer.

## Edge cases

- [Edge-case catalogue](https://etherdata.ai/blog/geo-interop-kb/edge-cases) - 93 entries; each at https://etherdata.ai/geo-interop-kb/edge-cases/<id>.md

## Structured data

- [Full KB JSON](https://etherdata.ai/geo-interop-kb/kb.json)
- [Search index](https://etherdata.ai/geo-interop-kb/search-index.json)